Sample records for internal climate variability

  1. New Perspectives on the Role of Internal Variability in Regional Climate Change and Climate Model Evaluation

    NASA Astrophysics Data System (ADS)

    Deser, C.

    2017-12-01

    Natural climate variability occurs over a wide range of time and space scales as a result of processes intrinsic to the atmosphere, the ocean, and their coupled interactions. Such internally generated climate fluctuations pose significant challenges for the identification of externally forced climate signals such as those driven by volcanic eruptions or anthropogenic increases in greenhouse gases. This challenge is exacerbated for regional climate responses evaluated from short (< 50 years) data records. The limited duration of the observations also places strong constraints on how well the spatial and temporal characteristics of natural climate variability are known, especially on multi-decadal time scales. The observational constraints, in turn, pose challenges for evaluation of climate models, including their representation of internal variability and assessing the accuracy of their responses to natural and anthropogenic radiative forcings. A promising new approach to climate model assessment is the advent of large (10-100 member) "initial-condition" ensembles of climate change simulations with individual models. Such ensembles allow for accurate determination, and straightforward separation, of externally forced climate signals and internal climate variability on regional scales. The range of climate trajectories in a given model ensemble results from the fact that each simulation represents a particular sequence of internal variability superimposed upon a common forced response. This makes clear that nature's single realization is only one of many that could have unfolded. This perspective leads to a rethinking of approaches to climate model evaluation that incorporate observational uncertainty due to limited sampling of internal variability. Illustrative examples across a range of well-known climate phenomena including ENSO, volcanic eruptions, and anthropogenic climate change will be discussed.

  2. An 'Observational Large Ensemble' to compare observed and modeled temperature trend uncertainty due to internal variability.

    NASA Astrophysics Data System (ADS)

    Poppick, A. N.; McKinnon, K. A.; Dunn-Sigouin, E.; Deser, C.

    2017-12-01

    Initial condition climate model ensembles suggest that regional temperature trends can be highly variable on decadal timescales due to characteristics of internal climate variability. Accounting for trend uncertainty due to internal variability is therefore necessary to contextualize recent observed temperature changes. However, while the variability of trends in a climate model ensemble can be evaluated directly (as the spread across ensemble members), internal variability simulated by a climate model may be inconsistent with observations. Observation-based methods for assessing the role of internal variability on trend uncertainty are therefore required. Here, we use a statistical resampling approach to assess trend uncertainty due to internal variability in historical 50-year (1966-2015) winter near-surface air temperature trends over North America. We compare this estimate of trend uncertainty to simulated trend variability in the NCAR CESM1 Large Ensemble (LENS), finding that uncertainty in wintertime temperature trends over North America due to internal variability is largely overestimated by CESM1, on average by a factor of 32%. Our observation-based resampling approach is combined with the forced signal from LENS to produce an 'Observational Large Ensemble' (OLENS). The members of OLENS indicate a range of spatially coherent fields of temperature trends resulting from different sequences of internal variability consistent with observations. The smaller trend variability in OLENS suggests that uncertainty in the historical climate change signal in observations due to internal variability is less than suggested by LENS.

  3. Internal Variability-Generated Uncertainty in East Asian Climate Projections Estimated with 40 CCSM3 Ensembles.

    PubMed

    Yao, Shuai-Lei; Luo, Jing-Jia; Huang, Gang

    2016-01-01

    Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation and surface air temperature (SAT) trends during 2005-2055 over East Asia based on 40 member ensemble projections of the Community Climate System Model Version 3 (CCSM3). The model ensembles are generated from a suite of different atmospheric initial conditions using the same SRES A1B greenhouse gas scenario. We find that projected precipitation trends are subject to considerably larger internal uncertainty and hence have lower confidence, compared to the projected SAT trends in both the boreal winter and summer. Projected SAT trends in winter have relatively higher uncertainty than those in summer. Besides, the lower-level atmospheric circulation has larger uncertainty than that in the mid-level. Based on k-means cluster analysis, we demonstrate that a substantial portion of internally-induced precipitation and SAT trends arises from internal large-scale atmospheric circulation variability. These results highlight the importance of internal climate variability in affecting regional climate projections on multi-decadal timescales.

  4. The CESM Large Ensemble Project: Inspiring New Ideas and Understanding

    NASA Astrophysics Data System (ADS)

    Kay, J. E.; Deser, C.

    2016-12-01

    While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model assessments [e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. In response, the Community Earth System Model (CESM) community designed the CESM Large Ensemble (CESM-LE) with the explicit goal of enabling assessment of climate change in the presence of internal climate variability. All CESM-LE simulations use a single CMIP5 model (CESM with the Community Atmosphere Model, version 5). The core simulations replay the twenty to twenty-first century (1920-2100) 40+ times under historical and representative concentration pathway 8.5 external forcing with small initial condition differences. Two companion 2000+-yr-long preindustrial control simulations (fully coupled, prognostic atmosphere and land only) allow assessment of internal climate variability in the absence of climate change. Comprehensive outputs, including many daily fields, are available as single-variable time series on the Earth System Grid for anyone to use. Examples of scientists and stakeholders that are using the CESM-LE outputs to help interpret the observational record, to understand projection spread and to plan for a range of possible futures influenced by both internal climate variability and forced climate change will be highlighted the presentation.

  5. Assessing the role of internal climate variability in Antarctica's contribution to future sea-level rise

    NASA Astrophysics Data System (ADS)

    Tsai, C. Y.; Forest, C. E.; Pollard, D.

    2017-12-01

    The Antarctic ice sheet (AIS) has the potential to be a major contributor to future sea-level rise (SLR). Current projections of SLR due to AIS mass loss remain highly uncertain. Better understanding of how ice sheets respond to future climate forcing and variability is essential for assessing the long-term risk of SLR. However, the predictability of future climate is limited by uncertainties from emission scenarios, model structural differences, and the internal variability that is inherently generated within the fully coupled climate system. Among those uncertainties, the impact of internal variability on the AIS changes has not been explicitly assessed. In this study, we quantify the effect of internal variability on the AIS evolutions by using climate fields from two large-ensemble experiments using the Community Earth System Model to force a three-dimensional ice sheet model. We find that internal variability of climate fields, particularly atmospheric fields, among ensemble members leads to significantly different AIS responses. Our results show that the internal variability can cause about 80 mm differences of AIS contribution to SLR by 2100 compared to the ensemble-mean contribution of 380-450 mm. Moreover, using ensemble-mean climate fields as the forcing in the ice sheet model does not produce realistic simulations of the ice loss. Instead, it significantly delays the onset of retreat of the West Antarctic Ice Sheet for up to 20 years and significantly underestimates the AIS contribution to SLR by 0.07-0.11 m in 2100 and up to 0.34 m in the 2250's. Therefore, because the uncertainty caused by internal variability is irreducible, we seek to highlight a critical need to assess the role of internal variability in projecting the AIS loss over the next few centuries. By quantifying the impact of internal variability on AIS contribution to SLR, policy makers can obtain more robust estimates of SLR and implement suitable adaptation strategies.

  6. Role of Internal Variability in Surface Temperature and Precipitation Change Uncertainties over India.

    NASA Astrophysics Data System (ADS)

    Achutarao, K. M.; Singh, R.

    2017-12-01

    There are various sources of uncertainty in model projections of future climate change. These include differences in the formulation of climate models, internal variability, and differences in scenarios. Internal variability in a climate system represents the unforced change due to the chaotic nature of the climate system and is considered irreducible (Deser et al., 2012). Internal variability becomes important at regional scales where it can dominate forced changes. Therefore it needs to be carefully assessed in future projections. In this study we segregate the role of internal variability in the future temperature and precipitation projections over the Indian region. We make use of the Coupled Model Inter-comparison Project - phase 5 (CMIP5; Taylor et al., 2012) database containing climate model simulations carried out by various modeling centers around the world. While the CMIP5 experimental protocol recommended producing numerous ensemble members, only a handful of the modeling groups provided multiple realizations. Having a small number of realizations is a limitation in producing a quantification of internal variability. We therefore exploit the Community Earth System Model Large Ensemble (CESM-LE; Kay et al., 2014) dataset which contains a 40 member ensemble of a single model- CESM1 (CAM5) to explore the role of internal variability in Future Projections. Surface air temperature and precipitation change projections over regional and sub-regional scale are analyzed under the IPCC emission scenario (RCP8.5) for different seasons and homogeneous climatic zones over India. We analyze the spread in projections due to internal variability in the CESM-LE and CMIP5 datasets over these regions.

  7. Estimating the impact of internal climate variability on ice sheet model simulations

    NASA Astrophysics Data System (ADS)

    Tsai, C. Y.; Forest, C. E.; Pollard, D.

    2016-12-01

    Rising sea level threatens human societies and coastal habitats and melting ice sheets are a major contributor to sea level rise (SLR). Thus, understanding uncertainty of both forcing and variability within the climate system is essential for assessing long-term risk of SLR given their impact on ice sheet evolution. The predictability of polar climate is limited by uncertainties from the given forcing, the climate model response to this forcing, and the internal variability from feedbacks within the fully coupled climate system. Among those sources of uncertainty, the impact of internal climate variability on ice sheet changes has not yet been robustly assessed. Here we investigate how internal variability affects ice sheet projections using climate fields from two Community Earth System Model (CESM) large-ensemble (LE) experiments to force a three-dimensional ice sheet model. Each ensemble member in an LE experiment undergoes the same external forcings but with unique initial conditions. We find that for both LEs, 2m air temperature variability over Greenland ice sheet (GrIS) can lead to significantly different ice sheet responses. Our results show that the internal variability from two fully coupled CESM LEs can cause about 25 35 mm differences of GrIS's contribution to SLR in 2100 compared to present day (about 20% of the total change), and 100m differences of SLR in 2300. Moreover, only using ensemble-mean climate fields as the forcing in ice sheet model can significantly underestimate the melt of GrIS. As the Arctic region becomes warmer, the role of internal variability is critical given the complex nonlinear interactions between surface temperature and ice sheet. Our results demonstrate that internal variability from coupled atmosphere-ocean general circulation model can affect ice sheet simulations and the resulting sea-level projections. This study highlights an urgent need to reassess associated uncertainties of projecting ice sheet loss over the next few centuries to obtain robust estimates of the contribution of ice sheet melt to SLR.

  8. Uncertainties in Future Regional Sea Level Trends: How to Deal with the Internal Climate Variability?

    NASA Astrophysics Data System (ADS)

    Becker, M.; Karpytchev, M.; Hu, A.; Deser, C.; Lennartz-Sassinek, S.

    2017-12-01

    Today, the Climate models (CM) are the main tools for forecasting sea level rise (SLR) at global and regional scales. The CM forecasts are accompanied by inherent uncertainties. Understanding and reducing these uncertainties is becoming a matter of increasing urgency in order to provide robust estimates of SLR impact on coastal societies, which need sustainable choices of climate adaptation strategy. These CM uncertainties are linked to structural model formulation, initial conditions, emission scenario and internal variability. The internal variability is due to complex non-linear interactions within the Earth Climate System and can induce diverse quasi-periodic oscillatory modes and long-term persistences. To quantify the effects of internal variability, most studies used multi-model ensembles or sea level projections from a single model ran with perturbed initial conditions. However, large ensembles are not generally available, or too small, and computationally expensive. In this study, we use a power-law scaling of sea level fluctuations, as observed in many other geophysical signals and natural systems, which can be used to characterize the internal climate variability. From this specific statistical framework, we (1) use the pre-industrial control run of the National Center for Atmospheric Research Community Climate System Model (NCAR-CCSM) to test the robustness of the power-law scaling hypothesis; (2) employ the power-law statistics as a tool for assessing the spread of regional sea level projections due to the internal climate variability for the 21st century NCAR-CCSM; (3) compare the uncertainties in predicted sea level changes obtained from a NCAR-CCSM multi-member ensemble simulations with estimates derived for power-law processes, and (4) explore the sensitivity of spatial patterns of the internal variability and its effects on regional sea level projections.

  9. Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

    NASA Astrophysics Data System (ADS)

    Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

    2018-06-01

    High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

  10. Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

    NASA Astrophysics Data System (ADS)

    Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

    2017-09-01

    High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

  11. Effects of Ensemble Configuration on Estimates of Regional Climate Uncertainties

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Goldenson, N.; Mauger, G.; Leung, L. R.

    Internal variability in the climate system can contribute substantial uncertainty in climate projections, particularly at regional scales. Internal variability can be quantified using large ensembles of simulations that are identical but for perturbed initial conditions. Here we compare methods for quantifying internal variability. Our study region spans the west coast of North America, which is strongly influenced by El Niño and other large-scale dynamics through their contribution to large-scale internal variability. Using a statistical framework to simultaneously account for multiple sources of uncertainty, we find that internal variability can be quantified consistently using a large ensemble or an ensemble ofmore » opportunity that includes small ensembles from multiple models and climate scenarios. The latter also produce estimates of uncertainty due to model differences. We conclude that projection uncertainties are best assessed using small single-model ensembles from as many model-scenario pairings as computationally feasible, which has implications for ensemble design in large modeling efforts.« less

  12. Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies.

    PubMed

    Fatichi, S; Rimkus, S; Burlando, P; Bordoy, R

    2014-09-15

    Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. Uncovering the Anthropogenic Sea Level Change using an Improved Sea Level Reconstruction for the Indian Ocean

    NASA Astrophysics Data System (ADS)

    Kumar, P.; Hamlington, B.; Thompson, P. R.; Han, W.

    2016-12-01

    Despite having some of the world's most densely populated and vulnerable coastal regions, sea level (SL) variability in the Indian Ocean (IO) has received considerably less attention than the Pacific Ocean. Differentiating the internal variability from the long-term trend in global mean sea level (GMSL) at decadal time-scales is vital for planning and mitigation efforts in the IO region. Understanding the dynamics of internal and anthropogenic SL change is essential for understanding the dynamic pathways that link the IO basin to terrestrial climates world-wide. With a sparse pre-satellite observational record of the IO, the Indo-Pacific internal climate variability is difficult to represent accurately. However, an improved representation of pre-satellite SL variability can be achieved by using a multivariate reconstruction technique. By using cyclostationary empirical orthogonal functions (CSEOFs) that can capture time-varying spatial patterns, gaps in the historical record when observations are sparse are filled using spatial relationships from time periods when the observational network is dense. This reconstruction method combines SL data and sea surface temperature (SST) to create a SL reconstruction that spans a period from 1900 to present, long enough to study climate signals over interannual to decadal time scales. This study aims at estimating the component of SL rise that relates to anthropogenic forcing by identifying and removing the fraction related to internal variability. An improved understanding of how the internal climate variability can affect the IO SL trend and variability, will provide an insight into the future SL changes. It is also important to study links between SL and climate variability in the past to understand how SL will respond to similar climatic events in the future and if this response will be influenced by the changing climate.

  14. The role of internal climate variability for interpreting climate change scenarios

    NASA Astrophysics Data System (ADS)

    Maraun, Douglas

    2013-04-01

    When communicating information on climate change, the use of multi-model ensembles has been advocated to sample uncertainties over a range as wide as possible. To meet the demand for easily accessible results, the ensemble is often summarised by its multi-model mean signal. In rare cases, additional uncertainty measures are given to avoid loosing all information on the ensemble spread, e.g., the highest and lowest projected values. Such approaches, however, disregard the fundamentally different nature of the different types of uncertainties and might cause wrong interpretations and subsequently wrong decisions for adaptation. Whereas scenario and climate model uncertainties are of epistemic nature, i.e., caused by an in principle reducible lack of knowledge, uncertainties due to internal climate variability are aleatory, i.e., inherently stochastic and irreducible. As wisely stated in the proverb "climate is what you expect, weather is what you get", a specific region will experience one stochastic realisation of the climate system, but never exactly the expected climate change signal as given by a multi model mean. Depending on the meteorological variable, region and lead time, the signal might be strong or weak compared to the stochastic component. In cases of a low signal-to-noise ratio, even if the climate change signal is a well defined trend, no trends or even opposite trends might be experienced. Here I propose to use the time of emergence (TOE) to quantify and communicate when climate change trends will exceed the internal variability. The TOE provides a useful measure for end users to assess the time horizon for implementing adaptation measures. Furthermore, internal variability is scale dependent - the more local the scale, the stronger the influence of internal climate variability. Thus investigating the TOE as a function of spatial scale could help to assess the required spatial scale for implementing adaptation measures. I exemplify this proposal with a recently published study on the TOE for mean and heavy precipitation trends in Europe. In some regions trends emerge only late in the 21st century or even later, suggesting that in these regions adaptation to internal variability rather than to climate change is required. Yet in other regions the climate change signal is strong, urging for timely adaptation. Douglas Maraun, When at what scale will trends in European mean and heavy precipitation emerge? Env. Res. Lett., in press, 2013.

  15. Observations of Local Positive Low Cloud Feedback Patterns and Their Role in Internal Variability and Climate Sensitivity

    NASA Astrophysics Data System (ADS)

    Yuan, Tianle; Oreopoulos, Lazaros; Platnick, Steven E.; Meyer, Kerry

    2018-05-01

    Modeling studies have shown that cloud feedbacks are sensitive to the spatial pattern of sea surface temperature (SST) anomalies, while cloud feedbacks themselves strongly influence the magnitude of SST anomalies. Observational counterparts to such patterned interactions are still needed. Here we show that distinct large-scale patterns of SST and low-cloud cover (LCC) emerge naturally from objective analyses of observations and demonstrate their close coupling in a positive local SST-LCC feedback loop that may be important for both internal variability and climate change. The two patterns that explain the maximum amount of covariance between SST and LCC correspond to the Interdecadal Pacific Oscillation and the Atlantic Multidecadal Oscillation, leading modes of multidecadal internal variability. Spatial patterns and time series of SST and LCC anomalies associated with both modes point to a strong positive local SST-LCC feedback. In many current climate models, our analyses suggest that SST-LCC feedback strength is too weak compared to observations. Modeled local SST-LCC feedback strength affects simulated internal variability so that stronger feedback produces more intense and more realistic patterns of internal variability. To the extent that the physics of the local positive SST-LCC feedback inferred from observed climate variability applies to future greenhouse warming, we anticipate significant amount of delayed warming because of SST-LCC feedback when anthropogenic SST warming eventually overwhelm the effects of internal variability that may mute anthropogenic warming over parts of the ocean. We postulate that many climate models may be underestimating both future warming and the magnitude of modeled internal variability because of their weak SST-LCC feedback.

  16. Impacts of climate change and internal climate variability on french rivers streamflows

    NASA Astrophysics Data System (ADS)

    Dayon, Gildas; Boé, Julien; Martin, Eric

    2016-04-01

    The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability of streamflows observed in the 20th century is generally weaker in the hydrological simulations done with the historical simulations from climate models. References: Dayon et al. (2015), Transferability in the future climate of a statistical downscaling mehtod for precipitation in France, J. Geophys. Res. Atmos., 120, 1023-1043, doi:10.1002/2014JD022236

  17. Pronounced differences between observed and CMIP5-simulated multidecadal climate variability in the twentieth century

    NASA Astrophysics Data System (ADS)

    Kravtsov, Sergey

    2017-06-01

    Identification and dynamical attribution of multidecadal climate undulations to either variations in external forcings or to internal sources is one of the most important topics of modern climate science, especially in conjunction with the issue of human-induced global warming. Here we utilize ensembles of twentieth century climate simulations to isolate the forced signal and residual internal variability in a network of observed and modeled climate indices. The observed internal variability so estimated exhibits a pronounced multidecadal mode with a distinctive spatiotemporal signature, which is altogether absent in model simulations. This single mode explains a major fraction of model-data differences over the entire climate index network considered; it may reflect either biases in the models' forced response or models' lack of requisite internal dynamics, or a combination of both.Plain Language SummaryGlobal and regional warming trends over the course of the twentieth century have been nonuniform, with decadal and longer periods of faster or slower warming, or even cooling. Here we show that state-of-the-art global models used to predict climate fail to adequately reproduce such multidecadal climate variations. In particular, the models underestimate the magnitude of the observed variability and misrepresent its spatial pattern. Therefore, our ability to interpret the observed climate change using these models is limited.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A23G0296L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A23G0296L"><span>The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements in Understanding AMOC</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lucas, S. E.</p> <p>2016-12-01</p> <p>The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). This poster will present the recently funded CVP projects on improving the understanding Atlantic Meridional Overturning Circulation (AMOC), its impact on decadal predictability, and its relationship with the overall climate system.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.2369R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.2369R"><span>Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.</p> <p>2018-04-01</p> <p>This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent deep-water formation in the Labrador Sea, resulting in overestimated North Atlantic SST variability. Concerning the influence of locally (isotropically) increased resolution, the ENSO pattern and index statistics improve significantly with higher resolution around the equator, illustrating the potential of the novel unstructured-mesh method for global climate modeling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp.2308Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp.2308Y"><span>On climate prediction: how much can we expect from climate memory?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg</p> <p>2018-03-01</p> <p>Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li class="active"><span>1</span></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_1 --> <div id="page_2" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li class="active"><span>2</span></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="21"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A11N0269L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A11N0269L"><span>The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lucas, S. E.; Todd, J. F.</p> <p>2015-12-01</p> <p>The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). The CVP Program currently supports multiple projects in areas that are aimed at improved representation of physical processes in global models. Some of the topics that are currently funded include: i) Improved Understanding of Intraseasonal Tropical Variability - DYNAMO field campaign and post -field projects, and the new climate model improvement teams focused on MJO processes; ii) Climate Process Teams (CPTs, co-funded with NSF) with projects focused on Cloud macrophysical parameterization and its application to aerosol indirect effects, and Internal-Wave Driven Mixing in Global Ocean Models; iii) Improved Understanding of Tropical Pacific Processes, Biases, and Climatology; iv) Understanding Arctic Sea Ice Mechanism and Predictability;v) AMOC Mechanisms and Decadal Predictability Recent results from CVP-funded projects will be summarized. Additional information can be found at http://cpo.noaa.gov/CVP.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140008676','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140008676"><span>Reply to Comment by Laprise on 'the Added Value to Global Model Projections of Climate Change by Dynamical Downscaling: a Case Study over the Continental U.S. Using the GISS-ModelE2 and WRF Models'</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shindell, Drew Todd; Racherla, Pavan; Milly, George Peter</p> <p>2014-01-01</p> <p>In his comment, Laprise raises several points that we agree merit consideration. His primary critique is that our study [Racherla et al., 2012] tested the ability of the WRF regional climate model to reproduce historical temperature and precipitation change relative to the driving global climate model (GCM) using only a single simulation rather than an ensemble. He asserts that the observed changes are smaller than the internal variability in the climate system (i.e., not statistically significant) and that thus a single simulation should not necessarily be able to capture the observations. Laprise points out that the statistical signal is reduced for a multi-decadal trend such as the one we analyzed in comparison with mean climatology and cites two studies showing that for particular climate parameters it can take any years for a signal to be discerned over internal variability. He states that The results of theexperiment as designed were strongly influenced by the presence of internal variability and sampling errors,which masked the rather small climate changes that may have occurred as a consequence of changes inforcing during the period considered. While Laprise discusses statistics in general terms at some length, for the actual climate trends examined in our study, he offers no evidence that the forced signal was smallcompared with internal variability. The two studies he cites [de Ela et al., 2013; Maraun, 2013] do not provide convincing evidence as they concern climate variables averaged over different times and areas. One in fact examines extreme precipitation events, which by definition are rare and thus have a lower significance level. We accept the general point that it is important to consider internal variability, and as noted in our paper we agree that an ensemble of simulations is in principle an optimal, though computationally expensive, approach. While we did not present the statistical significance of the observations in our original paper, we have now evaluated those for the regional temperature trends used in our study to evaluate the added value of WRF and thus can analyze data as to the magnitude of the trends with respect to internal variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ERL....12k4003M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ERL....12k4003M"><span>Impact of internal variability on projections of Sahel precipitation change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Monerie, Paul-Arthur; Sanchez-Gomez, Emilia; Pohl, Benjamin; Robson, Jon; Dong, Buwen</p> <p>2017-11-01</p> <p>The impact of the increase of greenhouse gases on Sahelian precipitation is very uncertain in both its spatial pattern and magnitude. In particular, the relative importance of internal variability versus external forcings depends on the time horizon considered in the climate projection. In this study we address the respective roles of the internal climate variability versus external forcings on Sahelian precipitation by using the data from the CESM Large Ensemble Project, which consists of a 40 member ensemble performed with the CESM1-CAM5 coupled model for the period 1920-2100. We show that CESM1-CAM5 is able to simulate the mean and interannual variability of Sahel precipitation, and is representative of a CMIP5 ensemble of simulations (i.e. it simulates the same pattern of precipitation change along with equivalent magnitude and seasonal cycle changes as the CMIP5 ensemble mean). However, CESM1-CAM5 underestimates the long-term decadal variability in Sahel precipitation. For short-term (2010-2049) and mid-term (2030-2069) projections the simulated internal variability component is able to obscure the projected impact of the external forcing. For long-term (2060-2099) projections external forcing induced change becomes stronger than simulated internal variability. Precipitation changes are found to be more robust over the central Sahel than over the western Sahel, where climate change effects struggle to emerge. Ten (thirty) members are needed to separate the 10 year averaged forced response from climate internal variability response in the western Sahel for a long-term (short-term) horizon. Over the central Sahel two members (ten members) are needed for a long-term (short-term) horizon.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PalOc..31..286K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PalOc..31..286K"><span>Testing competing forms of the Milankovitch hypothesis: A multivariate approach</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kaufmann, Robert K.; Juselius, Katarina</p> <p>2016-02-01</p> <p>We test competing forms of the Milankovitch hypothesis by estimating the coefficients and diagnostic statistics for a cointegrated vector autoregressive model that includes 10 climate variables and four exogenous variables for solar insolation. The estimates are consistent with the physical mechanisms postulated to drive glacial cycles. They show that the climate variables are driven partly by solar insolation, determining the timing and magnitude of glaciations and terminations, and partly by internal feedback dynamics, pushing the climate variables away from equilibrium. We argue that the latter is consistent with a weak form of the Milankovitch hypothesis and that it should be restated as follows: internal climate dynamics impose perturbations on glacial cycles that are driven by solar insolation. Our results show that these perturbations are likely caused by slow adjustment between land ice volume and solar insolation. The estimated adjustment dynamics show that solar insolation affects an array of climate variables other than ice volume, each at a unique rate. This implies that previous efforts to test the strong form of the Milankovitch hypothesis by examining the relationship between solar insolation and a single climate variable are likely to suffer from omitted variable bias.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSPO44A3119H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSPO44A3119H"><span>Forced Atlantic Multidecadal Variability Over the Past Millennium</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Halloran, P. R.; Reynolds, D.; Scourse, J. D.; Hall, I. R.</p> <p>2016-02-01</p> <p>Paul R. Halloran, David J. Reynolds, Ian R. Hall and James D. Scourse Multidecadal variability in Atlantic sea surface temperatures (SSTs) plays a first order role in determining regional atmospheric circulation and moisture transport, with major climatic consequences. These regional climate impacts range from drought in the Sahel and South America, though increased hurricane activity and temperature extremes, to modified monsoonal rainfall. Multidecadal Atlantic SST variability could arise through internal variability in the Atlantic Meridional Overturning Circulation (AMOC) (e.g., Knight et al., 2006), or through externally forced change (e.g. Booth et al., 2012). It is critical that we know whether internal or external forcing dominates if we are to provide useful near-term climate projections in the Atlantic region. A persuasive argument that internal variability plays an important role in Atlantic Multidecadal Variability is that periodic SST variability has been observed throughout much of the last millennium (Mann et al., 2009), and the hypothesized external forcing of historical Atlantic Multidecadal Variability (Booth et al., 2012) is largely anthropogenic in origin. Here we combine the first annually-resolved millennial marine reconstruction with multi-model analysis, to show that the Atlantic SST variability of the last millennium can be explained by a combination of direct volcanic forcing, and indirect, forced, AMOC variability. Our results indicate that whilst climate models capture the timing of both the directly forced SST and forced AMOC-mediated SST variability, the models fail to capture the magnitude of the forced AMOC change. Does this mean that models underestimate the 21st century reduction in AMOC strength? J. Knight, C. Folland and A. Scaife., Climate impacts of the Atlantic Multidecadal Oscillation, GRL, 2006 B.B.B Booth, N. Dunstone, P.R. Halloran et al., Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability, Nature, 2012 M.E. Mann, Z. Zhang, S. Rutherford et al., Global Signatures and Dynamical Origins of the Little Ice Age and Medieval Climate Anomaly, Science, 2009</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4412608','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4412608"><span>Climate Variability and Human Migration in the Netherlands, 1865–1937</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Jennings, Julia A.; Gray, Clark L.</p> <p>2014-01-01</p> <p>Human migration is frequently cited as a potential social outcome of climate change and variability, and these effects are often assumed to be stronger in the past when economies were less developed and markets more localized. Yet, few studies have used historical data to test the relationship between climate and migration directly. In addition, the results of recent studies that link demographic and climate data are not consistent with conventional narratives of displacement responses. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate data that cover the same period, we examine the effects of climate variability on migration using event history models. Only internal moves in the later period and for certain social groups are associated with negative climate conditions, and the strength and direction of the observed effects change over time. International moves decrease with extreme rainfall, suggesting that the complex relationships between climate and migration that have been observed for contemporary populations extend into the nineteenth century. PMID:25937689</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=300912&keyword=mit&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50','EPA-EIMS'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=300912&keyword=mit&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50"><span>Evaluating the Contribution of Natural Variability and Climate Model Response to Uncertainty in Projections of Climate Change Impacts on U.S. Air Quality</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p>We examine the effects of internal variability and model response in projections of climate impacts on U.S. ground-level ozone across the 21st century using integrated global system modeling and global atmospheric chemistry simulations. The impact of climate change on air polluti...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70157133','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70157133"><span>Climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Cronin, Thomas M.</p> <p>2016-01-01</p> <p>Climate change (including climate variability) refers to regional or global changes in mean climate state or in patterns of climate variability over decades to millions of years often identified using statistical methods and sometimes referred to as changes in long-term weather conditions (IPCC, 2012). Climate is influenced by changes in continent-ocean configurations due to plate tectonic processes, variations in Earth’s orbit, axial tilt and precession, atmospheric greenhouse gas (GHG) concentrations, solar variability, volcanism, internal variability resulting from interactions between the atmosphere, oceans and ice (glaciers, small ice caps, ice sheets, and sea ice), and anthropogenic activities such as greenhouse gas emissions and land use and their effects on carbon cycling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5400366','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5400366"><span>Domestic and International Climate Migration from Rural Mexico</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Nawrotzki, Raphael J.; Runfola, Daniel M.; Hunter, Lori M.; Riosmena, Fernando</p> <p>2016-01-01</p> <p>Evidence is increasing that climate change and variability may influence human migration patterns. However, there is less agreement regarding the type of migration streams most strongly impacted. This study tests whether climate change more strongly impacted international compared to domestic migration from rural Mexico during 1986-99. We employ eight temperature and precipitation-based climate change indices linked to detailed migration histories obtained from the Mexican Migration Project. Results from multilevel discrete-time event-history models challenge the assumption that climate-related migration will be predominantly short distance and domestic, but instead show that climate change more strongly impacted international moves from rural Mexico. The stronger climate impact on international migration may be explained by the self-insurance function of international migration, the presence of strong migrant networks, and climate-related changes in wage difference. While a warming in temperature increased international outmigration, higher levels of precipitation declined the odds of an international move. PMID:28439146</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28439146','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28439146"><span>Domestic and International Climate Migration from Rural Mexico.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Nawrotzki, Raphael J; Runfola, Daniel M; Hunter, Lori M; Riosmena, Fernando</p> <p>2016-12-01</p> <p>Evidence is increasing that climate change and variability may influence human migration patterns. However, there is less agreement regarding the type of migration streams most strongly impacted. This study tests whether climate change more strongly impacted international compared to domestic migration from rural Mexico during 1986-99. We employ eight temperature and precipitation-based climate change indices linked to detailed migration histories obtained from the Mexican Migration Project. Results from multilevel discrete-time event-history models challenge the assumption that climate-related migration will be predominantly short distance and domestic, but instead show that climate change more strongly impacted international moves from rural Mexico. The stronger climate impact on international migration may be explained by the self-insurance function of international migration, the presence of strong migrant networks, and climate-related changes in wage difference. While a warming in temperature increased international outmigration, higher levels of precipitation declined the odds of an international move.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1815843H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1815843H"><span>Bias and robustness of uncertainty components estimates in transient climate projections</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hingray, Benoit; Blanchet, Juliette; Jean-Philippe, Vidal</p> <p>2016-04-01</p> <p>A critical issue in climate change studies is the estimation of uncertainties in projections along with the contribution of the different uncertainty sources, including scenario uncertainty, the different components of model uncertainty and internal variability. Quantifying the different uncertainty sources faces actually different problems. For instance and for the sake of simplicity, an estimate of model uncertainty is classically obtained from the empirical variance of the climate responses obtained for the different modeling chains. These estimates are however biased. Another difficulty arises from the limited number of members that are classically available for most modeling chains. In this case, the climate response of one given chain and the effect of its internal variability may be actually difficult if not impossible to separate. The estimate of scenario uncertainty, model uncertainty and internal variability components are thus likely to be not really robust. We explore the importance of the bias and the robustness of the estimates for two classical Analysis of Variance (ANOVA) approaches: a Single Time approach (STANOVA), based on the only data available for the considered projection lead time and a time series based approach (QEANOVA), which assumes quasi-ergodicity of climate outputs over the whole available climate simulation period (Hingray and Saïd, 2014). We explore both issues for a simple but classical configuration where uncertainties in projections are composed of two single sources: model uncertainty and internal climate variability. The bias in model uncertainty estimates is explored from theoretical expressions of unbiased estimators developed for both ANOVA approaches. The robustness of uncertainty estimates is explored for multiple synthetic ensembles of time series projections generated with MonteCarlo simulations. For both ANOVA approaches, when the empirical variance of climate responses is used to estimate model uncertainty, the bias is always positive. It can be especially high with STANOVA. In the most critical configurations, when the number of members available for each modeling chain is small (< 3) and when internal variability explains most of total uncertainty variance (75% or more), the overestimation is higher than 100% of the true model uncertainty variance. The bias can be considerably reduced with a time series ANOVA approach, owing to the multiple time steps accounted for. The longer the transient time period used for the analysis, the larger the reduction. When a quasi-ergodic ANOVA approach is applied to decadal data for the whole 1980-2100 period, the bias is reduced by a factor 2.5 to 20 depending on the projection lead time. In all cases, the bias is likely to be not negligible for a large number of climate impact studies resulting in a likely large overestimation of the contribution of model uncertainty to total variance. For both approaches, the robustness of all uncertainty estimates is higher when more members are available, when internal variability is smaller and/or the response-to-uncertainty ratio is higher. QEANOVA estimates are much more robust than STANOVA ones: QEANOVA simulated confidence intervals are roughly 3 to 5 times smaller than STANOVA ones. Excepted for STANOVA when less than 3 members is available, the robustness is rather high for total uncertainty and moderate for internal variability estimates. For model uncertainty or response-to-uncertainty ratio estimates, the robustness is conversely low for QEANOVA to very low for STANOVA. In the most critical configurations (small number of member, large internal variability), large over- or underestimation of uncertainty components is very thus likely. To propose relevant uncertainty analyses and avoid misleading interpretations, estimates of uncertainty components should be therefore bias corrected and ideally come with estimates of their robustness. This work is part of the COMPLEX Project (European Collaborative Project FP7-ENV-2012 number: 308601; http://www.complex.ac.uk/). Hingray, B., Saïd, M., 2014. Partitioning internal variability and model uncertainty components in a multimodel multireplicate ensemble of climate projections. J.Climate. doi:10.1175/JCLI-D-13-00629.1 Hingray, B., Blanchet, J. (revision) Unbiased estimators for uncertainty components in transient climate projections. J. Climate Hingray, B., Blanchet, J., Vidal, J.P. (revision) Robustness of uncertainty components estimates in climate projections. J.Climate</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29170567','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29170567"><span>Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J</p> <p>2018-01-01</p> <p>Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29374176','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29374176"><span>Decadal climate predictability in the southern Indian Ocean captured by SINTEX-F using a simple SST-nudging scheme.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Morioka, Yushi; Doi, Takeshi; Behera, Swadhin K</p> <p>2018-01-26</p> <p>Decadal climate variability in the southern Indian Ocean has great influences on southern African climate through modulation of atmospheric circulation. Although many efforts have been made to understanding physical mechanisms, predictability of the decadal climate variability, in particular, the internally generated variability independent from external atmospheric forcing, remains poorly understood. This study investigates predictability of the decadal climate variability in the southern Indian Ocean using a coupled general circulation model, called SINTEX-F. The ensemble members of the decadal reforecast experiments were initialized with a simple sea surface temperature (SST) nudging scheme. The observed positive and negative peaks during late 1990s and late 2000s are well reproduced in the reforecast experiments initiated from 1994 and 1999, respectively. The experiments initiated from 1994 successfully capture warm SST and high sea level pressure anomalies propagating from the South Atlantic to the southern Indian Ocean. Also, the other experiments initiated from 1999 skillfully predict phase change from a positive to negative peak. These results suggest that the SST-nudging initialization has the essence to capture the predictability of the internally generated decadal climate variability in the southern Indian Ocean.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1427767','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1427767"><span>Role of Perturbing Ocean Initial Condition in Simulated Regional Sea Level Change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Hu, Aixue; Meehl, Gerald; Stammer, Detlef</p> <p></p> <p>Multiple lines of observational evidence indicate that the global climate has been getting warmer since the early 20th century. This warmer climate has led to a global mean sea level rise of about 18 cm during the 20th century, and over 6 cm for the first 15 years of the 21st century. Regionally the sea level rise is not uniform due in large part to internal climate variability. To better serve the community, the uncertainties of predicting/projecting regional sea level changes associated with internal climate variability need to be quantified. Previous research on this topic has used single-model large ensemblesmore » with perturbed atmospheric initial conditions (ICs). Here we compare uncertainties associated with perturbing ICs in just the atmosphere and just the ocean using a state-of-the-art coupled climate model. We find that by perturbing the oceanic ICs, the uncertainties in regional sea level changes increase compared to those with perturbed atmospheric ICs. In order for us to better assess the full spectrum of the impacts of such internal climate variability on regional and global sea level rise, approaches that involve perturbing both atmospheric and oceanic initial conditions are thus necessary.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1427767-role-perturbing-ocean-initial-condition-simulated-regional-sea-level-change','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1427767-role-perturbing-ocean-initial-condition-simulated-regional-sea-level-change"><span>Role of Perturbing Ocean Initial Condition in Simulated Regional Sea Level Change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Hu, Aixue; Meehl, Gerald; Stammer, Detlef; ...</p> <p>2017-06-05</p> <p>Multiple lines of observational evidence indicate that the global climate has been getting warmer since the early 20th century. This warmer climate has led to a global mean sea level rise of about 18 cm during the 20th century, and over 6 cm for the first 15 years of the 21st century. Regionally the sea level rise is not uniform due in large part to internal climate variability. To better serve the community, the uncertainties of predicting/projecting regional sea level changes associated with internal climate variability need to be quantified. Previous research on this topic has used single-model large ensemblesmore » with perturbed atmospheric initial conditions (ICs). Here we compare uncertainties associated with perturbing ICs in just the atmosphere and just the ocean using a state-of-the-art coupled climate model. We find that by perturbing the oceanic ICs, the uncertainties in regional sea level changes increase compared to those with perturbed atmospheric ICs. In order for us to better assess the full spectrum of the impacts of such internal climate variability on regional and global sea level rise, approaches that involve perturbing both atmospheric and oceanic initial conditions are thus necessary.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1328543-spatial-patterns-sea-level-variability-associated-natural-internal-climate-modes','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1328543-spatial-patterns-sea-level-variability-associated-natural-internal-climate-modes"><span>Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef</p> <p></p> <p>Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1328543-spatial-patterns-sea-level-variability-associated-natural-internal-climate-modes','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1328543-spatial-patterns-sea-level-variability-associated-natural-internal-climate-modes"><span>Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; ...</p> <p>2016-10-04</p> <p>Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017SGeo...38..217H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017SGeo...38..217H"><span>Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; Hu, Aixue; Hamlington, Benjamin; Kenigson, Jessica; Palanisamy, Hindumathi; Thompson, Philip</p> <p>2017-01-01</p> <p>Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth's climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modes and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this paper, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMPA24A..04O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMPA24A..04O"><span>Human Responses to Climate Variability: The Case of South Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Oppenheimer, M.; Licker, R.; Mastrorillo, M.; Bohra-Mishra, P.; Estes, L. D.; Cai, R.</p> <p>2014-12-01</p> <p>Climate variability has been associated with a range of societal and individual outcomes including migration, violent conflict, changes in labor productivity, and health impacts. Some of these may be direct responses to changes in mean temperature or precipitation or extreme events, such as displacement of human populations by tropical cyclones. Others may be mediated by a variety of biological, social, or ecological factors such as migration in response to long-term changes in crops yields. Research is beginning to elucidate and distinguish the many channels through which climate variability may influence human behavior (ranging from the individual to the collective, societal level) in order to better understand how to improve resilience in the face of current variability as well as future climate change. Using a variety of data sets from South Africa, we show how climate variability has influenced internal (within country) migration in recent history. We focus on South Africa as it is a country with high levels of internal migration and dramatic temperature and precipitation changes projected for the 21st century. High poverty rates and significant levels of rain-fed, smallholder agriculture leave large portions of South Africa's population base vulnerable to future climate change. In this study, we utilize two complementary statistical models - one micro-level model, driven by individual and household level survey data, and one macro-level model, driven by national census statistics. In both models, we consider the effect of climate on migration both directly (with gridded climate reanalysis data) and indirectly (with agricultural production statistics). With our historical analyses of climate variability, we gain insights into how the migration decisions of South Africans may be influenced by future climate change. We also offer perspective on the utility of micro and macro level approaches in the study of climate change and human migration.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H43D1670D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H43D1670D"><span>Improve projections of changes in southern African summer rainfall through comprehensive multi-timescale empirical statistical downscaling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dieppois, B.; Pohl, B.; Eden, J.; Crétat, J.; Rouault, M.; Keenlyside, N.; New, M. G.</p> <p>2017-12-01</p> <p>The water management community has hitherto neglected or underestimated many of the uncertainties in climate impact scenarios, in particular, uncertainties associated with decadal climate variability. Uncertainty in the state-of-the-art global climate models (GCMs) is time-scale-dependant, e.g. stronger at decadal than at interannual timescales, in response to the different parameterizations and to internal climate variability. In addition, non-stationarity in statistical downscaling is widely recognized as a key problem, in which time-scale dependency of predictors plays an important role. As with global climate modelling, therefore, the selection of downscaling methods must proceed with caution to avoid unintended consequences of over-correcting the noise in GCMs (e.g. interpreting internal climate variability as a model bias). GCM outputs from the Coupled Model Intercomparison Project 5 (CMIP5) have therefore first been selected based on their ability to reproduce southern African summer rainfall variability and their teleconnections with Pacific sea-surface temperature across the dominant timescales. In observations, southern African summer rainfall has recently been shown to exhibit significant periodicities at the interannual timescale (2-8 years), quasi-decadal (8-13 years) and inter-decadal (15-28 years) timescales, which can be interpret as the signature of ENSO, the IPO, and the PDO over the region. Most of CMIP5 GCMs underestimate southern African summer rainfall variability and their teleconnections with Pacific SSTs at these three timescales. In addition, according to a more in-depth analysis of historical and pi-control runs, this bias is might result from internal climate variability in some of the CMIP5 GCMs, suggesting potential for bias-corrected prediction based empirical statistical downscaling. A multi-timescale regression based downscaling procedure, which determines the predictors across the different timescales, has thus been used to simulate southern African summer rainfall. This multi-timescale procedure shows much better skills in simulating decadal timescales of variability compared to commonly used statistical downscaling approaches.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li class="active"><span>2</span></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_2 --> <div id="page_3" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active"><span>3</span></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="41"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.2487W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.2487W"><span>Disentangling Global Warming, Multidecadal Variability, and El Niño in Pacific Temperatures</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wills, Robert C.; Schneider, Tapio; Wallace, John M.; Battisti, David S.; Hartmann, Dennis L.</p> <p>2018-03-01</p> <p>A key challenge in climate science is to separate observed temperature changes into components due to internal variability and responses to external forcing. Extended integrations of forced and unforced climate models are often used for this purpose. Here we demonstrate a novel method to separate modes of internal variability from global warming based on differences in time scale and spatial pattern, without relying on climate models. We identify uncorrelated components of Pacific sea surface temperature variability due to global warming, the Pacific Decadal Oscillation (PDO), and the El Niño-Southern Oscillation (ENSO). Our results give statistical representations of PDO and ENSO that are consistent with their being separate processes, operating on different time scales, but are otherwise consistent with canonical definitions. We isolate the multidecadal variability of the PDO and find that it is confined to midlatitudes; tropical sea surface temperatures and their teleconnections mix in higher-frequency variability. This implies that midlatitude PDO anomalies are more persistent than previously thought.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy..tmp..785K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy..tmp..785K"><span>Intercomparison of model response and internal variability across climate model ensembles</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kumar, Devashish; Ganguly, Auroop R.</p> <p>2017-10-01</p> <p>Characterization of climate uncertainty at regional scales over near-term planning horizons (0-30 years) is crucial for climate adaptation. Climate internal variability (CIV) dominates climate uncertainty over decadal prediction horizons at stakeholders' scales (regional to local). In the literature, CIV has been characterized indirectly using projections of climate change from multi-model ensembles (MME) instead of directly using projections from multiple initial condition ensembles (MICE), primarily because adequate number of initial condition (IC) runs were not available for any climate model. Nevertheless, the recent availability of significant number of IC runs from one climate model allows for the first time to characterize CIV directly from climate model projections and perform a sensitivity analysis to study the dominance of CIV compared to model response variability (MRV). Here, we measure relative agreement (a dimensionless number with values ranging between 0 and 1, inclusive; a high value indicates less variability and vice versa) among MME and MICE and find that CIV is lower than MRV for all projection time horizons and spatial resolutions for precipitation and temperature. However, CIV exhibits greater dominance over MRV for seasonal and annual mean precipitation at higher latitudes where signals of climate change are expected to emerge sooner. Furthermore, precipitation exhibits large uncertainties and a rapid decline in relative agreement from global to continental, regional, or local scales for MICE compared to MME. The fractional contribution of uncertainty due to CIV is invariant for precipitation and decreases for temperature as lead time progresses towards the end of the century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A23F2435L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A23F2435L"><span>The Climate Variability & Predictability (CVP) Program at NOAA - Observing and Understanding Processes Affecting the Propagation of Intraseasonal Oscillations in the Maritime Continent Region</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lucas, S. E.</p> <p>2017-12-01</p> <p>The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). In 2017, the CVP Program had a call for proposals focused on observing and understanding processes affecting the propagation of intraseasonal oscillations in the Maritime Continent region. This poster will present the recently funded CVP projects, the expected scientific outcomes, the geographic areas of their work in the Maritime Continent region, and the collaborations with the Office of Naval Research, Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and other partners.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26563765','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26563765"><span>The Role of Individual Differences and Situational Variables in the Use of Workplace Sexual Identity Management Strategies.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Reed, Louren; Leuty, Melanie E</p> <p>2016-07-01</p> <p>Examination of individual difference variables have been largely ignored within research on the use of workplace sexual identity management strategies. The current study examined personality traits (extraversion, openness, and neuroticism), facets of sexual identity development (identity confusion, internalized heterosexism), and situational variables (e.g., perceptions of workplace climate and heterosexism) in explaining the use of management strategies, as well as possible interactions between individual and situational factors. Perceptions of the workplace climate toward lesbian and gay individuals significantly related to the use each of the management strategies, and Internalized Heterosexism was found to significantly predict the use of the Explicitly Out strategy. Most interactions between individual difference and situational variables were not supported, with the exception of an interaction between workplace heterosexism and internalized homophobia in explaining the use of the Explicitly Out strategy.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27092012','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27092012"><span>Country-Specific Effects of Climate Variability on Human Migration.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gray, Clark; Wise, Erika</p> <p>2016-04-01</p> <p>Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC31F1173L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC31F1173L"><span>Signal to noise quantification of regional climate projections</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, S.; Rupp, D. E.; Mote, P.</p> <p>2016-12-01</p> <p>One of the biggest challenges in interpreting climate model outputs for impacts studies and adaptation planning is understanding the sources of disagreement among models (which is often used imperfectly as a stand-in for system uncertainty). Internal variability is a primary source of uncertainty in climate projections, especially for precipitation, for which models disagree about even the sign of changes in large areas like the continental US. Taking advantage of a large initial-condition ensemble of regional climate simulations, this study quantifies the magnitude of changes forced by increasing greenhouse gas concentrations relative to internal variability. Results come from a large initial-condition ensemble of regional climate model simulations generated by weather@home, a citizen science computing platform, where the western United States climate was simulated for the recent past (1985-2014) and future (2030-2059) using a 25-km horizontal resolution regional climate model (HadRM3P) nested in global atmospheric model (HadAM3P). We quantify grid point level signal-to-noise not just in temperature and precipitation responses, but also the energy and moisture flux terms that are related to temperature and precipitation responses, to provide important insights regarding uncertainty in climate change projections at local and regional scales. These results will aid modelers in determining appropriate ensemble sizes for different climate variables and help users of climate model output with interpreting climate model projections.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A51O..05A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A51O..05A"><span>The Interplay of Internal and Forced Modes of Hadley Cell Expansion: Lessons from the Global Warming Hiatus</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Amaya, D. J.; Siler, N.; Xie, S. P.; Miller, A. J.</p> <p>2017-12-01</p> <p>The poleward branches of the Hadley Cells show a robust shift poleward shift during the satellite era, leading to concerns over the possible encroachment of the globe's subtropical dry zones into currently temperate climates. The extent to which this trend is caused by anthropogenic forcing versus internal variability remains the subject of considerable debate. In this study, we us a joint EOF method to identify two distinct modes of Hadley Cell variability: (i) an anthropogenically-forced mode, which we identify using a 20-member simulation of the historical climate, and (ii) an internal mode, which identify using a 1000-year pre-industrial control simulation with a global climate model. The forced mode is found to be closely related to the TOA radiative imbalance and exhibits a long-term trend since 1860, while the internal mode is found to be essentially indistinguishable from the El Niño Southern Oscillation (ENSO). Together these two modes explain an average of 70% of the interannual variability seen in model "edge indices" over the historical period. Since 1980, the superposition of forced and internal modes has resulted in a period of accelerated Hadley Cell expansion and decelerated global warming (i.e., the "hiatus"). A comparison of the change in these modes since 1980 indicates that by 2013 the signal has emerged above the noise of internal variability in the Southern Hemisphere (SH), but not in the Northern Hemisphere (NH), with the latter also exhibiting strong zonal asymmetry, particularly in the North Atlantic. Our results highlight the important interplay of internal and forced modes of Hadley Cell width change and improve our understanding of the interannual variability and long-term trend seen in observations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1918904Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1918904Z"><span>Statistical structure of intrinsic climate variability under global warming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhu, Xiuhua; Bye, John; Fraedrich, Klaus</p> <p>2017-04-01</p> <p>Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A31F0167L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A31F0167L"><span>The Climate Variability & Predictability (CVP) Program at NOAA - DYNAMO Recent Project Advancements</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lucas, S. E.; Todd, J. F.; Higgins, W.</p> <p>2013-12-01</p> <p>The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International Geosphere-Biosphere Programme (IGBP), and the U.S. Global Change Research Program (USGCRP). The CVP program sits within the Earth System Science (ESS) Division at NOAA's Climate Program Office. Dynamics of the Madden-Julian Oscillation (DYNAMO): The Indian Ocean is one of Earth's most sensitive regions because the interactions between ocean and atmosphere there have a discernable effect on global climate patterns. The tropical weather that brews in that region can move eastward along the equator and reverberate around the globe, shaping weather and climate in far-off places. The vehicle for this variability is a phenomenon called the Madden-Julian Oscillation, or MJO. The MJO, which originates over the Indian Ocean roughly every 30 to 90 days, is known to influence the Asian and Australian monsoons. It can also enhance hurricane activity in the northeast Pacific and Gulf of Mexico, trigger torrential rainfall along the west coast of North America, and affect the onset of El Niño. CVP-funded scientists participated in the DYNAMO field campaign in 2011-12. Results from this international campaign are expected to improve researcher's insights into this influential phenomenon. A better understanding of the processes governing MJO is an essential step toward improving their representations in numerical models and improving MJO simulation and prediction. Recent results from CVP-funded projects will be summarized in this poster.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950046568&hterms=Jun+Make&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DJun%2BMake','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950046568&hterms=Jun+Make&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DJun%2BMake"><span>The Sun as a variable star: Solar and stellar irradiance variations; Colloquium of the International Astronomical Union, 143rd, Boulder, CO, Jun. 20-25, 1993</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pap, Judit M. (Editor); Froehlich, Claus (Editor); Hudson, Hugh S. (Editor); Tobiska, W. Kent (Editor)</p> <p>1994-01-01</p> <p>Variations in solar and stellar irradiances have long been of interest. An International Astronomical Union (IAU) colloquium reviewed such relevant subjects as observations, theoretical interpretations, and empirical and physical models, with a special emphasis on climatic impact of solar irradiance variability. Specific topics discussed included: (1) General Reviews on Observations of Solar and Stellar Irradiance Variability; (2) Observational Programs for Solar and Stellar Irradiance Variability; (3) Variability of Solar and Stellar Irradiance Related to the Network, Active Regions (Sunspots and Plages), and Large-Scale Magnetic Structures; (4) Empirical Models of Solar Total and Spectral Irradiance Variability; (5) Solar and Stellar Oscillations, Irradiance Variations and their Interpretations; and (6) The Response of the Earth's Atmosphere to Solar Irradiance Variations and Sun-Climate Connections.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.4246B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.4246B"><span>Role of internal variability in recent decadal to multidecadal tropical Pacific climate changes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bordbar, Mohammad Hadi; Martin, Thomas; Latif, Mojib; Park, Wonsun</p> <p>2017-05-01</p> <p>While the Earth's surface has considerably warmed over the past two decades, the tropical Pacific has featured a cooling of sea surface temperatures in its eastern and central parts, which went along with an unprecedented strengthening of the equatorial trade winds, the surface component of the Pacific Walker Circulation (PWC). Previous studies show that this decadal trend in the trade winds is generally beyond the range of decadal trends simulated by climate models when forced by historical radiative forcing. There is still a debate on the origin of and the potential role that internal variability may have played in the recent decadal surface wind trend. Using a number of long control (unforced) integrations of global climate models and several observational data sets, we address the question as to whether the recent decadal to multidecadal trends are robustly classified as an unusual event or the persistent response to external forcing. The observed trends in the tropical Pacific surface climate are still within the range of the long-term internal variability spanned by the models but represent an extreme realization of this variability. Thus, the recent observed decadal trends in the tropical Pacific, though highly unusual, could be of natural origin. We note that the long-term trends in the selected PWC indices exhibit a large observational uncertainty, even hindering definitive statements about the sign of the trends.<abstract type="synopsis"><title type="main">Plain Language SummaryWhile the Earth's surface has considerably warmed over the past two decades, the tropical Pacific has featured a cooling of sea surface temperatures in its eastern and central parts, which went along with an unprecedented strengthening of the equatorial trade winds. Here we show that climate models simulate a high level of internal variability, so that the recent changes in the tropical Pacific could still be due to natural processes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4832924','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4832924"><span>Country-Specific Effects of Climate Variability on Human Migration</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Gray, Clark; Wise, Erika</p> <p>2016-01-01</p> <p>Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe. PMID:27092012</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ERL....12d4007M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ERL....12d4007M"><span>Influence of internal variability on population exposure to hydroclimatic changes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mankin, Justin S.; Viviroli, Daniel; Mekonnen, Mesfin M.; Hoekstra, Arjen Y.; Horton, Radley M.; E Smerdon, Jason; Diffenbaugh, Noah S.</p> <p>2017-04-01</p> <p>Future freshwater supply, human water demand, and people’s exposure to water stress are subject to multiple sources of uncertainty, including unknown future pathways of fossil fuel and water consumption, and ‘irreducible’ uncertainty arising from internal climate system variability. Such internal variability can conceal forced hydroclimatic changes on multi-decadal timescales and near-continental spatial-scales. Using three projections of population growth, a large ensemble from a single Earth system model, and assuming stationary per capita water consumption, we quantify the likelihoods of future population exposure to increased hydroclimatic deficits, which we define as the average duration and magnitude by which evapotranspiration exceeds precipitation in a basin. We calculate that by 2060, ∽31%-35% of the global population will be exposed to >50% probability of hydroclimatic deficit increases that exceed existing hydrological storage, with up to 9% of people exposed to >90% probability. However, internal variability, which is an irreducible uncertainty in climate model predictions that is under-sampled in water resource projections, creates substantial uncertainty in predicted exposure: ∽86%-91% of people will reside where irreducible uncertainty spans the potential for both increases and decreases in sub-annual water deficits. In one population scenario, changes in exposure to large hydroclimate deficits vary from -3% to +6% of global population, a range arising entirely from internal variability. The uncertainty in risk arising from irreducible uncertainty in the precise pattern of hydroclimatic change, which is typically conflated with other uncertainties in projections, is critical for climate risk management that seeks to optimize adaptations that are robust to the full set of potential real-world outcomes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ClDy...43.2297H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ClDy...43.2297H"><span>On the generation of climate model ensembles</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Haughton, Ned; Abramowitz, Gab; Pitman, Andy; Phipps, Steven J.</p> <p>2014-10-01</p> <p>Climate model ensembles are used to estimate uncertainty in future projections, typically by interpreting the ensemble distribution for a particular variable probabilistically. There are, however, different ways to produce climate model ensembles that yield different results, and therefore different probabilities for a future change in a variable. Perhaps equally importantly, there are different approaches to interpreting the ensemble distribution that lead to different conclusions. Here we use a reduced-resolution climate system model to compare three common ways to generate ensembles: initial conditions perturbation, physical parameter perturbation, and structural changes. Despite these three approaches conceptually representing very different categories of uncertainty within a modelling system, when comparing simulations to observations of surface air temperature they can be very difficult to separate. Using the twentieth century CMIP5 ensemble for comparison, we show that initial conditions ensembles, in theory representing internal variability, significantly underestimate observed variance. Structural ensembles, perhaps less surprisingly, exhibit over-dispersion in simulated variance. We argue that future climate model ensembles may need to include parameter or structural perturbation members in addition to perturbed initial conditions members to ensure that they sample uncertainty due to internal variability more completely. We note that where ensembles are over- or under-dispersive, such as for the CMIP5 ensemble, estimates of uncertainty need to be treated with care.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011ERL.....6c1002H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011ERL.....6c1002H"><span>Global warming: it's not only size that matters</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hegerl, Gabriele C.</p> <p>2011-09-01</p> <p>Observed and model simulated warming is particularly large in high latitudes, and hence the Arctic is often seen as the posterchild of vulnerability to global warming. However, Mahlstein et al (2011) point out that the signal of climate change is emerging locally from that of climate variability earliest in regions of low climate variability, based on climate model data, and in agreement with observations. This is because high latitude regions are not only regions of strong feedbacks that enhance the global warming signal, but also regions of substantial climate variability, driven by strong dynamics and enhanced by feedbacks (Hall 2004). Hence the spatial pattern of both observed warming and simulated warming for the 20th century shows strong warming in high latitudes, but this warming occurs against a backdrop of strong variability. Thus, the ratio of the warming to internal variability is not necessarily highest in the regions that warm fastest—and Mahlstein et al illustrate that it is actually the low-variability regions where the signal of local warming emerges first from that of climate variability. Thus, regions with strongest warming are neither the most important to diagnose that forcing changes climate, nor are they the regions which will necessarily experience the strongest impact. The importance of the signal-to-noise ratio has been known to the detection and attribution community, but has been buried in technical 'optimal fingerprinting' literature (e.g., Hasselmann 1979, Allen and Tett 1999), where it was used for an earlier detection of climate change by emphasizing aspects of the fingerprint of global warming associated with low variability in estimates of the observed warming. What, however, was not discussed was that the local signal-to-noise ratio is of interest also for local climate change: where temperatures emerge from the range visited by internal climate variability, it is reasonable to assume that changes in climate will also cause more impacts than temperatures that have occurred frequently due to internal climate variability. Determining when exactly temperatures enter unusual ranges may be done in many different ways (and the paper shows several, and more could be imagined), but the main result of first local emergence in low latitudes remains robust. A worrying factor is that the regions where the signal is expected to emerge first, or is already emerging are largely regions in Africa, parts of South and Central America, and the Maritime Continent; regions that are vulnerable to climate change for a variety of regions (see IPCC 2007), and regions which contribute generally little to global greenhouse gas emissions. In contrast, strong emissions of greenhouse gases occur in regions of low warming-to-variability ratio. To get even closer to the relevance of this finding for impacts, it would be interesting to place the emergence of highly unusual summer temperatures in the context not of internal variability, but in the context of variability experienced by the climate system prior to the 20th century, as, e.g. documented in palaeoclimatic reconstructions and simulated in simulations of the last millennium (see Jansen et al 2007). External forcing has moved the temperature range around more strongly for some regions and in some seasons than others. For example, while reconstructions of summer temperatures in Europe appear to show small long-term variations, winter shows deep drops in temperature in the little Ice Age and a long-term increase since then (Luterbacher et al 2004), which was at least partly caused by external forcing (Hegerl et al 2011a) and therefore 'natural variability' may be different from internal variability. A further interesting question in attempts to provide a climate-based proxy for impacts of climate change is: to what extent does the rapidity of change matter, and how does it compare to trends due to natural variability? It is reasonable to assume that fast changes impact ecosystems and society more than slow, gradual ones. Also, is it really the mean seasonal temperature that counts, or should the focus change to extremes (see Hegerl et al 2011b)? Is seasonal mean exceedance of the prior temperature envelope a good and robust measure that also reflects these other, more complex diagnostics? Lots of food for thought and research! References Allen M R and Tett S F B 1999 Checking for model consistency in optimal finger printing Clim. Dyn. 15 419-34 Hall A 2004 The role of surface albedo feedback in climate J. Clim. 17 1550-68 Hasselmann K 1979 On the signal-to-noise problem in atmospheric response studies Meteorology of Tropical Oceans ed D B Shaw (Bracknell: Royal Meteorological Society) pp 251-9 Hegerl G C, Luterbacher J, Gonzalez-Ruoco F, Tett S F B and Xoplaki E 2011a Influence of human and natural forcing on European seasonal temperatures Nature Geoscience 4 99-103 Hegerl G, Hanlon H and Beierkuhnlein C 2011b Climate science: elusive extremes Nature Geoscience 4 142-3 IPCC 2007 Climate Change 2007: Impacts, Adaption and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed M L Parry, O F Canziani, J P Palutikof, P J van der Linden and C E Hanson (Cambridge: Cambridge University Press) Jansen E et al 2007 Palaeoclimate Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed S Solomon et al (Cambridge: Cambridge University Press) Luterbacher J et al 2004 European seasonal and annual temperature variability, trends, and extremes since 1500 Science 303 1499-503 Mahlstein I, Knutti R, Solomon S and Portmann R W 2011 Early onset of significant local warming in low latitude countries Environ. Res. Lett. 6 034009</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016CliPa..12.2107C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016CliPa..12.2107C"><span>The 1430s: a cold period of extraordinary internal climate variability during the early Spörer Minimum with social and economic impacts in north-western and central Europe</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Camenisch, Chantal; Keller, Kathrin M.; Salvisberg, Melanie; Amann, Benjamin; Bauch, Martin; Blumer, Sandro; Brázdil, Rudolf; Brönnimann, Stefan; Büntgen, Ulf; Campbell, Bruce M. S.; Fernández-Donado, Laura; Fleitmann, Dominik; Glaser, Rüdiger; González-Rouco, Fidel; Grosjean, Martin; Hoffmann, Richard C.; Huhtamaa, Heli; Joos, Fortunat; Kiss, Andrea; Kotyza, Oldřich; Lehner, Flavio; Luterbacher, Jürg; Maughan, Nicolas; Neukom, Raphael; Novy, Theresa; Pribyl, Kathleen; Raible, Christoph C.; Riemann, Dirk; Schuh, Maximilian; Slavin, Philip; Werner, Johannes P.; Wetter, Oliver</p> <p>2016-12-01</p> <p>Changes in climate affected human societies throughout the last millennium. While European cold periods in the 17th and 18th century have been assessed in detail, earlier cold periods received much less attention due to sparse information available. New evidence from proxy archives, historical documentary sources and climate model simulations permit us to provide an interdisciplinary, systematic assessment of an exceptionally cold period in the 15th century. Our assessment includes the role of internal, unforced climate variability and external forcing in shaping extreme climatic conditions and the impacts on and responses of the medieval society in north-western and central Europe.Climate reconstructions from a multitude of natural and anthropogenic archives indicate that the 1430s were the coldest decade in north-western and central Europe in the 15th century. This decade is characterised by cold winters and average to warm summers resulting in a strong seasonal cycle in temperature. Results from comprehensive climate models indicate consistently that these conditions occurred by chance due to the partly chaotic internal variability within the climate system. External forcing like volcanic eruptions tends to reduce simulated temperature seasonality and cannot explain the reconstructions. The strong seasonal cycle in temperature reduced food production and led to increasing food prices, a subsistence crisis and a famine in parts of Europe. Societies were not prepared to cope with failing markets and interrupted trade routes. In response to the crisis, authorities implemented numerous measures of supply policy and adaptation such as the installation of grain storage capacities to be prepared for future food production shortfalls.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1228364','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1228364"><span>Detection of Historical and Future Precipitation Variations and Extremes Over the Continental United States</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Anderson, Bruce T.</p> <p>2015-12-11</p> <p>Problem: The overall goal of this proposal is to detect observed seasonal-mean precipitation variations and extreme event occurrences over the United States. Detection, e.g. the process of demonstrating that an observed change in climate is unusual, first requires some means of estimating the range of internal variability absent any external drivers. Ideally, the internal variability would be derived from the observations themselves, however generally the observed variability is a confluence of both internal variability and variability in response to external drivers. Further, numerical climate models—the standard tool for detection studies—have their own estimates of intrinsic variability, which may differ substantiallymore » from that found in the observed system as well as other model systems. These problems are further compounded for weather and climate extremes, which as singular events are particularly ill-suited for detection studies because of their infrequent occurrence, limited spatial range, and underestimation within global and even regional numerical models. Rationale: As a basis for this research we will show how stochastic daily-precipitation models—models in which the simulated interannual-to-multidecadal precipitation variance is purely the result of the random evolution of daily precipitation events within a given time period—can be used to address many of these issues simultaneously. Through the novel application of these well-established models, we can first estimate the changes/trends in various means and extremes that can occur even with fixed daily-precipitation characteristics, e.g. that can occur simply as a result of the stochastic evolution of daily weather events within a given climate. Detection of a change in the observed climate—either naturally or anthropogenically forced—can then be defined as any change relative to this stochastic variability, e.g. as changes/trends in the means and extremes that could only have occurred through a change in the underlying climate. As such, this method is capable of detecting “hot spot” regions—as well as “flare ups” within the hot spot regions—that have experienced interannual to multi-decadal scale variations and trends in seasonal-mean precipitation and extreme events. Further by applying the same methods to numerical climate models we can discern the fidelity of the current-generation climate models in representing detectability within the observed climate system. In this way, we can objectively determine the utility of these model systems for performing detection studies of historical and future climate change.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29780186','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29780186"><span>Internal ocean-atmosphere variability drives megadroughts in Western North America.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Coats, S; Smerdon, J E; Cook, B I; Seager, R; Cook, E R; Anchukaitis, K J</p> <p>2016-09-28</p> <p>Multidecadal droughts that occurred during the Medieval Climate Anomaly represent an important target for validating the ability of climate models to adequately characterize drought risk over the near-term future. A prominent hypothesis is that these megadroughts were driven by a centuries-long radiatively forced shift in the mean state of the tropical Pacific Ocean. Here we use a novel combination of spatiotemporal tree-ring reconstructions of Northern Hemisphere hydroclimate to infer the atmosphere-ocean dynamics that coincide with megadroughts over the American West, and find that these features are consistently associated with ten-to-thirty year periods of frequent cold El Niño Southern Oscillation conditions and not a centuries-long shift in the mean of the tropical Pacific Ocean. These results suggest an important role for internal variability in driving past megadroughts. State-of-the art climate models from the Coupled Model Intercomparison Project phase 5, however, do not simulate a consistent association between megadroughts and internal variability of the tropical Pacific Ocean, with implications for our confidence in megadrought risk projections.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29170619','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29170619"><span>Internal and International Mobility as Adaptation to Climatic Variability in Contemporary Mexico: Evidence from the Integration of Census and Satellite Data.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Leyk, Stefan; Runfola, Dan; Nawrotzki, Raphael J; Hunter, Lori M; Riosmena, Fernando</p> <p>2017-08-01</p> <p>Migration provides a strategy for rural Mexican households to cope with, or adapt to, weather events and climatic variability. Yet prior studies on "environmental migration" in this context have not examined the differences between choices of internal (domestic) or international movement. In addition, much of the prior work relied on very coarse spatial scales to operationalize the environmental variables such as rainfall patterns. To overcome these limitations, we use fine-grain rainfall estimates derived from NASA's Tropical Rainfall Measuring Mission (TRMM) satellite. The rainfall estimates are combined with Population and Agricultural Census information to examine associations between environmental changes and municipal rates of internal and international migration 2005-2010. Our findings suggest that municipal-level rainfall deficits relative to historical levels are an important predictor of both international and internal migration, especially in areas dependent on seasonal rainfall for crop productivity. Although our findings do not contradict results of prior studies using coarse spatial resolution, they offer clearer results and a more spatially nuanced examination of migration as related to social and environmental vulnerability and thus higher degrees of confidence.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.7831M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.7831M"><span>How are interannual modes of variability IOD, ENSO, SAM, AMO excited by natural and anthropogenic forcing?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maher, Nicola; Marotzke, Jochem</p> <p>2017-04-01</p> <p>Natural climate variability is found in observations, paleo-proxies, and climate models. Such climate variability can be intrinsic internal variability or externally forced, for example by changes in greenhouse gases or large volcanic eruptions. There are still questions concerning how external forcing, both natural (e.g., volcanic eruptions and solar variability) and anthropogenic (e.g., greenhouse gases and ozone) may excite both interannual modes of variability in the climate system. This project aims to address some of these problems, utilising the large ensemble of the MPI-ESM-LR climate model. In this study we investigate the statistics of four modes of interannual variability, namely the North Atlantic Oscillation (NAO), the Indian Ocean Dipole (IOD), the Southern Annular Mode (SAM) and the El Niño Southern Oscillation (ENSO). Using the 100-member ensemble of MPI-ESM-LR the statistical properties of these modes (amplitude and standard deviation) can be assessed over time. Here we compare the properties in the pre-industrial control run, historical run and future scenarios (RCP4.5, RCP2.6) and present preliminary results.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active"><span>3</span></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_3 --> <div id="page_4" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="61"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/55710','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/55710"><span>Trends in seasonal warm anomalies across the contiguous United States: Contributions from natural climate variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Lejiang Yu; Shiyuan Zhong; Warren E. Heilman; Xindi Bian</p> <p>2018-01-01</p> <p>Many studies have shown the importance of anthropogenic greenhouse gas emissions in contributing to observed upward trends in the occurrences of temperature extremes over the U.S. However, few studies have investigated the contributions of internal variability in the climate system to these observed trends. Here we use daily maximum temperature time series from the...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ERL....12d4005E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ERL....12d4005E"><span>The influence of internal climate variability on heatwave frequency trends</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>E Perkins-Kirkpatrick, S.; Fischer, E. M.; Angélil, O.; Gibson, P. B.</p> <p>2017-04-01</p> <p>Understanding what drives changes in heatwaves is imperative for all systems impacted by extreme heat. We examine short- (13 yr) and long-term (56 yr) heatwave frequency trends in a 21-member ensemble of a global climate model (Community Earth System Model; CESM), where each member is driven by identical anthropogenic forcings. To estimate changes dominantly due to internal climate variability, trends were calculated in the corresponding pre-industrial control run. We find that short-term trends in heatwave frequency are not robust indicators of long-term change. Additionally, we find that a lack of a long-term trend is possible, although improbable, under historical anthropogenic forcing over many regions. All long-term trends become unprecedented against internal variability when commencing in 2015 or later, and corresponding short-term trends by 2030, while the length of trend required to represent regional long-term changes is dependent on a given realization. Lastly, within ten years of a short-term decline, 95% of regional heatwave frequency trends have reverted to increases. This suggests that observed short-term changes of decreasing heatwave frequency could recover to increasing trends within the next decade. The results of this study are specific to CESM and the ‘business as usual’ scenario, and may differ under other representations of internal variability, or be less striking when a scenario with lower anthropogenic forcing is employed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=depression+AND+problem+AND+student&pg=3&id=EJ1096472','ERIC'); return false;" href="https://eric.ed.gov/?q=depression+AND+problem+AND+student&pg=3&id=EJ1096472"><span>School Climate and Student Absenteeism and Internalizing and Externalizing Behavioral Problems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Hendron, Marisa; Kearney, Christopher A.</p> <p>2016-01-01</p> <p>This study examined whether school climate variables were directly and inversely related to absenteeism severity and key symptoms of psychopathology among youths specifically referred for problematic attendance (N = 398). Adolescents in our sample completed the School Climate Survey Revised Edition, which measured sharing of resources, order and…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23996901','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23996901"><span>Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal-scale biological variability.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Litzow, Michael A; Mueter, Franz J; Hobday, Alistair J</p> <p>2014-01-01</p> <p>In areas of the North Pacific that are largely free of overfishing, climate regime shifts - abrupt changes in modes of low-frequency climate variability - are seen as the dominant drivers of decadal-scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific-North American Pattern (PNA), North Pacific Index (NPI), El Niño-Southern Oscillation (ENSO)] to explain decadal-scale (1965-2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1-2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1-2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1-2 satisfied assumptions of independent residuals and out-performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1-2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations. © 2013 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC32B..01P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC32B..01P"><span>Inability of CMIP5 Climate Models to Simulate Recent Multi-decadal Climate Change in the Tropical Pacific.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Power, S.; Delage, F.; Kociuba, G.; Wang, G.; Smith, I.</p> <p>2017-12-01</p> <p>Observed 15-year surface temperature trends beginning 1998 or later have attracted a great deal of interest because of an apparent slowdown in the rate of global warming, and contrasts between climate model simulations and observations of such trends. Many studies have addressed the statistical significance of these relatively short trends, whether they indicate a possible bias in models and the implications for global warming generally. Here we analyse historical and projected changes in 38 CMIP5 climate models. All of the models simulate multi-decadal warming in the Pacific over the past half-century that exceeds observed values. This stark difference cannot be fully explained by observed, internal multi-decadal climate variability, even if allowance is made for an apparent tendency for models to underestimate internal multi-decadal variability in the Pacific. We also show that CMIP5 models are not able to simulate the magnitude of the strengthening of the Walker Circulation over the past thirty years. Some of the reasons for these major shortcomings in the ability of models to simulate multi-decadal variability in the Pacific, and the impact these findings have on our confidence in global 21st century projections, will be discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC41A1002M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC41A1002M"><span>Does internal variability change in response to global warming? A large ensemble modelling study of tropical rainfall</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Milinski, S.; Bader, J.; Jungclaus, J. H.; Marotzke, J.</p> <p>2017-12-01</p> <p>There is some consensus on mean state changes of rainfall under global warming; changes of the internal variability, on the other hand, are more difficult to analyse and have not been discussed as much despite their importance for understanding changes in extreme events, such as droughts or floodings. We analyse changes in the rainfall variability in the tropical Atlantic region. We use a 100-member ensemble of historical (1850-2005) model simulations with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1) to identify changes of internal rainfall variability. To investigate the effects of global warming on the internal variability, we employ an additional ensemble of model simulations with stronger external forcing (1% CO2-increase per year, same integration length as the historical simulations) with 68 ensemble members. The focus of our study is on the oceanic Atlantic ITCZ. We find that the internal variability of rainfall over the tropical Atlantic does change due to global warming and that these changes in variability are larger than changes in the mean state in some regions. From splitting the total variance into patterns of variability, we see that the variability on the southern flank of the ITCZ becomes more dominant, i.e. explaining a larger fraction of the total variance in a warmer climate. In agreement with previous studies, we find that changes in the mean state show an increase and narrowing of the ITCZ. The large ensembles allow us to do a statistically robust differentiation between the changes in variability that can be explained by internal variability and those that can be attributed to the external forcing. Furthermore, we argue that internal variability in a transient climate is only well defined in the ensemble domain and not in the temporal domain, which requires the use of a large ensemble.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5141387','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5141387"><span>Prospects for a prolonged slowdown in global warming in the early 21st century</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Knutson, Thomas R.; Zhang, Rong; Horowitz, Larry W.</p> <p>2016-01-01</p> <p>Global mean temperature over 1998 to 2015 increased at a slower rate (0.1 K decade−1) compared with the ensemble mean (forced) warming rate projected by Coupled Model Intercomparison Project 5 (CMIP5) models (0.2 K decade−1). Here we investigate the prospects for this slower rate to persist for a decade or more. The slower rate could persist if the transient climate response is overestimated by CMIP5 models by a factor of two, as suggested by recent low-end estimates. Alternatively, using CMIP5 models' warming rate, the slower rate could still persist due to strong multidecadal internal variability cooling. Combining the CMIP5 ensemble warming rate with internal variability episodes from a single climate model—having the strongest multidecadal variability among CMIP5 models—we estimate that the warming slowdown (<0.1 K decade−1 trend beginning in 1998) could persist, due to internal variability cooling, through 2020, 2025 or 2030 with probabilities 16%, 11% and 6%, respectively. PMID:27901045</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.C11C0514W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.C11C0514W"><span>Variability and Change in the Canadian Cryosphere: A Canadian Science Contribution to International Polar Year</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Walker, A. E.; Derksen, C.</p> <p>2008-12-01</p> <p>The cryosphere (snow, permafrost and seasonally frozen ground, ice caps and glaciers, sea-, river-, and lake ice) represents a significant feature of the Canadian landscape that impacts climate, hydrology, the economy and the daily lives of all Canadians, especially those living in northern communities. Over the past few decades significant changes have been observed in cryospheric elements (e.g. decreases in snow cover, glacier extent, sea ice cover) that have been attributed to a warming climate. This poster presentation will highlight initial scientific results from the approved Canadian International Polar Year project "Variability and Change in the Canadian Cryosphere" that is being led by Environment Canada and involves 33 co- investigators from government, academia and the private sector and links with international collaborators. This project builds on Canadian strengths in remote sensing, climate analysis and modeling with the overall objective to observe and understand the current state of the cryosphere in Canada and determine how fast it is changing and why. Research activities are focused on: (1) developing new satellite-based capabilities to provide information on the current state of the Canadian cryosphere during the IPY period; (2) placing current cryospheric conditions in the context of the historical record to document the magnitude of changes over the 50 years since the last International Polar Year (IGY 1957-1958); (3) characterizing and explaining the observed variability and changes in the context of the coupled climate cryosphere system; and (4) improving the representation of the cryosphere in Canadian land surface and climate models to provide current and future climate simulations of the cryosphere for climate impact studies. The project also includes several outreach activities to engage northern communities in cryospheric monitoring and incorporate traditional knowledge with remotely-sensed information to generate new maps on local river ice and sea ice conditions to assist residents in planning safe navigation routes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JOUC...17..219L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JOUC...17..219L"><span>Plausible Effect of Weather on Atlantic Meridional Overturning Circulation with a Coupled General Circulation Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Zedong; Wan, Xiuquan</p> <p>2018-04-01</p> <p>The Atlantic meridional overturning circulation (AMOC) is a vital component of the global ocean circulation and the heat engine of the climate system. Through the use of a coupled general circulation model, this study examines the role of synoptic systems on the AMOC and presents evidence that internally generated high-frequency, synoptic-scale weather variability in the atmosphere could play a significant role in maintaining the overall strength and variability of the AMOC, thereby affecting climate variability and change. Results of a novel coupling technique show that the strength and variability of the AMOC are greatly reduced once the synoptic weather variability is suppressed in the coupled model. The strength and variability of the AMOC are closely linked to deep convection events at high latitudes, which could be strongly affected by the weather variability. Our results imply that synoptic weather systems are important in driving the AMOC and its variability. Thus, interactions between atmospheric weather variability and AMOC may be an important feedback mechanism of the global climate system and need to be taken into consideration in future climate change studies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy...48.1841V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy...48.1841V"><span>Decadal climate prediction with a refined anomaly initialisation approach</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco J.; Hawkins, Ed; Nichols, Nancy K.</p> <p>2017-03-01</p> <p>In decadal prediction, the objective is to exploit both the sources of predictability from the external radiative forcings and from the internal variability to provide the best possible climate information for the next decade. Predicting the climate system internal variability relies on initialising the climate model from observational estimates. We present a refined method of anomaly initialisation (AI) applied to the ocean and sea ice components of the global climate forecast model EC-Earth, with the following key innovations: (1) the use of a weight applied to the observed anomalies, in order to avoid the risk of introducing anomalies recorded in the observed climate, whose amplitude does not fit in the range of the internal variability generated by the model; (2) the AI of the ocean density, instead of calculating it from the anomaly initialised state of temperature and salinity. An experiment initialised with this refined AI method has been compared with a full field and standard AI experiment. Results show that the use of such refinements enhances the surface temperature skill over part of the North and South Atlantic, part of the South Pacific and the Mediterranean Sea for the first forecast year. However, part of such improvement is lost in the following forecast years. For the tropical Pacific surface temperature, the full field initialised experiment performs the best. The prediction of the Arctic sea-ice volume is improved by the refined AI method for the first three forecast years and the skill of the Atlantic multidecadal oscillation is significantly increased compared to a non-initialised forecast, along the whole forecast time.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A51L..03T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A51L..03T"><span>Forced and Internal Multi-Decadal Variability in the North Atlantic and their Climate Impacts</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ting, M.</p> <p>2017-12-01</p> <p>Atlantic Multidecadal Variability (AMV), a basin-wide North Atlantic sea surface temperature warming or cooling pattern varying on decadal and longer time scales, is one of the most important climate variations in the Atlantic basin. The AMV has shown to be associated with significant climate impacts regionally and globally, from Atlantic hurricane activities, frequency and severity of droughts across North America, as well as rainfall anomalies across the African Sahel and northeast Brazil. Despite the important impacts of the AMV, its mechanisms are not completely understood. In particular, it is not clear how much of the historical Atlantic SST fluctuations were forced by anthropogenic sources such as greenhouse warming and aerosol cooling, versus driven internally by changes in the coupled ocean-atmosphere processes in the Atlantic. Using climate models such as the NCAR large ensemble simulations, we were able to successfully separate the forced and internally generated North Atlantic sea surface temperature anomalies through a signal-to-noise maximizing Empirical Orthogonal Function (S/N EOF) analysis method. Two forced modes were identified with one representing a hemispherical symmetric mode and one asymmetric mode. The symmetric mode largely represents the greenhouse forced component while the asymmetric mode resembles the anthropogenic aerosol forcing. When statistically removing both of the forced modes, the residual multidecadal Atlantic SST variability shows a very similar structure as the AMV in the preindustrial simulation. The distinct climate impacts of each of these modes are also identified and the implications and challenges for decadal climate prediction will be discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC41B0544A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC41B0544A"><span>Social vulnerability and climate variability in southern Brazil: a TerraPop case study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Adamo, S. B.; Fitch, C. A.; Kugler, T.; Doxsey-Whitfield, E.</p> <p>2014-12-01</p> <p>Climate variability is an inherent characteristic of the Earth's climate, including but not limited to climate change. It affects and impacts human society in different ways, depending on the underlying socioeconomic vulnerability of specific places, social groups, households and individuals. This differential vulnerability presents spatial and temporal variations, and is rooted in historical patterns of development and relations between human and ecological systems. This study aims to assess the impact of climate variability on livelihoods and well-being, as well as their changes over time and across space, and for rural and urban populations. The geographic focus is Southern Brazil-the states of Parana, Santa Catarina and Rio Grande do Sul-- and the objectives include (a) to identify and map critical areas or hotspots of exposure to climate variability (temperature and precipitation), and (b) to identify internal variation or differential vulnerability within these areas and its evolution over time (1980-2010), using newly available integrated data from the Terra Populus project. These data include geo-referenced climate and agricultural data, and data describing demographic and socioeconomic characteristics of individuals, households and places.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1377777-cmip5-scientific-gaps-recommendations-cmip6','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1377777-cmip5-scientific-gaps-recommendations-cmip6"><span>CMIP5 Scientific Gaps and Recommendations for CMIP6</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Stouffer, R. J.; Eyring, V.; Meehl, G. A.; ...</p> <p>2017-01-23</p> <p>The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP,more » that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1377777','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1377777"><span>CMIP5 Scientific Gaps and Recommendations for CMIP6</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Stouffer, R. J.; Eyring, V.; Meehl, G. A.</p> <p></p> <p>The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP,more » that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.7093T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.7093T"><span>Resilience, rapid transitions and regime shifts: fingerprinting the responses of Lake Żabińskie (NE Poland) to climate variability and human disturbance since 1000 AD</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tylmann, Wojciech; Hernández-Almeida, Iván; Grosjean, Martin; José Gómez Navarro, Juan; Larocque-Tobler, Isabelle; Bonk, Alicja; Enters, Dirk; Ustrzycka, Alicja; Piotrowska, Natalia; Przybylak, Rajmund; Wacnik, Agnieszka; Witak, Małgorzata</p> <p>2016-04-01</p> <p>Rapid ecosystem transitions and adverse effects on ecosystem services as responses to combined climate and human impacts are of major concern. Yet few quantitative observational data exist, particularly for ecosystems that have a long history of human intervention. Here, we combine quantitative summer and winter climate reconstructions, climate model simulations and proxies for three major environmental pressures (land use, nutrients and erosion) to explore the system dynamics, resilience, and the role of disturbance regimes in varved eutrophic Lake Żabińskie since AD 1000. Comparison between regional and global climate simulations and quantitative climate reconstructions indicate that proxy data capture noticeably natural forced climate variability, while internal variability appears as the dominant source of climate variability in the climate model simulations during most parts of the last millennium. Using different multivariate analyses and change point detection techniques, we identify ecosystem changes through time and shifts between rather stable states and highly variable ones, as expressed by the proxies for land-use, erosion and productivity in the lake. Prior to AD 1600, the lake ecosystem was characterized by a high stability and resilience against considerable observed natural climate variability. In contrast, lake-ecosystem conditions started to fluctuate at high frequency across a broad range of states after AD 1600. The period AD 1748-1868 represents the phase with the strongest human disturbance of the ecosystem. Analyses of the frequency of change points in the multi-proxy dataset suggests that the last 400 years were highly variable and flickering with increasing vulnerability of the ecosystem to the combined effects of climate variability and anthropogenic disturbances. This led to significant rapid ecosystem transformations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916891M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916891M"><span>Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander</p> <p>2017-04-01</p> <p>An analysis of global climate response to external forcing, both anthropogenic (mainly, CO2 and aerosol) and natural (solar and volcanic), is needed for adequate predictions of global climate change. Being complex dynamical system, the climate reacts to external perturbations exciting feedbacks (both positive and negative) making the response non-trivial and poorly predictable. Thus an extraction of internal modes of climate system, investigation of their interaction with external forcings and further modeling and forecast of their dynamics, are all the problems providing the success of climate modeling. In the report the new method for principal mode extraction from climate data is presented. The method is based on the Nonlinear Dynamical Mode (NDM) expansion [1,2], but takes into account a number of external forcings applied to the system. Each NDM is represented by hidden time series governing the observed variability, which, together with external forcing time series, are mapped onto data space. While forcing time series are considered to be known, the hidden unknown signals underlying the internal climate dynamics are extracted from observed data by the suggested method. In particular, it gives us an opportunity to study the evolution of principal system's mode structure in changing external conditions and separate the internal climate variability from trends forced by external perturbations. Furthermore, the modes so obtained can be extrapolated beyond the observational time series, and long-term prognosis of modes' structure including characteristics of interconnections and responses to external perturbations, can be carried out. In this work the method is used for reconstructing and studying the principal modes of climate variability on inter-annual and decadal time scales accounting the external forcings such as anthropogenic emissions, variations of the solar activity and volcanic activity. The structure of the obtained modes as well as their response to external factors, e.g. forecast their change in 21 century under different CO2 emission scenarios, are discussed. [1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510 [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. http://doi.org/10.1063/1.4968852</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC52D..04W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC52D..04W"><span>Compounding nonlinearities in the climate and wildfire system contribute to high uncertainty in estimates of future burned area in the western United State</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Williams, P.</p> <p>2015-12-01</p> <p>Ecological studies are increasingly recognizing the importance of atmospheric vapor-pressure deficit (VPD) as a driver of forest drought stress and disturbance processes such as wildfire. Because of the nonlinear Clausius-Clapeyron relationship between temperature and saturation vapor pressure, small variations in temperature can have large impacts on VPD, and therefore drought, particularly in warm, dry areas and particularly during the warm season. It is also clear that VPD and drought affect forest fire nonlinearly, as incremental drying leads to increasingly large burned areas. Forest fire is also affected by fuel amount and connectivity, which are promoted by vegetation growth in previous years, which is in turn promoted by lack of drought, highlighting the importance of nuances in the sequencing of natural interannual climate variations in modulating the impacts of drought on wildfire. The many factors affecting forest fire, and the nonlinearities embedded within the climate and wildfire systems, cause interannual variability in forest-fire area and frequency to be wildly variable and strongly affected by internal climate variability. In addition, warming over the past century has produced a background increase in forest fire frequency and area in many regions. In this talk I focus on the western United States and will explore whether the relationships between internal climate variability on forest fire area have been amplified by the effects of warming as a result of the compounding nonlinearities described above. I will then explore what this means for future burned area in the western United States and make the case that uncertainties in the future global greenhouse gas emissions trajectory, model projections of mean temperatures, model projections of precipitation, and model projections of natural climate variability translate to very large uncertainties in the effects of future climate variability on forest fire area in the United States and globally.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20180001315','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20180001315"><span>Large-Scale Circulation and Climate Variability. Chapter 5</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.</p> <p>2017-01-01</p> <p>The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GML....37..515H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GML....37..515H"><span>Evidence for Holocene centennial variability in sea ice cover based on IP25 biomarker reconstruction in the southern Kara Sea (Arctic Ocean)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hörner, Tanja; Stein, Rüdiger; Fahl, Kirsten</p> <p>2017-10-01</p> <p>The Holocene is characterized by the late Holocene cooling trend as well as by internal short-term centennial fluctuations. Because Arctic sea ice acts as a significant component (amplifier) within the climate system, investigating its past long- and short-term variability and controlling processes is beneficial for future climate predictions. This study presents the first biomarker-based (IP25 and PIP25) sea ice reconstruction from the Kara Sea (core BP00-07/7), covering the last 8 ka. These biomarker proxies reflect conspicuous short-term sea ice variability during the last 6.5 ka that is identified unprecedentedly in the source region of Arctic sea ice by means of a direct sea ice indicator. Prominent peaks of extensive sea ice cover occurred at 3, 2, 1.3 and 0.3 ka. Spectral analysis of the IP25 record revealed 400- and 950-year cycles. These periodicities may be related to the Arctic/North Atlantic Oscillation, but probably also to internal climate system fluctuations. This demonstrates that sea ice belongs to a complex system that more likely depends on multiple internal forcing.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990080947&hterms=asian+american&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dasian%2Bamerican','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990080947&hterms=asian+american&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dasian%2Bamerican"><span>The East Asian Jet Stream and Asian-Pacific Climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yang, Song; Lau, K.-M.; Kim, K.-M.</p> <p>1999-01-01</p> <p>In this study, the NASA GEOS and NCEP/NCAR reanalyses and GPCP rainfall data have been used to study the variability of the East Asian westerly jet stream and its impact on the Asian-Pacific climate, with a focus on interannual time scales. Results indicate that external forcings such as sea surface temperature (SST) and land surface processes also play an important role in the variability of the jet although this variability is strongly governed by internal dynamics. There is a close link between the jet and Asian-Pacific climate including the Asian winter monsoon and tropical convection. The atmospheric teleconnection pattern associated with the jet is different from the ENSO-related pattern. The influence of the jet on eastern Pacific and North American climate is also discussed.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_4 --> <div id="page_5" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="81"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP52A..08C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP52A..08C"><span>Two Centuries of Climate Variability From a Gulf of Papua Coral Confirms a Coherent, Widespread Multidecadal Signal</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cole, J. E.; Lough, J.; Reed, E. V.; Schrag, D. P.</p> <p>2016-12-01</p> <p>The Indo-Pacific warm pool is intimately involved with large-scale climate variability on seasonal to secular time scales. The lack of long instrumental observations in this region has motivated paleoclimatic analyses using diverse proxy data sources. We present here new multicentury paleoclimate records from a Gulf of Papua coral that capture past variability with a Pacific-wide signature. We have developed stable isotope, Sr/Ca, skeletal density, and luminescence data from a coral core recovered at Bramble Cay, Australia (9°S, 144°E). The geochemical records span CE 1775-1993 and are dominated by low-frequency (decade-century scale) variability that is consistent with records from other proxies in the same region, and with other coral records from far-flung sites across the southwest Pacific. Unlike in many Pacific coral records, we observe no strong trend towards warmer conditions. Although skeletal density bands are clearly visible, they show inconsistent seasonal phasing with the geochemical tracers of sea surface temperature (SST; Sr/Ca and oxygen isotope content), and skeletal density does not correlate with these tracers on longer time scales. In this coral, density banding must be controlled by a more complex mix of internal and/or external factors. Luminescent banding and reconstructed salinity provide similar histories, suggesting a common hydroclimatic signal with significant variability at periods of decades and longer. The strong low-frequency behavior in these new climate records of SST and hydroclimate, from a remote region of the Indo-Pacific, confirms an important source of internal climate variability, on a poorly documented time scale, from a region with far-reaching climatic importance.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.3411H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.3411H"><span>Long-term Internal Variability of the Tropical Pacific Atmosphere-Ocean System</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hadi Bordbar, Mohammad; Martin, Thomas; Park, Wonsun; Latif, Mojib</p> <p>2016-04-01</p> <p>The tropical Pacific has featured some remarkable trends during the recent decades such as an unprecedented strengthening of the Trade Winds, a strong cooling of sea surface temperatures (SST) in the eastern and central part, thereby slowing global warming and strengthening the zonal SST gradient, and highly asymmetric sea level trends with an accelerated rise relative to the global average in the western and a drop in the eastern part. These trends have been linked to an anomalously strong Pacific Walker Circulation, the major zonal atmospheric overturning cell in the tropical Pacific sector, but the origin of the strengthening is controversial. Here we address the question as to whether the recent decadal trends in the tropical Pacific atmosphere-ocean system are within the range of internal variability, as simulated in long unforced integrations of global climate models. We show that the recent trends are still within the range of long-term internal decadal variability. Further, such variability strengthens in response to enhanced greenhouse gas concentrations, which may further hinder detection of anthropogenic climate signals in that region.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1712560D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1712560D"><span>Exploring the control of land-atmospheric oscillations over terrestrial vegetation productivity</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Depoorter, Mathieu; Green, Julia; Gentine, Pierre; Liu, Yi; van Eck, Christel; Regnier, Pierre; Dorigo, Wouter; Verhoest, Niko; Miralles, Diego</p> <p>2015-04-01</p> <p>Vegetation dynamics play an important role in the climate system due to their control on the carbon, energy and water cycles. The spatiotemporal variability of vegetation is regulated by internal climate variability as well as natural and anthropogenic forcing mechanisms, including fires, land use, volcano eruptions or greenhouse gas emissions. Ocean-atmospheric oscillations, affect the fluxes of heat and water over continents, leading to anomalies in radiation, precipitation or temperature at widely separated locations (i.e. teleconnections); an effect of ocean-atmospheric oscillations on terrestrial primary productivity can therefore be expected. While different studies have shown the general importance of internal climate variability for global vegetation dynamics, the control by particular teleconnections over the regional growth and decay of vegetation is still poorly understood. At continental to global scales, satellite remote sensing offers a feasible approach to enhance our understanding of the main drivers of vegetation variability. Traditional studies of the multi-decadal variability of global vegetation have been usually based on the normalized difference vegetation index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR), which extends back to the early '80s. There are, however, some limitations to NDVI observations; arguably the most important of these limitations is that from the plant physiology perspective the index does not have a well-defined meaning, appearing poorly correlated to vegetation productivity. On the other hand, recently developed records from other remotely-sensed properties of vegetation, like fluorescence or microwave vegetation optical depth, have proven a significantly better correspondence to above-ground biomass. To enhance our understanding of the controls of ocean-atmosphere oscillations over vegetation, we propose to explore the link between climate oscillation extremes and net primary productivity over the last two decades. The co-variability of a range of climate oscillation indices and newly-derived records of fluorescence and vegetation optical depth is analyzed using a statistical framework based on correlations, bootstrapping and Empirical Orthogonal Functions (EOFs). Results will enable us to characterize regional hotspots where particular climatic oscillations control vegetation productivity, as well as allowing us to underpin the climatic variables behind this control.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1408807-us-climate-variability-predictability-project','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1408807-us-climate-variability-predictability-project"><span>US Climate Variability and Predictability Project</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Patterson, Mike</p> <p></p> <p>The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year supportmore » of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1408807-us-climate-variability-predictability-clivar-project-final-report','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1408807-us-climate-variability-predictability-clivar-project-final-report"><span>US Climate Variability and Predictability (CLIVAR) Project- Final Report</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Patterson, Mike</p> <p></p> <p>The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year supportmore » of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1245323-grace-era-terrestrial-water-trends-driven-anthropogenic-climate-change','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1245323-grace-era-terrestrial-water-trends-driven-anthropogenic-climate-change"><span>Are GRACE-era terrestrial water trends driven by anthropogenic climate change?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Fasullo, J. T.; Lawrence, D. M.; Swenson, S. C.</p> <p>2016-01-01</p> <p>To provide context for observed trends in terrestrial water storage (TWS) during GRACE (2003–2014), trends and variability in the CESM1-CAM5 Large Ensemble (LE) are examined. Motivated in part by the anomalous nature of climate variability during GRACE, the characteristics of both forced change and internal modes are quantified and their influences on observations are estimated. Trends during the GRACE era in the LE are dominated by internal variability rather than by the forced response, with TWS anomalies in much of the Americas, eastern Australia, Africa, and southwestern Eurasia largely attributable to the negative phases of the Pacific Decadal Oscillation (PDO)more » and Atlantic Multidecadal Oscillation (AMO). While similarities between observed trends and the model-inferred forced response also exist, it is inappropriate to attribute such trends mainly to anthropogenic forcing. For several key river basins, trends in the mean state and interannual variability and the time at which the forced response exceeds background variability are also estimated while aspects of global mean TWS, including changes in its annual amplitude and decadal trends, are quantified. Lastly, the findings highlight the challenge of detecting anthropogenic climate change in temporally finite satellite datasets and underscore the benefit of utilizing models in the interpretation of the observed record.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1245323-grace-era-terrestrial-water-trends-driven-anthropogenic-climate-change','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1245323-grace-era-terrestrial-water-trends-driven-anthropogenic-climate-change"><span>Are GRACE-era terrestrial water trends driven by anthropogenic climate change?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Fasullo, J. T.; Lawrence, D. M.; Swenson, S. C.</p> <p></p> <p>To provide context for observed trends in terrestrial water storage (TWS) during GRACE (2003–2014), trends and variability in the CESM1-CAM5 Large Ensemble (LE) are examined. Motivated in part by the anomalous nature of climate variability during GRACE, the characteristics of both forced change and internal modes are quantified and their influences on observations are estimated. Trends during the GRACE era in the LE are dominated by internal variability rather than by the forced response, with TWS anomalies in much of the Americas, eastern Australia, Africa, and southwestern Eurasia largely attributable to the negative phases of the Pacific Decadal Oscillation (PDO)more » and Atlantic Multidecadal Oscillation (AMO). While similarities between observed trends and the model-inferred forced response also exist, it is inappropriate to attribute such trends mainly to anthropogenic forcing. For several key river basins, trends in the mean state and interannual variability and the time at which the forced response exceeds background variability are also estimated while aspects of global mean TWS, including changes in its annual amplitude and decadal trends, are quantified. Lastly, the findings highlight the challenge of detecting anthropogenic climate change in temporally finite satellite datasets and underscore the benefit of utilizing models in the interpretation of the observed record.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMPP21A1403A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMPP21A1403A"><span>Objective spatiotemporal proxy-model comparisons of the Asian monsoon for the last millennium</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Anchukaitis, K. J.; Cook, E. R.; Ammann, C. M.; Buckley, B. M.; D'Arrigo, R. D.; Jacoby, G.; Wright, W. E.; Davi, N.; Li, J.</p> <p>2008-12-01</p> <p>The Asian monsoon system can be studied using a complementary proxy/simulation approach which evaluates climate models using estimates of past precipitation and temperature, and which subsequently applies the best understanding of the physics of the climate system as captured in general circulation models to evaluate the broad-scale dynamics behind regional paleoclimate reconstructions. Here, we use a millennial-length climate field reconstruction of monsoon season summer (JJA) drought, developed from tree- ring proxies, with coupled climate simulations from NCAR CSM1.4 and CCSM3 to evaluate the cause of large- scale persistent droughts over the last one thousand years. Direct comparisons are made between the external forced response within the climate model and the spatiotemporal field reconstruction. In order to identify patterns of drought associated with internal variability in the climate system, we use a model/proxy analog technique which objectively selects epochs in the model that most closely reproduce those observed in the reconstructions. The concomitant ocean-atmosphere dynamics are then interpreted in order to identify and understand the internal climate system forcing of low frequency monsoon variability. We examine specific periods of extensive or intensive regional drought in the 15th, 17th, and 18th centuries, many of which are coincident with major cultural changes in the region.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015GeoRL..42..831D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015GeoRL..42..831D"><span>Climate modulates internal wave activity in the Northern South China Sea</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>DeCarlo, Thomas M.; Karnauskas, Kristopher B.; Davis, Kristen A.; Wong, George T. F.</p> <p>2015-02-01</p> <p>Internal waves (IWs) generated in the Luzon Strait propagate into the Northern South China Sea (NSCS), enhancing biological productivity and affecting coral reefs by modulating nutrient concentrations and temperature. Here we use a state-of-the-art ocean data assimilation system to reconstruct water column stratification in the Luzon Strait as a proxy for IW activity in the NSCS and diagnose mechanisms for its variability. Interannual variability of stratification is driven by intrusions of the Kuroshio Current into the Luzon Strait and freshwater fluxes associated with the El Niño-Southern Oscillation. Warming in the upper 100 m of the ocean caused a trend of increasing IW activity since 1900, consistent with global climate model experiments that show stratification in the Luzon Strait increases in response to radiative forcing. IW activity is expected to increase in the NSCS through the 21st century, with implications for mitigating climate change impacts on coastal ecosystems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70032531','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70032531"><span>Attribution of declining Western U.S. Snowpack to human effects</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Pierce, D.W.; Barnett, T.P.; Hidalgo, H.G.; Das, T.; Bonfils, Celine; Santer, B.D.; Bala, G.; Dettinger, M.D.; Cayan, D.R.; Mirin, A.; Wood, A.W.; Nozawa, T.</p> <p>2008-01-01</p> <p>Observations show snowpack has declined across much of the western United States over the period 1950-99. This reduction has important social and economic implications, as water retained in the snowpack from winter storms forms an important part of the hydrological cycle and water supply in the region. A formal model-based detection and attribution (D-A) study of these reductions is performed. The detection variable is the ratio of 1 April snow water equivalent (SWE) to water-year-to-date precipitation (P), chosen to reduce the effect of P variability on the results. Estimates of natural internal climate variability are obtained from 1600 years of two control simulations performed with fully coupled ocean-atmosphere climate models. Estimates of the SWE/P response to anthropogenic greenhouse gases, ozone, and some aerosols are taken from multiple-member ensembles of perturbation experiments run with two models. The D-A shows the observations and anthropogenically forced models have greater SWE/P reductions than can be explained by natural internal climate variability alone. Model-estimated effects of changes in solar and volcanic forcing likewise do not explain the SWE/P reductions. The mean model estimate is that about half of the SWE/P reductions observed in the west from 1950 to 1999 are the result of climate changes forced by anthropogenic greenhouse gases, ozone, and aerosols. ?? 2008 American Meteorological Society.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy..tmp..782A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy..tmp..782A"><span>The interplay of internal and forced modes of Hadley Cell expansion: lessons from the global warming hiatus</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Amaya, Dillon J.; Siler, Nicholas; Xie, Shang-Ping; Miller, Arthur J.</p> <p>2017-09-01</p> <p>The poleward branches of the Hadley Cells and the edge of the tropics show a robust poleward shift during the satellite era, leading to concerns over the possible encroachment of the globe's subtropical dry zones into currently temperate climates. The extent to which this trend is caused by anthropogenic forcing versus internal variability remains the subject of considerable debate. In this study, we use a Joint EOF method to identify two distinct modes of tropical width variability: (1) an anthropogenically-forced mode, which we identify using a 20-member simulation of the historical climate, and (2) an internal mode, which we identify using a 1000-year pre-industrial control simulation. The forced mode is found to be closely related to the top of the atmosphere radiative imbalance and exhibits a long-term trend since 1860, while the internal mode is essentially indistinguishable from the El Niño Southern Oscillation. Together these two modes explain an average of 70% of the interannual variability seen in model "edge indices" over the historical period. Since 1980, the superposition of forced and internal modes has resulted in a period of accelerated Hadley Cell expansion and decelerated global warming (i.e., the "hiatus"). A comparison of the change in these modes since 1980 indicates that by 2013 the signal has emerged above the noise of internal variability in the Southern Hemisphere, but not in the Northern Hemisphere, with the latter also exhibiting strong zonal asymmetry, particularly in the North Atlantic. Our results highlight the important interplay of internal and forced modes of tropical width change and improve our understanding of the interannual variability and long-term trend seen in observations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..12.5449G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..12.5449G"><span>Teleconnections in the Presence of Climate Change: A Case Study of the Annular Modes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gerber, Edwin; Baldwin, Mark</p> <p>2010-05-01</p> <p>Long model integrations of future and past climates present a problem for defining teleconnection patterns through Empirical Orthogonal Function (EOF) or correlation analysis when trends in the underlying climate begin to dominate the covariance structure. Similar issues may soon appear in observations as the record becomes longer, especially if climate trends accelerate. The Northern and Southern Annular Modes provide a prime example, because the poleward shift of the jet streams strongly projects onto these patterns, particularly in the Southern Hemisphere. Climate forecasts of the 21st century by chemistry climate models provide a case study. Computation of the annular modes in these long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The new procedure involves two key changes. First, the global mean geopotential height is removed at each time step before computing anomalies. This is particularly important high in the atmosphere, where seasonal variations in geopotential height become significant, and filters out trends due to changes in the temperature structure of the atmosphere. Pattern definition can be very sensitive near the tropopause, as regions of the atmosphere that used to be more of stratospheric character begin to take on tropospheric characteristics as the tropopause rises. The second change is to define anomalies relative to a slowly evolving seasonal climatology, so that the covariance structure reflects internal variability. Once these changes are accounted for, it is found that the zonal mean variability of the atmosphere stays remarkably constant, despite significant changes in the baseline climate forecast for the rest of the century. This stability of the internal variability makes it possible to relate trends in climate to teleconnections.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040016048&hterms=ensemble&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Densemble','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040016048&hterms=ensemble&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Densemble"><span>A 12-year (1987-1998) Ensemble Simulation of the US Climate with a Variable Resolution Stretched Grid GCM</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Govindaraju, Ravi C.</p> <p>2002-01-01</p> <p>The variable-resolution stretched-grid (SG) GEOS (Goddard Earth Observing System) GCM has been used for limited ensemble integrations with a relatively coarse, 60 to 100 km, regional resolution over the U.S. The experiments have been run for the 12-year period, 1987-1998, that includes the recent ENSO cycles. Initial conditions 1-2 days apart are used for ensemble members. The goal of the experiments is analyzing the long-term SG-GCM ensemble integrations in terms of their potential in reducing the uncertainties of regional climate simulation while producing realistic mesoscales. The ensemble integration results are analyzed for both prognostic and diagnostic fields. A special attention is devoted to analyzing the variability of precipitation over the U.S. The internal variability of the SG-GCM has been assessed. The ensemble means appear to be closer to the verifying analyses than the individual ensemble members. The ensemble means capture realistic mesoscale patterns, especially those of induced by orography. Two ENSO cycles have been analyzed in terms their impact on the U.S. climate, especially on precipitation. The ability of the SG-GCM simulations to produce regional climate anomalies has been confirmed. However, the optimal size of the ensembles depending on fine regional resolution used, is still to be determined. The SG-GCM ensemble simulations are performed as a preparation or a preliminary stage for the international SGMIP (Stretched-Grid Model Intercomparison Project) that is under way with participation of the major centers and groups employing the SG-approach for regional climate modeling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.3651F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.3651F"><span>ENSO-related Interannual Variability of Southern Hemisphere Atmospheric Circulation: Assessment and Projected Changes in CMIP5 Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Frederiksen, Carsten; Grainger, Simon; Zheng, Xiaogu; Sisson, Janice</p> <p>2013-04-01</p> <p>ENSO variability is an important driver of the Southern Hemisphere (SH) atmospheric circulation. Understanding the observed and projected changes in ENSO variability is therefore important to understanding changes in Australian surface climate. Using a recently developed methodology (Zheng et al., 2009), the coherent patterns, or modes, of ENSO-related variability in the SH atmospheric circulation can be separated from modes that are related to intraseasonal variability or to changes in radiative forcings. Under this methodology, the seasonal mean SH 500 hPa geopotential height is considered to consist of three components. These are: (1) an intraseasonal component related to internal dynamics on intraseasonal time scales; (2) a slow-internal component related to internal dynamics on slowly varying (interannual or longer) time scales, including ENSO; and (3) a slow-external component related to external (i.e. radiative) forcings. Empirical Orthogonal Functions (EOFs) are used to represent the modes of variability of the interannual covariance of the three components. An assessment is first made of the modes in models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) dataset for the SH summer and winter seasons in the 20th century. In reanalysis data, two EOFs of the slow component (which includes the slow-internal and slow-external components) have been found to be related to ENSO variability (Frederiksen and Zheng, 2007). In SH summer, the CMIP5 models reproduce the leading ENSO mode very well when the structures of the EOF and the associated SST, and associated variance are considered. There is substantial improvement in this mode when compared with the CMIP3 models shown in Grainger et al. (2012). However, the second ENSO mode in SH summer has a poorly reproduced EOF structure in the CMIP5 models, and the associated variance is generally underestimated. In SH winter, the performance of the CMIP5 models in reproducing the structure and variance is similar for both ENSO modes, with the associated variance being generally underestimated. Projected changes in the modes in the 21st century are then investigated using ensembles of CMIP5 models that reproduce well the 20th century slow modes. The slow-internal and slow-external components are examined separately, allowing the projected changes in the response to ENSO variability to be separated from the response to changes in greenhouse gas concentrations. By using several ensembles, the model-dependency of the projected changes in the ENSO-related slow-internal modes is examined. Frederiksen, C. S., and X. Zheng, 2007: Variability of seasonal-mean fields arising from intraseasonal variability. Part 3: Application to SH winter and summer circulations. Climate Dyn., 28, 849-866. Grainger, S., C. S. Frederiksen, and X. Zheng, 2012: Modes of interannual variability of Southern Hemisphere atmospheric circulation in CMIP3 models: Assessment and Projections. Climate Dyn., in press. Zheng, X., D. M. Straus, C. S. Frederiksen, and S. Grainger, 2009: Potentially predictable patterns of extratropical tropospheric circulation in an ensemble of climate simulations with the COLA AGCM. Quart. J. Roy. Meteor. Soc., 135, 1816-1829.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMNG34A..08H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMNG34A..08H"><span>Creation of Synthetic Surface Temperature and Precipitation Ensembles Through A Computationally Efficient, Mixed Method Approach</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hartin, C.; Lynch, C.; Kravitz, B.; Link, R. P.; Bond-Lamberty, B. P.</p> <p>2017-12-01</p> <p>Typically, uncertainty quantification of internal variability relies on large ensembles of climate model runs under multiple forcing scenarios or perturbations in a parameter space. Computationally efficient, standard pattern scaling techniques only generate one realization and do not capture the complicated dynamics of the climate system (i.e., stochastic variations with a frequency-domain structure). In this study, we generate large ensembles of climate data with spatially and temporally coherent variability across a subselection of Coupled Model Intercomparison Project Phase 5 (CMIP5) models. First, for each CMIP5 model we apply a pattern emulation approach to derive the model response to external forcing. We take all the spatial and temporal variability that isn't explained by the emulator and decompose it into non-physically based structures through use of empirical orthogonal functions (EOFs). Then, we perform a Fourier decomposition of the EOF projection coefficients to capture the input fields' temporal autocorrelation so that our new emulated patterns reproduce the proper timescales of climate response and "memory" in the climate system. Through this 3-step process, we derive computationally efficient climate projections consistent with CMIP5 model trends and modes of variability, which address a number of deficiencies inherent in the ability of pattern scaling to reproduce complex climate model behavior.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA093176','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA093176"><span>An Assessment of Team Development at the Air Force Flight Dynamics Laboratory.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>1980-09-01</p> <p>FLIGHT DYNAMICS LABORATORY S. PERFORMING OG. REPORT NUMGER 7. AUTHOR(*) S. CONTRACT ON GRANT NUMBER(s) illiam D. Rutley, Captain, USAF _. PERFORMING ...the change from 1978 to 1980 on eleven criterion variables, employee job satisfaction, job motivation and absenteeism ; five organizational climate...variables except absenteeism . Absenteeism data were obtained from AFFDL intern~al records. The four main pro- duct divisions of AFlDL se.-ve-i as subjects</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.8888B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.8888B"><span>Why inputs matter: Selection of climatic variables for species distribution modelling in the Himalayan region</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bobrowski, Maria; Schickhoff, Udo</p> <p>2017-04-01</p> <p>Betula utilis is a major constituent of alpine treeline ecotones in the western and central Himalayan region. The objective of this study is to provide first time analysis of the potential distribution of Betula utilis in the subalpine and alpine belts of the Himalayan region using species distribution modelling. Using Generalized Linear Models (GLM) we aim at examining climatic factors controlling the species distribution under current climate conditions. Furthermore we evaluate the prediction ability of climate data derived from different statistical methods. GLMs were created using least correlated bioclimatic variables derived from two different climate models: 1) interpolated climate data (i.e. Worldclim, Hijmans et al., 2005) and 2) quasi-mechanistical statistical downscaling (i.e. Chelsa; Karger et al., 2016). Model accuracy was evaluated by the ability to predict the potential species distribution range. We found that models based on variables of Chelsa climate data had higher predictive power, whereas models using Worldclim climate data consistently overpredicted the potential suitable habitat for Betula utilis. Although climatic variables of Worldclim are widely used in modelling species distribution, our results suggest to treat them with caution when remote regions like the Himalayan mountains are in focus. Unmindful usage of climatic variables for species distribution models potentially cause misleading projections and may lead to wrong implications and recommendations for nature conservation. References: Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978. Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N., Linder, H.P. & Kessler, M. (2016) Climatologies at high resolution for the earth land surface areas. arXiv:1607.00217 [physics].</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFMPP22A..04Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFMPP22A..04Z"><span>Model simulations and proxy-based reconstructions for the European region in the past millennium (Invited)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zorita, E.</p> <p>2009-12-01</p> <p>One of the objectives when comparing simulations of past climates to proxy-based climate reconstructions is to asses the skill of climate models to simulate climate change. This comparison may accomplished at large spatial scales, for instance the evolution of simulated and reconstructed Northern Hemisphere annual temperature, or at regional or point scales. In both approaches a 'fair' comparison has to take into account different aspects that affect the inevitable uncertainties and biases in the simulations and in the reconstructions. These efforts face a trade-off: climate models are believed to be more skillful at large hemispheric scales, but climate reconstructions are these scales are burdened by the spatial distribution of available proxies and by methodological issues surrounding the statistical method used to translate the proxy information into large-spatial averages. Furthermore, the internal climatic noise at large hemispheric scales is low, so that the sampling uncertainty tends to be also low. On the other hand, the skill of climate models at regional scales is limited by the coarse spatial resolution, which hinders a faithful representation of aspects important for the regional climate. At small spatial scales, the reconstruction of past climate probably faces less methodological problems if information from different proxies is available. The internal climatic variability at regional scales is, however, high. In this contribution some examples of the different issues faced when comparing simulation and reconstructions at small spatial scales in the past millennium are discussed. These examples comprise reconstructions from dendrochronological data and from historical documentary data in Europe and climate simulations with global and regional models. These examples indicate that the centennial climate variations can offer a reasonable target to assess the skill of global climate models and of proxy-based reconstructions, even at small spatial scales. However, as the focus shifts towards higher frequency variability, decadal or multidecadal, the need for larger simulation ensembles becomes more evident. Nevertheless,the comparison at these time scales may expose some lines of research on the origin of multidecadal regional climate variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.H33H..06B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.H33H..06B"><span>Climate change hampers endangered species through intensified moisture-related plant stresses (Invited)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bartholomeus, R.; Witte, J.; van Bodegom, P.; Dam, J. V.; Aerts, R.</p> <p>2010-12-01</p> <p>With recent climate change, extremes in meteorological conditions are forecast and observed to increase globally, and to affect vegetation composition. More prolonged dry periods will alternate with more intensive rainfall events, both within and between years, which will change soil moisture dynamics. In temperate climates, soil moisture, in concert with nutrient availability and soil acidity, is the most important environmental filter in determining local plant species composition, as it determines the availability of both oxygen and water to plant roots. These resources are indispensable for meeting the physiological demands of plants. The consequences of climate change for our natural environment are among the most pressing issues of our time. The international research community is beginning to realise that climate extremes may be more powerful drivers of vegetation change and species extinctions than slow-and-steady climatic changes, but the causal mechanisms of such changes are presently unknown. The roles of amplitudes in water availability as drivers of vegetation change have been particularly elusive owing to the lack of integration of the key variables involved. Here we show that the combined effect of increased rainfall variability, temperature and atmospheric CO2-concentration will lead to an increased variability in both wet and dry extremes in stresses faced by plants (oxygen and water stress, respectively). We simulated these plant stresses with a novel, process-based approach, incorporating in detail the interacting processes in the soil-plant-atmosphere interface. In order to quantify oxygen and water stress with causal measures, we focused on interacting meteorological, soil physical, microbial, and plant physiological processes in the soil-plant-atmosphere system. As both the supply and demand of oxygen and water depend strongly on the prevailing meteorological conditions, both oxygen and water stress were calculated dynamically in time to capture climate change effects. We demonstrate that increased rainfall variability in interaction with predicted changes in temperature and CO2, affects soil moisture conditions and plant oxygen and water demands such, that both oxygen stress and water stress will intensify due to climate change. Moreover, these stresses will increasingly coincide, causing variable stress conditions. These variable stress conditions were found to decrease future habitat suitability, especially for plant species that are presently endangered. The future existence of such species is thus at risk by climate change, which has direct implications for policies to maintain endangered species, as applied by international nature management organisations (e.g. IUCN). Our integrated mechanistic analysis of two stresses combined, which has never been done so far, reveals large impacts of climate change on species extinctions and thereby on biodiversity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018Geomo.304...40T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018Geomo.304...40T"><span>Climate change and water table fluctuation: Implications for raised bog surface variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Taminskas, Julius; Linkevičienė, Rita; Šimanauskienė, Rasa; Jukna, Laurynas; Kibirkštis, Gintautas; Tamkevičiūtė, Marija</p> <p>2018-03-01</p> <p>Cyclic peatland surface variability is influenced by hydrological conditions that highly depend on climate and/or anthropogenic activities. A low water level leads to a decrease of peatland surface and an increase of C emissions into the atmosphere, whereas a high water level leads to an increase of peatland surface and carbon sequestration in peatlands. The main aim of this article is to evaluate the influence of hydrometeorological conditions toward the peatland surface and its feedback toward the water regime. A regional survey of the raised bog water table fluctuation and surface variability was made in one of the largest peatlands in Lithuania. Two appropriate indicators for different peatland surface variability periods (increase and decrease) were detected. The first one is an 200 mm y- 1 average net rainfall over a three-year range. The second one is an average annual water depth of 25-30 cm. The application of these indicators enabled the reconstruction of Čepkeliai peatland surface variability during a 100 year period. Processes of peatland surface variability differ in time and in separate parts of peatland. Therefore, internal subbasins in peatland are formed. Subbasins involve autogenic processes that can later affect their internal hydrology, nutrient status, and vegetation succession. Internal hydrological conditions, surface fluctuation, and vegetation succession in peatland subbasins should be taken into account during evaluation of their state, nature management projects, and other peatland research works.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_5 --> <div id="page_6" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="101"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1412032G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1412032G"><span>Climate variability in China during the last millennium based on reconstructions and simulations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>García-Bustamante, E.; Luterbacher, J.; Xoplaki, E.; Werner, J. P.; Jungclaus, J.; Zorita, E.; González-Rouco, J. F.; Fernández-Donado, L.; Hegerl, G.; Ge, Q.; Hao, Z.; Wagner, S.</p> <p>2012-04-01</p> <p>Multi-decadal to centennial climate variability in China during the last millennium is analysed. We compare the low frequency temperature and precipitation variations from proxy-based reconstructions and palaeo-simulations from climate models. Focusing on the regional responses to the global climate evolution is of high relevance due to the complexity of the interactions between physical mechanisms at different spatio-temporal scales and the potential severity of the derived multiple socio-economic impacts. China stands out as a particularly interesting region, not only due to its complex climatic features, ranging from the semiarid northwestern Tibetan Plateau to the tropical monsoon southeastern climates, but also because of its wealth of proxy data. However, comprehensive assessments of proxy- and model-based information about palaeo-climatic variations in China are, to our knowledge, still lacking. In addition, existing studies depict a general lack of agreement between reconstructions and model simulations with respect to the amplitude and/or occurrence of warmer/colder and wetter/drier periods during the last millennium and the magnitude of the 20th century warming trend. Furthermore, these works are mainly focused on eastern China regions that show a denser proxy data coverage. We investigate how last millennium palaeo-runs compare to independent evidences from an unusual large number of proxy reconstructions over the study area by employing state-of-the-art palaeo-simulations with multi-member ensembles from the CMIP5/PMIP3 project. This shapes an ideal frame for the evaluation of the uncertainties associated to internal and intermodel model variability. Preliminary results indicate that despite the strong regional and seasonal dependencies, temperature reconstructions in China evidence coherent variations among all regions at centennial scale, especially during the last 500 years. The spatial consistency of low frequency temperature changes is an interesting aspect and of relevance for the assessment of forced climatic responses in China. The comparison between reconstructions and simulations from climate models show that, apart from the 20th century warming trend, the variance of the reconstructed mean China temperature lies in the envelope (uncertainty range) spanned by the temperature simulations. The uncertainty arises from the internal (multi-member ensembles) and the inter-model variability. Centennial variations tend to be broadly synchronous in the reconstructions and the simulations. However, the simulations show a delay of the warm period 1000-1300 AD. This warm medieval period both in the simulations and the reconstructions is followed by cooling till 1800 AD. Based on the simulations, the recent warming is not unprecedented and is comparable to the medieval warming. Further steps of this study will address the individual contribution of anthropogenic and natural forcings on climate variability and change during the last millennium in China. We will make use of of models that provide runs including single forcings (fingerprints) for the attribution of climate variations from decadal to multi-centennial time scales. With this aim, we will implement statistical techniques for the detection of optimal signal-to-noise-ratio between external forcings and internal variability of reconstructed temperatures and precipitation. To apply these approaches the uncertainties associated with both reconstructions and simulations will be estimated. The latter will shed some light into the mechanisms behind current climate evolution and will help to constrain uncertainties in the sensitivity of model simulations to increasing CO2 scenarios of future climate change. This work will also contribute to the overall aims of the PAGES 2k initiative in Asia (http://www.pages.unibe.ch/workinggroups/2k-network)</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eosweb.larc.nasa.gov/project/isccp/isccp-m_table','SCIGOV-ASDC'); return false;" href="https://eosweb.larc.nasa.gov/project/isccp/isccp-m_table"><span>ISCCP-M Data and Informtion</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://eosweb.larc.nasa.gov/">Atmospheric Science Data Center </a></p> <p></p> <p>2018-03-08</p> <p>ISCCP-M Data and Information Global Cloud Process Studies in the Context of ... Climate Variability: Enhancement and Continuation of Data Analysis for the International Satellite Cloud Climatology Project (ISCCP) ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28545590','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28545590"><span>Effect of climatic variability on malaria trends in Baringo County, Kenya.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Kipruto, Edwin K; Ochieng, Alfred O; Anyona, Douglas N; Mbalanya, Macrae; Mutua, Edna N; Onguru, Daniel; Nyamongo, Isaac K; Estambale, Benson B A</p> <p>2017-05-25</p> <p>Malaria transmission in arid and semi-arid regions of Kenya such as Baringo County, is seasonal and often influenced by climatic factors. Unravelling the relationship between climate variables and malaria transmission dynamics is therefore instrumental in developing effective malaria control strategies. The main aim of this study was to describe the effects of variability of rainfall, maximum temperature and vegetation indices on seasonal trends of malaria in selected health facilities within Baringo County, Kenya. Climate variables sourced from the International Research Institute (IRI)/Lamont-Doherty Earth Observatory (LDEO) climate database and malaria cases reported in 10 health facilities spread across four ecological zones (riverine, lowland, mid-altitude and highland) between 2004 and 2014 were subjected to a time series analysis. A negative binomial regression model with lagged climate variables was used to model long-term monthly malaria cases. The seasonal Mann-Kendall trend test was then used to detect overall monotonic trends in malaria cases. Malaria cases increased significantly in the highland and midland zones over the study period. Changes in malaria prevalence corresponded to variations in rainfall and maximum temperature. Rainfall at a time lag of 2 months resulted in an increase in malaria transmission across the four zones while an increase in temperature at time lags of 0 and 1 month resulted in an increase in malaria cases in the riverine and highland zones, respectively. Given the existence of a time lag between climatic variables more so rainfall and peak malaria transmission, appropriate control measures can be initiated at the onset of short and after long rains seasons.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhDT........71P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhDT........71P"><span>Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Parsons, Luke Alexander</p> <p></p> <p>Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall structure of the variance spectrum has important consequences for the probability of multi-year drought. Our lake record suggests there is a significant background threat of multi-year, and even decade-length, drought in western Amazonia, whereas climate model simulations indicate most droughts likely last no longer than one to three years. These findings suggest climate models may underestimate the future risk of extended drought in this important region. In Appendix C, we expand our analysis of climate variability beyond South America. We use observations, well-constrained tropical paleoclimate, and Earth system model data to examine the overall shape of the climate spectrum across interannual to century frequencies. We find a general agreement among observations and models that temperature variability increases with timescale across most of the globe outside the tropics. However, as compared to paleoclimate records, climate models generate too little low-frequency variability in the tropics (e.g., Laepple and Huybers, 2014). When we compare the shape of the simulated climate spectrum to the spectrum of a simple autoregressive process, we find much of the modeled surface temperature variability in the tropics could be explained by ocean smoothing of weather noise. Importantly, modeled precipitation tends to be similar to white noise across much of the globe. By contrast, paleoclimate records of various types from around the globe indicate that both temperature and precipitation variability should experience much more low-frequency variability than a simple autoregressive or white-noise process. In summary, state-of-the-art climate models generate some degree of dynamically driven low-frequency climate variability, especially at high latitudes. However, the latest climate models, observations, and paleoclimate data provide us with drastically different pictures of the background climate system and its associated risks. This research has important consequences for improving how we simulate climate extremes as we enter a warmer (and often drier) world in the coming centuries; if climate models underestimate low-frequency variability, we will underestimate the risk of future abrupt change and extreme events, such as megadroughts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ERL....10k4023N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ERL....10k4023N"><span>Climate change as a migration driver from rural and urban Mexico</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nawrotzki, Raphael J.; Hunter, Lori M.; Runfola, Daniel M.; Riosmena, Fernando</p> <p>2015-11-01</p> <p>Studies investigating migration as a response to climate variability have largely focused on rural locations to the exclusion of urban areas. This lack of urban focus is unfortunate given the sheer numbers of urban residents and continuing high levels of urbanization. To begin filling this empirical gap, this study investigates climate change impacts on US-bound migration from rural and urban Mexico, 1986-1999. We employ geostatistical interpolation methods to construct two climate change indices, capturing warm and wet spell duration, based on daily temperature and precipitation readings for 214 weather stations across Mexico. In combination with detailed migration histories obtained from the Mexican Migration Project, we model the influence of climate change on household-level migration from 68 rural and 49 urban municipalities. Results from multilevel event-history models reveal that a temperature warming and excessive precipitation significantly increased international migration during the study period. However, climate change impacts on international migration is only observed for rural areas. Interactions reveal a causal pathway in which temperature (but not precipitation) influences migration patterns through employment in the agricultural sector. As such, climate-related international migration may decline with continued urbanization and the resulting reductions in direct dependence of households on rural agriculture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26692890','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26692890"><span>Climate Change as Migration Driver from Rural and Urban Mexico.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Nawrotzki, Raphael J; Hunter, Lori M; Runfola, Daniel M; Riosmena, Fernando</p> <p>2015-11-01</p> <p>Studies investigating migration as a response to climate variability have largely focused on rural locations to the exclusion of urban areas. This lack of urban focus is unfortunate given the sheer numbers of urban residents and continuing high levels of urbanization. To begin filling this empirical gap, this study investigates climate change impacts on U.S.-bound migration from rural and urban Mexico, 1986-1999. We employ geostatistical interpolation methods to construct two climate change indices, capturing warm and wet spell duration, based on daily temperature and precipitation readings for 214 weather stations across Mexico. In combination with detailed migration histories obtained from the Mexican Migration Project, we model the influence of climate change on household-level migration from 68 rural and 49 urban municipalities. Results from multilevel event-history models reveal that a temperature warming and excessive precipitation significantly increased international migration during the study period. However, climate change impacts on international migration is only observed for rural areas. Interactions reveal a causal pathway in which temperature (but not precipitation) influences migration patterns through employment in the agricultural sector. As such, climate-related international migration may decline with continued urbanization and the resulting reductions in direct dependence of households on rural agriculture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC23F..04C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC23F..04C"><span>Variance decomposition shows the importance of human-climate feedbacks in the Earth system</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.</p> <p>2017-12-01</p> <p>The human and Earth systems are intricately linked: climate influences agricultural production, renewable energy potential, and water availability, for example, while anthropogenic emissions from industry and land use change alter temperature and precipitation. Such feedbacks have the potential to significantly alter future climate change. Current climate change projections contain significant uncertainties, however, and because Earth System Models do not generally include dynamic human (demography, economy, energy, water, land use) components, little is known about how climate feedbacks contribute to that uncertainty. Here we use variance decomposition of a novel coupled human-earth system model to show that the influence of human-climate feedbacks can be as large as 17% of the total variance in the near term for global mean temperature rise, and 11% in the long term for cropland area. The near-term contribution of energy and land use feedbacks to the climate on global mean temperature rise is as large as that from model internal variability, a factor typically considered in modeling studies. Conversely, the contribution of climate feedbacks to cropland extent, while non-negligible, is less than that from socioeconomics, policy, or model. Previous assessments have largely excluded these feedbacks, with the climate community focusing on uncertainty due to internal variability, scenario, and model and the integrated assessment community focusing on uncertainty due to socioeconomics, technology, policy, and model. Our results set the stage for a new generation of models and hypothesis testing to determine when and how bidirectional feedbacks between human and Earth systems should be considered in future assessments of climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA482695','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA482695"><span>The ARGO Project: Global Ocean Observations for Understanding and Prediction of Climate Variability. Report for Calendar Year 2004</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2004-01-01</p> <p>international Argo practices. Data appropriate for research applications and for comparison with climate change models are not available for several...global ocean heat and fresh water storage and the detection and attribution of climate change . These presentations can be accessed at http...stresses on ocean ecosystems have serious consequences, and sometimes dramatic ones, such as coral reef bleaching . In the future, the impacts of a</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A12H..05M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A12H..05M"><span>Variability of North Atlantic Hurricane Frequency in a Large Ensemble of High-Resolution Climate Simulations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mei, W.; Kamae, Y.; Xie, S. P.</p> <p>2017-12-01</p> <p>Forced and internal variability of North Atlantic hurricane frequency during 1951-2010 is studied using a large ensemble of climate simulations by a 60-km atmospheric general circulation model that is forced by observed sea surface temperatures (SSTs). The simulations well capture the interannual-to-decadal variability of hurricane frequency in best track data, and further suggest a possible underestimate of hurricane counts in the current best track data prior to 1966 when satellite measurements were unavailable. A genesis potential index (GPI) averaged over the Main Development Region (MDR) accounts for more than 80% of the forced variations in hurricane frequency, with potential intensity and vertical wind shear being the dominant factors. In line with previous studies, the difference between MDR SST and tropical mean SST is a simple but useful predictor; a one-degree increase in this SST difference produces 7.1±1.4 more hurricanes. The hurricane frequency also exhibits internal variability that is comparable in magnitude to the interannual variability. The 100-member ensemble allows us to address the following important questions: (1) Are the observations equivalent to one realization of such a large ensemble? (2) How many ensemble members are needed to reproduce the variability in observations and in the forced component of the simulations? The sources of the internal variability in hurricane frequency will be identified and discussed. The results provide an explanation for the relatively week correlation ( 0.6) between MDR GPI and hurricane frequency on interannual timescales in observations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC31F1164O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC31F1164O"><span>Reducing the Uncertainty in Atlantic Meridional Overturning Circulation Projections Using Bayesian Model Averaging</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Olson, R.; An, S. I.</p> <p>2016-12-01</p> <p>Atlantic Meridional Overturning Circulation (AMOC) in the ocean might slow down in the future, which can lead to a host of climatic effects in North Atlantic and throughout the world. Despite improvements in climate models and availability of new observations, AMOC projections remain uncertain. Here we constrain CMIP5 multi-model ensemble output with observations of a recently developed AMOC index to provide improved Bayesian predictions of future AMOC. Specifically, we first calculate yearly AMOC index loosely based on Rahmstorf et al. (2015) for years 1880—2004 for both observations, and the CMIP5 models for which relevant output is available. We then assign a weight to each model based on a Bayesian Model Averaging method that accounts for differential model skill in terms of both mean state and variability. We include the temporal autocorrelation in climate model errors, and account for the uncertainty in the parameters of our statistical model. We use the weights to provide future weighted projections of AMOC, and compare them to un-weighted ones. Our projections use bootstrapping to account for uncertainty in internal AMOC variability. We also perform spectral and other statistical analyses to show that AMOC index variability, both in models and in observations, is consistent with red noise. Our results improve on and complement previous work by using a new ensemble of climate models, a different observational metric, and an improved Bayesian weighting method that accounts for differential model skill at reproducing internal variability. Reference: Rahmstorf, S., Box, J. E., Feulner, G., Mann, M. E., Robinson, A., Rutherford, S., & Schaffernicht, E. J. (2015). Exceptional twentieth-century slowdown in atlantic ocean overturning circulation. Nature Climate Change, 5(5), 475-480. doi:10.1038/nclimate2554</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=commercial+AND+bank&pg=2&id=ED296407','ERIC'); return false;" href="https://eric.ed.gov/?q=commercial+AND+bank&pg=2&id=ED296407"><span>Internal Communication and Job Satisfaction Revisited: The Impact of Organizational Trust and Influence on Commercial Bank Supervisors.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Pincus, J. David; And Others</p> <p></p> <p>Using H. Dennis' (1974) five-factor communication climate construct framework as a predictor variable, a study investigated the relationship between perceptions of communication climate and job satisfaction of supervisory employees in the banking industry. A systematic random sample was drawn from 68 commercial banks in Orange County, California,…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24955649','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24955649"><span>Climate and atmosphere simulator for experiments on ecological systems in changing environments.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Verdier, Bruno; Jouanneau, Isabelle; Simonnet, Benoit; Rabin, Christian; Van Dooren, Tom J M; Delpierre, Nicolas; Clobert, Jean; Abbadie, Luc; Ferrière, Régis; Le Galliard, Jean-François</p> <p>2014-01-01</p> <p>Grand challenges in global change research and environmental science raise the need for replicated experiments on ecosystems subjected to controlled changes in multiple environmental factors. We designed and developed the Ecolab as a variable climate and atmosphere simulator for multifactor experimentation on natural or artificial ecosystems. The Ecolab integrates atmosphere conditioning technology optimized for accuracy and reliability. The centerpiece is a highly contained, 13-m(3) chamber to host communities of aquatic and terrestrial species and control climate (temperature, humidity, rainfall, irradiance) and atmosphere conditions (O2 and CO2 concentrations). Temperature in the atmosphere and in the water or soil column can be controlled independently of each other. All climatic and atmospheric variables can be programmed to follow dynamical trajectories and simulate gradual as well as step changes. We demonstrate the Ecolab's capacity to simulate a broad range of atmospheric and climatic conditions, their diurnal and seasonal variations, and to support the growth of a model terrestrial plant in two contrasting climate scenarios. The adaptability of the Ecolab design makes it possible to study interactions between variable climate-atmosphere factors and biotic disturbances. Developed as an open-access, multichamber platform, this equipment is available to the international scientific community for exploring interactions and feedbacks between ecological and climate systems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1235117-el-nino-southern-oscillation-frequency-cascade','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1235117-el-nino-southern-oscillation-frequency-cascade"><span>El Niño$-$Southern Oscillation frequency cascade</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Stuecker, Malte F.; Jin, Fei -Fei; Timmermann, Axel</p> <p>2015-10-19</p> <p>The El Niño$-$Southern Oscillation (ENSO) phenomenon, the most pronounced feature of internally generated climate variability, occurs on interannual timescales and impacts the global climate system through an interaction with the annual cycle. The tight coupling between ENSO and the annual cycle is particularly pronounced over the tropical Western Pacific. In this paper, we show that this nonlinear interaction results in a frequency cascade in the atmospheric circulation, which is characterized by deterministic high-frequency variability on near-annual and subannual timescales. Finally, through climate model experiments and observational analysis, it is documented that a substantial fraction of the anomalous Northwest Pacific anticyclonemore » variability, which is the main atmospheric link between ENSO and the East Asian Monsoon system, can be explained by these interactions and is thus deterministic and potentially predictable.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1235117-el-nino-southern-oscillation-frequency-cascade','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1235117-el-nino-southern-oscillation-frequency-cascade"><span>El Niño$-$Southern Oscillation frequency cascade</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Stuecker, Malte F.; Jin, Fei -Fei; Timmermann, Axel</p> <p></p> <p>The El Niño$-$Southern Oscillation (ENSO) phenomenon, the most pronounced feature of internally generated climate variability, occurs on interannual timescales and impacts the global climate system through an interaction with the annual cycle. The tight coupling between ENSO and the annual cycle is particularly pronounced over the tropical Western Pacific. In this paper, we show that this nonlinear interaction results in a frequency cascade in the atmospheric circulation, which is characterized by deterministic high-frequency variability on near-annual and subannual timescales. Finally, through climate model experiments and observational analysis, it is documented that a substantial fraction of the anomalous Northwest Pacific anticyclonemore » variability, which is the main atmospheric link between ENSO and the East Asian Monsoon system, can be explained by these interactions and is thus deterministic and potentially predictable.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A11L0165G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A11L0165G"><span>Implications of climate variability for monitoring the effectiveness of global mercury policy</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Giang, A.; Monier, E.; Couzo, E. A.; Pike-thackray, C.; Selin, N. E.</p> <p>2016-12-01</p> <p>We investigate how climate variability affects ability to detect policy-related anthropogenic changes in mercury emissions in wet deposition monitoring data using earth system and atmospheric chemistry modeling. The Minamata Convention, a multilateral environmental agreement that aims to protect human health and the environment from anthropogenic emissions and releases of mercury, includes provisions for monitoring treaty effectiveness. Because meteorology can affect mercury chemistry and transport, internal variability is an important contributor to uncertainty in how effective policy may be in reducing the amount of mercury entering ecosystems through wet deposition. We simulate mercury chemistry using the GEOS-Chem global transport model to assess the influence of meteorology in the context of other uncertainties in mercury cycling and policy. In these simulations, we find that interannual variability in meteorology may be a dominant contributor to the spatial pattern and magnitude of historical regional wet deposition trends. To further assess the influence of climate variability in the GEOS-Chem mercury simulation, we use a 5-member ensemble of meteorological fields from the MIT Integrated Global System Model under present and future climate. Each member involves randomly initialized 20 year simulations centered around 2000 and 2050 (under a no-policy and a climate stabilization scenario). Building on previous efforts to understand climate-air quality interactions for ground-level O3 and particulate matter, we estimate from the ensemble the range of trends in mercury wet deposition given natural variability, and, to extend our previous results on regions that are sensitive to near-source vs. remote anthropogenic signals, we identify geographic regions where mercury wet deposition is most sensitive to this variability. We discuss how an improved understanding of natural variability can inform the Conference of Parties on monitoring strategy and policy ambition.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29133863','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29133863"><span>A real-time Global Warming Index.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Haustein, K; Allen, M R; Forster, P M; Otto, F E L; Mitchell, D M; Matthews, H D; Frame, D J</p> <p>2017-11-13</p> <p>We propose a simple real-time index of global human-induced warming and assess its robustness to uncertainties in climate forcing and short-term climate fluctuations. This index provides improved scientific context for temperature stabilisation targets and has the potential to decrease the volatility of climate policy. We quantify uncertainties arising from temperature observations, climate radiative forcings, internal variability and the model response. Our index and the associated rate of human-induced warming is compatible with a range of other more sophisticated methods to estimate the human contribution to observed global temperature change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMNG41A0121M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMNG41A0121M"><span>Extracting Leading Nonlinear Modes of Changing Climate From Global SST Time Series</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mukhin, D.; Gavrilov, A.; Loskutov, E. M.; Feigin, A. M.; Kurths, J.</p> <p>2017-12-01</p> <p>Data-driven modeling of climate requires adequate principal variables extracted from observed high-dimensional data. For constructing such variables it is needed to find spatial-temporal patterns explaining a substantial part of the variability and comprising all dynamically related time series from the data. The difficulties of this task rise from the nonlinearity and non-stationarity of the climate dynamical system. The nonlinearity leads to insufficiency of linear methods of data decomposition for separating different processes entangled in the observed time series. On the other hand, various forcings, both anthropogenic and natural, make the dynamics non-stationary, and we should be able to describe the response of the system to such forcings in order to separate the modes explaining the internal variability. The method we present is aimed to overcome both these problems. The method is based on the Nonlinear Dynamical Mode (NDM) decomposition [1,2], but takes into account external forcing signals. An each mode depends on hidden, unknown a priori, time series which, together with external forcing time series, are mapped onto data space. Finding both the hidden signals and the mapping allows us to study the evolution of the modes' structure in changing external conditions and to compare the roles of the internal variability and forcing in the observed behavior. The method is used for extracting of the principal modes of SST variability on inter-annual and multidecadal time scales accounting the external forcings such as CO2, variations of the solar activity and volcanic activity. The structure of the revealed teleconnection patterns as well as their forecast under different CO2 emission scenarios are discussed.[1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ASCMO...3...33P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ASCMO...3...33P"><span>Estimating trends in the global mean temperature record</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Poppick, Andrew; Moyer, Elisabeth J.; Stein, Michael L.</p> <p>2017-06-01</p> <p>Given uncertainties in physical theory and numerical climate simulations, the historical temperature record is often used as a source of empirical information about climate change. Many historical trend analyses appear to de-emphasize physical and statistical assumptions: examples include regression models that treat time rather than radiative forcing as the relevant covariate, and time series methods that account for internal variability in nonparametric rather than parametric ways. However, given a limited data record and the presence of internal variability, estimating radiatively forced temperature trends in the historical record necessarily requires some assumptions. Ostensibly empirical methods can also involve an inherent conflict in assumptions: they require data records that are short enough for naive trend models to be applicable, but long enough for long-timescale internal variability to be accounted for. In the context of global mean temperatures, empirical methods that appear to de-emphasize assumptions can therefore produce misleading inferences, because the trend over the twentieth century is complex and the scale of temporal correlation is long relative to the length of the data record. We illustrate here how a simple but physically motivated trend model can provide better-fitting and more broadly applicable trend estimates and can allow for a wider array of questions to be addressed. In particular, the model allows one to distinguish, within a single statistical framework, between uncertainties in the shorter-term vs. longer-term response to radiative forcing, with implications not only on historical trends but also on uncertainties in future projections. We also investigate the consequence on inferred uncertainties of the choice of a statistical description of internal variability. While nonparametric methods may seem to avoid making explicit assumptions, we demonstrate how even misspecified parametric statistical methods, if attuned to the important characteristics of internal variability, can result in more accurate uncertainty statements about trends.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSPC54C2279D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSPC54C2279D"><span>Can unforced radiative variability explain the "hiatus"?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Donohoe, A.</p> <p>2016-02-01</p> <p>The paradox of the "hiatus" is characterized as a decade long period over which global mean surface temperature remained relatively constant even though greenhouse forcing forcing is believed to have been positive and increasing. Explanations of the hiatus have focused on two primary lines of thought: 1. There was a net radiative imbalance at the top of atmosphere (TOA) but this energy input was stored in the ocean without increasing surface temperature or 2. There was no radiative imbalance at the TOA because the greenhouse forcing was offset by other climate forcings. Here, we explore a third hypothesis: that there was no TOA radiative imbalance over the decade due to unforced, natural modes of radiative variability that are unrelated to global mean temperature. Is it possible that the Earth could emit enough radiation to offset greenhouse forcing without increasing its temperature due to internal modes of climate variability? Global mean TOA energy imbalance is estimated to be 0.65 W m-2 as determined from the long term change in ocean heat content - where the majority of the energy imbalance is stored. Therefore, in order to offset this TOA energy imbalance natural modes of radiative variability with amplitudes of order 0.5 W m-2 at the decadal timescale are required. We demonstrate that unforced coupled climate models have global mean radiative variability of the required magnitude (2 standard deviations of 0.57 W m-2 in the inter-model mean) and that the vast majority (>90%) of this variability is unrelated to surface temperature radiative feedbacks. However, much of this variability is at shorter (monthly and annual) timescales and does not persist from year to year making the possibility of a decade long natural interruption of the energy accumulation in the climate system unlikely due to natural radiative variability alone given the magnitude of the greenhouse forcing on Earth. Comparison to observed satellite data suggest the models capture the magnitude (2 sigma = 0.61 W m-2) and mechanisms of internal radiative variability but we cannot exclude the possibility of low frequency modes of variability with significant magnitude given the limited length of the satellite record.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018NatCC...8..414L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018NatCC...8..414L"><span>Early emergence of anthropogenically forced heat waves in the western United States and Great Lakes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lopez, Hosmay; West, Robert; Dong, Shenfu; Goni, Gustavo; Kirtman, Ben; Lee, Sang-Ki; Atlas, Robert</p> <p>2018-05-01</p> <p>Climate projections for the twenty-first century suggest an increase in the occurrence of heat waves. However, the time at which externally forced signals of anthropogenic climate change (ACC) emerge against background natural variability (time of emergence (ToE)) has been challenging to quantify, which makes future heat-wave projections uncertain. Here we combine observations and model simulations under present and future forcing to assess how internal variability and ACC modulate US heat waves. We show that ACC dominates heat-wave occurrence over the western United States and Great Lakes regions, with ToE that occurred as early as the 2020s and 2030s, respectively. In contrast, internal variability governs heat waves in the northern and southern Great Plains, where ToE occurs in the 2050s and 2070s; this later ToE is believed to be a result of a projected increase in circulation variability, namely the Great Plain low-level jet. Thus, greater mitigation and adaptation efforts are needed in the Great Lakes and western United States regions.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_6 --> <div id="page_7" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="121"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A41C2289V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A41C2289V"><span>Evaluating the ClimEx Single Model Large Ensemble in Comparison with EURO-CORDEX Results of Seasonal Means and Extreme Precipitation Indicators</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>von Trentini, F.; Schmid, F. J.; Braun, M.; Brisette, F.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.</p> <p>2017-12-01</p> <p>Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several extreme indicators like R95pTOT, RX5day and others are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1514190L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1514190L"><span>The MedCLIVAR Network</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lionello, Piero; Medclivar sg, The</p> <p>2013-04-01</p> <p>The MedCLIVAR initiative was first proposed at the 2003 European Geosciences Union assembly in Nice, France. In 2005, it was endorsed by the International Climate Variability and Predictability (CLIVAR) office. Subsequently, the MedCLIVAR Research Network Project was formally approved by the European Science Foundation and launched in May 2006 with the support of funding agencies from 12 countries. Since then, MedCLIVAR has served as a scientific network to promote interaction among different scientific disciplines and to develop a multidisciplinary vision of the evolution of the Mediterranean climate through studies that integrate atmospheric, marine, and terrestrial climate components at time scales ranging from paleoreconstructions to future climate scenarios. Presently, the network continues dealing with scientific issues including past climate variability; connections between the Mediterranean and global climate; the Mediterranean Sea circulation and sea level; feedbacks on the global climate system; and regional responses to greenhouse gas, air pollution, and aerosols. Its present activities include the publication of a newsletter, the organization of the next MedCLIVAR conference in 2014 and the publication of a special issue of Regional Environmental Change devoted to the climate of the Mediterranean region.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018QSRv..189...31H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018QSRv..189...31H"><span>Punctuated Holocene climate of Vestfirðir, Iceland, linked to internal/external variables and oceanographic conditions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Harning, David J.; Geirsdóttir, Áslaug; Miller, Gifford H.</p> <p>2018-06-01</p> <p>Emerging Holocene paleoclimate datasets point to a non-linear response of Icelandic climate against a background of steady orbital cooling. The Vestfirðir peninsula (NW Iceland) is an ideal target for continued climate reconstructions due to the presence of a small ice cap (Drangajökull) and numerous lakes, which provide two independent means to evaluate existing Icelandic climate records and to constrain the forcing mechanisms behind centennial-scale cold anomalies. Here, we present new evidence for Holocene expansions of Drangajökull based on 14C dates from entombed dead vegetation as well as two continuous Holocene lake sediment records. Lake sediments were analyzed for both bulk physical (MS) and biological (%TOC, δ13C, C/N, and BSi) parameters. Composite BSi and C/N records from the two lakes yield a sub-centennial qualitative perspective on algal (diatom) productivity and terrestrial landscape stability, respectively. The Vestfirðir lake proxies suggest initiation of the Holocene Thermal Maximum by ∼8.8 ka with subsequent and pronounced cooling not apparent until ∼3 ka. Synchronous periods of reduced algal productivity and accelerated landscape instability point to cold anomalies centered at ∼8.2, 6.6, 4.2, 3.3, 2.3, 1.8, 1, and 0.25 ka. Triggers for cold anomalies are linked to variable combinations of freshwater pulses, low total solar irradiance, explosive and effusive volcanism, and internal modes of climate variability, with cooling likely sustained by ocean/sea-ice feedbacks. The climate evolution reflected by our glacial and organic proxy records corresponds closely to marine records from the North Iceland Shelf.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1914547S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1914547S"><span>The role of internal variability for decadal carbon uptake anomalies in the Southern Ocean</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Spring, Aaron; Hi, Hongmei; Ilyina, Tatiana</p> <p>2017-04-01</p> <p>The Southern Ocean is a major sink for anthropogenic CO2 emissions and hence it plays an essential role in modulating global carbon cycle and climate change. Previous studies based on observations (e.g., Landschützer et al. 2015) show pronounced decadal variations of carbon uptake in the Southern Ocean in recent decades and this variability is largely driven by internal climate variability. However, due to limited ensemble size of simulations, the variability of this important ocean sink is still poorly assessed by the state-of-the-art earth system models (ESMs). To assess the internal variability of carbon sink in the Southern Ocean, we use a large ensemble of 100 member simulations based on the Max Planck Institute-ESM (MPI-ESM). The large ensemble of simulations is generated via perturbed initial conditions in the ocean and atmosphere. Each ensemble member includes a historical simulation from 1850 to 2005 with an extension until 2100 under Representative Concentration Pathway (RCP) 4.5 future projections. Here we use model simulations from 1980-2015 to compare with available observation-based dataset. We found several ensemble members showing decadal decreasing trends in the carbon sink, which are similar to the trend shown in observations. This result suggests that MPI-ESM large ensemble simulations are able to reproduce decadal variation of carbon sink in the Southern Ocean. Moreover, the decreasing trends of Southern Ocean carbon sink in MPI-ESM are mainly contributed by region between 50-60°S. To understand the internal variability of the air-sea carbon fluxes in the Southern Ocean, we further investigate the variability of underlying processes, such as physical climate variability and ocean biological processes. Our results indicate two main drivers for the decadal decreasing trend of carbon sink: i) Intensified winds enhance upwelling of old carbon-rich waters, this leads to increase of the ocean surface pCO2; ii) Primary production is reduced in area from 50-60°S, probably induced by reduced euphotic water column stability; therefore the biological drawdown of ocean surface pCO2 is weakened accordingly and hence the ocean is in favor of carbon outgassing. Landschützer, et al. (2015): The reinvigoration of the Southern Ocean carbon sink, Science, 349, 1221-1224.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA.....9175S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA.....9175S"><span>Is modern climate variability reflected in compund specific hydrogen isotope ratios of sedimentary biomarkers?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sachse, D.; Radke, J.; Gleixner, G.</p> <p>2003-04-01</p> <p>Compound specific hydrogen isotope ratios are emerging as a new palaeoclimatic and palaeohydrological proxy. First reconstructions of palaeoclimate using D/H ratios from n-alkanes are available (Andersen et al. 2001, Sauer et al. 2001, Sachse et al. 2003). However, a systematic approach comparing recent sedimentary biomarkers with climate data is still lacking. We are establishing an ecosystem study of small, ground water fed lakes with known limnology. Nearly all lakes are close to a long-term climate-monitoring site (CARBOEUROPE flux tower site, IAEA precipitation monitoring) delivering ecophysiological and climatic data as temperature, precipitation, evapotranspiration etc. Water, primary biomass, plant, soil and sediment were sampled from lakes and the surrounding ecosystem along a climatic and isotopic gradient in meteoric waters from northern Finland (deltaD: -130 permil vs. VSMOW) to southern Italy (deltaD: -30 permil vs. VSMOW, IAEA 2001). Biomarkers were extracted from the samples to test if climatic variability is reflected in their D/H ratios. First results of the factors influencing the hydrogen isotope composition of sedimentary biomarkers and their use as palaeoclimatic and palaeohydrological proxy will be presented. Andersen N, Paul HA, Bernasconi SM, McKenzie JA, Behrens A, Schaeffer P, Albrecht P (2001) Large and rapid climate variability during the Messinian salinity crisis: Evidence from deuterium concentrations of individual biomarkers. Geology 29:799-802 IAEA (2001) GNIP Maps and Animations. International Atomic Energy Agency, Vienna. Accessible at http://isohis.iaea.org Sachse D, Radke J, Gaupp R, Schwark L, Lüniger G, Gleixner G (2003) Reconstruction of palaeohydrological conditions in a lagoon during the 2nd Zechstein cycle through simultaneous use of deltaD values of individual n-alkanes and delta18O and delta13C values of carbonates. International Journal of Earth Sciences, submitted Sauer PE, Eglington TI, Hayes JM, Schimmelman A, Sessions AL (2001) Compound-specific D/H ratios of lipid biomarkers from sediments as a proxy for environmental and climatic conditions. Geochimica et Cosmochimica Acta 65:213-222</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1306152','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1306152"><span></span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Elliott, Elizabeth J.; Yu, Sungduk; Kooperman, Gabriel J.</p> <p></p> <p>The sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global-scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger-scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS-likemore » events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP-CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS-like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five-summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one-moment and two-moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP-GCMs. Furthermore, these results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1112627H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1112627H"><span>Water management to cope with and adapt to climate variability and change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hamdy, A.; Trisorio-Liuzzi, G.</p> <p>2009-04-01</p> <p>In many parts of the world, variability in climatic conditions is already resulting in major impacts. These impacts are wide ranging and the link to water management problems is obvious and profound. The know-how and the available information undoubtedly indicate that climate change will lead to an intensification of the global hydrological cycle and can have major impacts on regional water resources, affecting both ground and surface water supply for sectorial water uses and, in particular, the irrigation field imposing notable negative effects on food security and poverty alleviation programs in most arid and semi-arid developing countries. At the United Nations Millennium Summit, in September 2000, world leaders adopted the Millennium Development Declaration. From this declaration, the IWRM was recognised as the key concept the water sector should be using for water related development and measures and, hence, for achieving the water related MDG's. However, the potential impacts of climate change and increasing climate variability are not sufficiently addressed in the IWRM plans. Indeed, only a very limited IWRM national plans have been prepared, coping with climate variability and changes. This is mainly due to the lack of operational instruments to deal with climate change and climate variability issues. This is particularly true in developing countries where the financial, human and ecological impacts are potentially greatest and where water resources may be already highly stressed, but the capacity to cope and adapt is weakest. Climate change has now brought realities including mainly rising temperatures and increasing frequency of floods and droughts that present new challenges to be addressed by the IWRM practice. There are already several regional and international initiatives underway that focus on various aspects of water resources management those to be linked with climate changes and vulnerability issues. This is the way where the water resources management and climate scientist communities are engaged in a process for building confidence and understanding, identifying options and defining the water resources management strategies which to cope with impacts of climate variability and change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.4171O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.4171O"><span>North Atlantic observations sharpen meridional overturning projections</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Olson, R.; An, S.-I.; Fan, Y.; Evans, J. P.; Caesar, L.</p> <p>2018-06-01</p> <p>Atlantic Meridional Overturning Circulation (AMOC) projections are uncertain due to both model errors, as well as internal climate variability. An AMOC slowdown projected by many climate models is likely to have considerable effects on many aspects of global and North Atlantic climate. Previous studies to make probabilistic AMOC projections have broken new ground. However, they do not drift-correct or cross-validate the projections, and do not fully account for internal variability. Furthermore, they consider a limited subset of models, and ignore the skill of models at representing the temporal North Atlantic dynamics. We improve on previous work by applying Bayesian Model Averaging to weight 13 Coupled Model Intercomparison Project phase 5 models by their skill at modeling the AMOC strength, and its temporal dynamics, as approximated by the northern North-Atlantic temperature-based AMOC Index. We make drift-corrected projections accounting for structural model errors, and for the internal variability. Cross-validation experiments give approximately correct empirical coverage probabilities, which validates our method. Our results present more evidence that AMOC likely already started slowing down. While weighting considerably moderates and sharpens our projections, our results are at low end of previously published estimates. We project mean AMOC changes between periods 1960-1999 and 2060-2099 of -4.0 Sv and -6.8 Sv for RCP4.5 and RCP8.5 emissions scenarios respectively. The corresponding average 90% credible intervals for our weighted experiments are [-7.2, -1.2] and [-10.5, -3.7] Sv respectively for the two scenarios.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4674075','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4674075"><span>Climate Change as Migration Driver from Rural and Urban Mexico</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Hunter, Lori M.; Runfola, Daniel M.; Riosmena, Fernando</p> <p>2015-01-01</p> <p>Studies investigating migration as a response to climate variability have largely focused on rural locations to the exclusion of urban areas. This lack of urban focus is unfortunate given the sheer numbers of urban residents and continuing high levels of urbanization. To begin filling this empirical gap, this study investigates climate change impacts on U.S.-bound migration from rural and urban Mexico, 1986–1999. We employ geostatistical interpolation methods to construct two climate change indices, capturing warm and wet spell duration, based on daily temperature and precipitation readings for 214 weather stations across Mexico. In combination with detailed migration histories obtained from the Mexican Migration Project, we model the influence of climate change on household-level migration from 68 rural and 49 urban municipalities. Results from multilevel event-history models reveal that a temperature warming and excessive precipitation significantly increased international migration during the study period. However, climate change impacts on international migration is only observed for rural areas. Interactions reveal a causal pathway in which temperature (but not precipitation) influences migration patterns through employment in the agricultural sector. As such, climate-related international migration may decline with continued urbanization and the resulting reductions in direct dependence of households on rural agriculture. PMID:26692890</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1356931','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1356931"><span></span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Buechler, Elizabeth D.; Pallin, Simon B.; Boudreaux, Philip R.</p> <p></p> <p>The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, HVAC system performance, and occupant comfort. Therefore, indoor climate data is generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies is influenced by weather, occupant behavior and internal loads, and is generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ClDy...43.1693P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ClDy...43.1693P"><span>On the use of nudging techniques for regional climate modeling: application for tropical convection</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pohl, Benjamin; Crétat, Julien</p> <p>2014-09-01</p> <p>Using a large set of WRF ensemble simulations at 70-km horizontal resolution over a domain encompassing the Warm Pool region and its surroundings [45°N-45°S, 10°E-240°E], this study aims at quantifying how nudging techniques can modify the simulation of deep atmospheric convection. Both seasonal mean climate, transient variability at intraseasonal timescales, and the respective weight of internal (stochastic) and forced (reproducible) variability are considered. Sensitivity to a large variety of nudging settings (nudged variables and layers and nudging strength) and to the model physics (using 3 convective parameterizations) is addressed. Integrations are carried out during a 7-month season characterized by neutral background conditions and strong intraseasonal variability. Results show that (1) the model responds differently to the nudging from one parameterization to another. Biases are decreased by ~50 % for Betts-Miller-Janjic convection against 17 % only for Grell-Dévényi, the scheme producing yet the largest biases; (2) relaxing air temperature is the most efficient way to reduce biases, while nudging the wind increases most co-variability with daily observations; (3) the model's internal variability is drastically reduced and mostly depends on the nudging strength and nudged variables; (4) interrupting the relaxation before the end of the simulations leads to an abrupt convergence towards the model's natural solution, with no clear effects on the simulated climate after a few days. The usefulness and limitations of the approach are finally discussed through the example of the Madden-Julian Oscillation, that the model fails at simulating and that can be artificially and still imperfectly reproduced in relaxation experiments.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26919189','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26919189"><span>Global vegetation productivity response to climatic oscillations during the satellite era.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gonsamo, Alemu; Chen, Jing M; Lombardozzi, Danica</p> <p>2016-10-01</p> <p>Climate control on global vegetation productivity patterns has intensified in response to recent global warming. Yet, the contributions of the leading internal climatic variations to global vegetation productivity are poorly understood. Here, we use 30 years of global satellite observations to study climatic variations controls on continental and global vegetation productivity patterns. El Niño-Southern Oscillation (ENSO) phases (La Niña, neutral, and El Niño years) appear to be a weaker control on global-scale vegetation productivity than previously thought, although continental-scale responses are substantial. There is also clear evidence that other non-ENSO climatic variations have a strong control on spatial patterns of vegetation productivity mainly through their influence on temperature. Among the eight leading internal climatic variations, the East Atlantic/West Russia Pattern extensively controls the ensuing year vegetation productivity of the most productive tropical and temperate forest ecosystems of the Earth's vegetated surface through directionally consistent influence on vegetation greenness. The Community Climate System Model (CCSM4) simulations do not capture the observed patterns of vegetation productivity responses to internal climatic variations. Our analyses show the ubiquitous control of climatic variations on vegetation productivity and can further guide CCSM and other Earth system models developments to represent vegetation response patterns to unforced variability. Several winter time internal climatic variation indices show strong potentials on predicting growing season vegetation productivity two to six seasons ahead which enables national governments and farmers forecast crop yield to ensure supplies of affordable food, famine early warning, and plan management options to minimize yield losses ahead of time. © 2016 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14...80K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14...80K"><span>An Interface between Law and Science: The Climate Change Regime</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kuleshov, Y.; Grandbois, M.; Kaniaha, S.</p> <p>2012-04-01</p> <p>Law and Science are jointly building the international climate change regime. Up to date, international law and climate science have been unable to take into consideration both regional law and Pacific climate science in this process. Under the International Climate Change Adaptation Initiative (the Australian Government Initiative to assist with high priority climate adaptation needs in vulnerable countries in the Asia-Pacific region) significant efforts were dedicated to improve understanding of climate in the Pacific through the Pacific Climate Change Science Program (PCCSP) and through the Pacific Adaptation Strategy Assistance Program (PASAP). The first comprehensive PCCSP scientific report on the South Pacific climate has been published in 2011. Under the PASAP, web-based information tools for seasonal climate prediction have been developed and now outputs from dynamical climate model are used in 15 countries of the North-West and South Pacific for enhanced prediction of rainfall, air and sea surface temperatures which reduces countries' vulnerability to climate variability in the context of a changing climate. On a regional scale, the Meteorological and Geohazards Department of Vanuatu is preparing a full report on Climate change impacts on the country. These scientific reports and tools could lead to a better understanding of climate change in the South Pacific and to a better understanding of climate change science, for lawyers and policy-makers. The International climate change regime develops itself according to science findings, and at the pace of the four scientific reports issued by the Intergovernmental Panel on Climate Change (IPCC). In return, Law is a contributing factor to climate change, a structural data in the development and perception of environmental issues and it exerts an influence on Science. Because of the dependency of law on science, the PCCSP and PASAP outcomes will also stimulate and orientate developments in law of the Pacific Island countries, as well as it could increase countries' contributions to the future of international environmental law. Vanuatu is pioneering this process in the Pacific and could make a leading contribution to the development of Nationally appropriate mitigation actions by developing country Parties, according to the Bali action Plan and to participate actively in the negotiations of a successor agreement to the Kyoto Protocol. In studying and transposing the national climate change report, Vanuatu would also sensibly improve its own environmental laws in response to climate change. By building a bridge between law and science in the Pacific, we are training scientists to climate change law, and training lawyers and policy-makers to climate change science; increasing the collaborative process and the cooperation between scientists and lawyers, in drafting national environmental laws and in negotiating international climate change agreements; and enhancing the contribution of small vulnerable islands to the development of the international climate change regime, as it regards to law and to science. Training for climate scientists and for lawyers and policy-makers on climate change science and law will be provided through the USP Course on climate change international law and climate change science - the first course on this type in the Pacific.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMIN32B..01T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMIN32B..01T"><span>A new statistical tool for NOAA local climate studies</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Timofeyeva, M. M.; Meyers, J. C.; Hollingshead, A.</p> <p>2011-12-01</p> <p>The National Weather Services (NWS) Local Climate Analysis Tool (LCAT) is evolving out of a need to support and enhance the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) field offices' ability to efficiently access, manipulate, and interpret local climate data and characterize climate variability and change impacts. LCAT will enable NOAA's staff to conduct regional and local climate studies using state-of-the-art station and reanalysis gridded data and various statistical techniques for climate analysis. The analysis results will be used for climate services to guide local decision makers in weather and climate sensitive actions and to deliver information to the general public. LCAT will augment current climate reference materials with information pertinent to the local and regional levels as they apply to diverse variables appropriate to each locality. The LCAT main emphasis is to enable studies of extreme meteorological and hydrological events such as tornadoes, flood, drought, severe storms, etc. LCAT will close a very critical gap in NWS local climate services because it will allow addressing climate variables beyond average temperature and total precipitation. NWS external partners and government agencies will benefit from the LCAT outputs that could be easily incorporated into their own analysis and/or delivery systems. Presently we identified five existing requirements for local climate: (1) Local impacts of climate change; (2) Local impacts of climate variability; (3) Drought studies; (4) Attribution of severe meteorological and hydrological events; and (5) Climate studies for water resources. The methodologies for the first three requirements will be included in the LCAT first phase implementation. Local rate of climate change is defined as a slope of the mean trend estimated from the ensemble of three trend techniques: (1) hinge, (2) Optimal Climate Normals (running mean for optimal time periods), (3) exponentially-weighted moving average. Root mean squared error is used to determine the best fit of trend to the observations with the least error. The studies of climate variability impacts on local extremes use composite techniques applied to various definitions of local variables: from specified percentiles to critical thresholds. Drought studies combine visual capabilities of Google maps with statistical estimates of drought severity indices. The process of development will be linked to local office interactions with users to ensure the tool will meet their needs as well as provide adequate training. A rigorous internal and tiered peer-review process will be implemented to ensure the studies are scientifically-sound that will be published and submitted to the local studies catalog (database) and eventually to external sources, such as the Climate Portal.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1356931-probabilistic-modeling-indoor-climates-residential-buildings-using-energyplus','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1356931-probabilistic-modeling-indoor-climates-residential-buildings-using-energyplus"><span>Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Buechler, Elizabeth D.; Pallin, Simon B.; Boudreaux, Philip R.; ...</p> <p>2017-04-25</p> <p>The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, HVAC system performance, and occupant comfort. Therefore, indoor climate data is generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies is influenced by weather, occupant behavior and internal loads, and is generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPP43D..06A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPP43D..06A"><span>A robust null hypothesis for the potential causes of megadrought in western North America</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ault, T.; St George, S.; Smerdon, J. E.; Coats, S.; Mankin, J. S.; Cruz, C. C.; Cook, B.; Stevenson, S.</p> <p>2017-12-01</p> <p>The western United States was affected by several megadroughts during the last 1200 years, most prominently during the Medieval Climate Anomaly (MCA: 800 to 1300 CE). A null hypothesis is developed to test the possibility that, given a sufficiently long period of time, these events are inevitable and occur purely as a consequence of internal climate variability. The null distribution of this hypothesis is populated by a linear inverse model (LIM) constructed from global sea-surface temperature anomalies and self-calibrated Palmer Drought Severity Index data for North America. Despite being trained only on seasonal data from the late 20th century, the LIM produces megadroughts that are comparable in their duration, spatial scale, and magnitude as the most severe events of the last 12 centuries. The null hypothesis therefore cannot be rejected with much confidence when considering these features of megadrought, meaning that similar events are possible today, even without any changes to boundary conditions. In contrast, the observed clustering of megadroughts in the MCA, as well as the change in mean hydroclimate between the MCA and the 1500-2000 period, are more likely to have been caused by either external forcing or by internal climate variability not well sampled during the latter half of the Twentieth Century. Finally, the results demonstrate the LIM is a viable tool for determining whether paleoclimate reconstructions events should be ascribed to external forcings, "out of sample" climate mechanisms, or if they are consistent with the variability observed during the recent period.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMOS23D..01H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMOS23D..01H"><span>Multi-decadal trend and space-time variability of sea level over the Indian Ocean since the 1950s: impact of decadal climate modes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Han, W.; Stammer, D.; Meehl, G. A.; Hu, A.; Sienz, F.</p> <p>2016-12-01</p> <p>Sea level varies on decadal and multi-decadal timescales over the Indian Ocean. The variations are not spatially uniform, and can deviate considerably from the global mean sea level rise (SLR) due to various geophysical processes. One of these processes is the change of ocean circulation, which can be partly attributed to natural internal modes of climate variability. Over the Indian Ocean, the most influential climate modes on decadal and multi-decadal timescales are the Interdecadal Pacific Oscillation (IPO) and decadal variability of the Indian Ocean dipole (IOD). Here, we first analyze observational datasets to investigate the impacts of IPO and IOD on spatial patterns of decadal and interdecadal (hereafter decal) sea level variability & multi-decadal trend over the Indian Ocean since the 1950s, using a new statistical approach of Bayesian Dynamical Linear regression Model (DLM). The Bayesian DLM overcomes the limitation of "time-constant (static)" regression coefficients in conventional multiple linear regression model, by allowing the coefficients to vary with time and therefore measuring "time-evolving (dynamical)" relationship between climate modes and sea level. For the multi-decadal sea level trend since the 1950s, our results show that climate modes and non-climate modes (the part that cannot be explained by climate modes) have comparable contributions in magnitudes but with different spatial patterns, with each dominating different regions of the Indian Ocean. For decadal variability, climate modes are the major contributors for sea level variations over most region of the tropical Indian Ocean. The relative importance of IPO and decadal variability of IOD, however, varies spatially. For example, while IOD decadal variability dominates IPO in the eastern equatorial basin (85E-100E, 5S-5N), IPO dominates IOD in causing sea level variations in the tropical southwest Indian Ocean (45E-65E, 12S-2S). To help decipher the possible contribution of external forcing to the multi-decadal sea level trend and decadal variability, we also analyze the model outputs from NCAR's Community Earth System Model (CESM) Large Ensemble Experiments, and compare the results with our observational analyses.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.2998W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.2998W"><span>Disentangling the effects of climate variability and functional change on ecosystem carbon dynamics using semi-empirical modelling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, J.; van der Linden, L.; Lasslop, G.; Carvalhais, N.; Pilegaard, K.; Beier, C.; Ibrom, A.</p> <p>2012-04-01</p> <p>The ecosystem carbon balance is affected by both external climatic forcing (e.g. solar radiation, air temperature and humidity) and internal dynamics in the ecosystem functional properties (e.g. canopy structure, leaf photosynthetic capacity and carbohydrate reserve). In order to understand to what extent and at which temporal scale, climatic variability and functional changes regulated the interannual variation (IAV) in the net ecosystem exchange of CO2 (NEE), data-driven analysis and semi-empirical modelling (Lasslop et al. 2010) were performed based on a 13 year NEE record in a temperate deciduous forest (Pilegaard et al 2011, Wu et al. 2012). We found that the sensitivity of carbon fluxes to climatic variability was significantly higher at shorter than at longer time scales and changed seasonally. This implied that the changing distribution of climate anomalies during the vegetation period could have stronger impacts on future ecosystem carbon balances than changes in average climate. At the annual time scale, approximately 80% of the interannual variability in NEE was attributed to the variation in the model parameters, indicating the observed IAV in the carbon dynamics at the investigated site was dominated by changes in ecosystem functioning. In general this study showed the need for understanding the mechanisms of ecosystem functional change. The method can be applied at other sites to explore ecosystem behavior across different plant functional types and climate gradients. Incorporating ecosystem functional change into process based models will reduce the uncertainties in long-term predictions of ecosystem carbon balances in global climate change projections. Acknowledgements. This work was supported by the EU FP7 project CARBO-Extreme, the DTU Climate Centre and the Danish national project ECOCLIM (Danish Council for Strategic Research).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A21B0034B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A21B0034B"><span>Interactive influence of the Atlantic and Pacific climates and their contribution to the multidecadal variations of global temperature and precipitation.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barcikowska, M. J.; Knutson, T. R.; Zhang, R.</p> <p>2016-12-01</p> <p>This study investigates mechanisms and global-scale climate impacts of multidecadal climate variability. Here we show, using observations and CSIRO-Mk3.6.0 model control run, that multidecadal variability of the Atlantic Meridional Overturning Circulation (AMOC) may have a profound impact on the thermal- and hydro-climatic changes over the Pacific region. In our model-based analysis we propose a mechanism, which comprises a coupled ocean-atmosphere teleconnection, established through the atmospheric overturning circulation cell between the tropical North Atlantic and tropical Pacific. For example, warming SSTs over the tropical North Atlantic intensify local convection and reinforce subsidence, low-level divergence in the eastern tropical Pacific. This is also accompanied with an intensification of trade winds, cooling and drying anomalies in the tropical central-east Pacific. The derived multidecadal changes, associated with the AMOC, contribute remarkably to the global temperature and precipitation variations. This highlights its potential predictive value. Shown here results suggest a possibility that: 1) recently observed slowdown in global warming may partly originate from internal variability, 2) climate system may be undergoing a transition to a cold AMO phase which could prolong the global slowdown.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1914238D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1914238D"><span>Harmonising and semantically linking key variables from in-situ observing networks of an Integrated Atlantic Ocean Observing System, AtlantOS</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Darroch, Louise; Buck, Justin</p> <p>2017-04-01</p> <p>Atlantic Ocean observation is currently undertaken through loosely-coordinated, in-situ observing networks, satellite observations and data management arrangements at regional, national and international scales. The EU Horizon 2020 AtlantOS project aims to deliver an advanced framework for the development of an Integrated Atlantic Ocean Observing System that strengthens the Global Ocean Observing System (GOOS) and contributes to the aims of the Galway Statement on Atlantic Ocean Cooperation. One goal is to ensure that data from different and diverse in-situ observing networks are readily accessible and useable to a wider community, including the international ocean science community and other stakeholders in this field. To help achieve this goal, the British Oceanographic Data Centre (BODC) produced a parameter matrix to harmonise data exchange, data flow and data integration for the key variables acquired by multiple in-situ AtlantOS observing networks such as ARGO, Seafloor Mapping and OceanSITES. Our solution used semantic linking of controlled vocabularies and metadata for parameters that were "mappable" to existing EU and international standard vocabularies. An AtlantOS Essential Variables list of terms (aggregated level) based on Global Climate Observing System (GCOS) Essential Climate Variables (ECV), GOOS Essential Ocean Variables (EOV) and other key network variables was defined and published on the Natural Environment Research Council (NERC) Vocabulary Server (version 2.0) as collection A05 (http://vocab.nerc.ac.uk/collection/A05/current/). This new vocabulary was semantically linked to standardised metadata for observed properties and units that had been validated by the AtlantOS community: SeaDataNet parameters (P01), Climate and Forecast (CF) Standard Names (P07) and SeaDataNet units (P06). Observed properties were mapped to biological entities from the internationally assured AphiaID from the WOrld Register of Marine Species (WoRMS), http://www.marinespecies.org/aphia.php?p=webservice. The AtlantOS parameter matrix offers a way to harmonise the globally important variables (such as ECVs and EOVs) from in-situ observing networks that use different flavours of exchange formats based on SeaDataNet and CF parameter metadata. It also offers a way to standardise data in the wider Integrated Ocean Observing System. It uses sustainable and trusted standardised vocabularies that are governed by internationally renowned and long-standing organisations and is interoperable through the use of persistent resource identifiers, such as URNs and PURLs. It is the first step to integrating and serving data in a variety of international exchange formats using Application programming interfaces (API) improving both data discoverability and utility for users.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_7 --> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27640648','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27640648"><span>A multicenter study: how do medical students perceive clinical learning climate?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Yilmaz, Nilufer Demiral; Velipasaoglu, Serpil; Ozan, Sema; Basusta, Bilge Uzun; Midik, Ozlem; Mamakli, Sumer; Karaoglu, Nazan; Tengiz, Funda; Durak, Halil İbrahim; Sahin, Hatice</p> <p>2016-01-01</p> <p>The relationship between students and instructors is of crucial importance for the development of a positive learning climate. Learning climate is a multifaceted concept, and its measurement is a complicated process. The aim of this cross-sectional study was to determine medical students' perceptions about the clinical learning climate and to investigate differences in their perceptions in terms of various variables. Medical students studying at six medical schools in Turkey were recruited for the study. All students who completed clinical rotations, which lasted for 3 or more weeks, were included in the study (n=3,097). Data were collected using the Clinical Learning Climate Scale (CLCS). The CLCS (36 items) includes three subscales: clinical environment, emotion, and motivation. Each item is scored using a 5-point Likert scale (1: strongly disagree to 5: strongly agree). The response rate for the trainees was 69.67% (n=1,519), and for the interns it was 51.47% (n=917). The mean total CLCS score was 117.20±17.19. The rotation during which the clinical learning climate was perceived most favorably was the Physical Therapy and Rehabilitation rotation (mean score: 137.77). The most negatively perceived rotation was the General Internal Medicine rotation (mean score: 104.31). There were significant differences between mean total scores in terms of trainee/intern characteristics, internal medicine/surgical medicine rotations, and perception of success. The results of this study drew attention to certain aspects of the clinical learning climate in medical schools. Clinical teacher/instructor/supervisor, clinical training programs, students' interactions in clinical settings, self-realization, mood, students' intrinsic motivation, and institutional commitment are important components of the clinical learning climate. For this reason, the aforementioned components should be taken into consideration in studies aiming to improve clinical learning climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28165976','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28165976"><span>A multicenter study: how do medical students perceive clinical learning climate?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Yilmaz, Nilufer Demiral; Velipasaoglu, Serpil; Ozan, Sema; Basusta, Bilge Uzun; Midik, Ozlem; Mamakli, Sumer; Karaoglu, Nazan; Tengiz, Funda; Durak, Halil İbrahim; Sahin, Hatice</p> <p>2016-01-01</p> <p>Background The relationship between students and instructors is of crucial importance for the development of a positive learning climate. Learning climate is a multifaceted concept, and its measurement is a complicated process. The aim of this cross-sectional study was to determine medical students' perceptions about the clinical learning climate and to investigate differences in their perceptions in terms of various variables. Methods Medical students studying at six medical schools in Turkey were recruited for the study. All students who completed clinical rotations, which lasted for 3 or more weeks, were included in the study (n=3,097). Data were collected using the Clinical Learning Climate Scale (CLCS). The CLCS (36 items) includes three subscales: clinical environment, emotion, and motivation. Each item is scored using a 5-point Likert scale (1: strongly disagree to 5: strongly agree). Results The response rate for the trainees was 69.67% (n=1,519), and for the interns it was 51.47% (n=917). The mean total CLCS score was 117.20±17.19. The rotation during which the clinical learning climate was perceived most favorably was the Physical Therapy and Rehabilitation rotation (mean score: 137.77). The most negatively perceived rotation was the General Internal Medicine rotation (mean score: 104.31). There were significant differences between mean total scores in terms of trainee/intern characteristics, internal medicine/surgical medicine rotations, and perception of success. Conclusion The results of this study drew attention to certain aspects of the clinical learning climate in medical schools. Clinical teacher/instructor/supervisor, clinical training programs, students' interactions in clinical settings, self-realization, mood, students' intrinsic motivation, and institutional commitment are important components of the clinical learning climate. For this reason, the aforementioned components should be taken into consideration in studies aiming to improve clinical learning climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeoRL..43.9113J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeoRL..43.9113J"><span>How predictable is the timing of a summer ice-free Arctic?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jahn, Alexandra; Kay, Jennifer E.; Holland, Marika M.; Hall, David M.</p> <p>2016-09-01</p> <p>Climate model simulations give a large range of over 100 years for predictions of when the Arctic could first become ice free in the summer, and many studies have attempted to narrow this uncertainty range. However, given the chaotic nature of the climate system, what amount of spread in the prediction of an ice-free summer Arctic is inevitable? Based on results from large ensemble simulations with the Community Earth System Model, we show that internal variability alone leads to a prediction uncertainty of about two decades, while scenario uncertainty between the strong (Representative Concentration Pathway (RCP) 8.5) and medium (RCP4.5) forcing scenarios adds at least another 5 years. Common metrics of the past and present mean sea ice state (such as ice extent, volume, and thickness) as well as global mean temperatures do not allow a reduction of the prediction uncertainty from internal variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26601136','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26601136"><span>Old World megadroughts and pluvials during the Common Era.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cook, Edward R; Seager, Richard; Kushnir, Yochanan; Briffa, Keith R; Büntgen, Ulf; Frank, David; Krusic, Paul J; Tegel, Willy; van der Schrier, Gerard; Andreu-Hayles, Laia; Baillie, Mike; Baittinger, Claudia; Bleicher, Niels; Bonde, Niels; Brown, David; Carrer, Marco; Cooper, Richard; Čufar, Katarina; Dittmar, Christoph; Esper, Jan; Griggs, Carol; Gunnarson, Björn; Günther, Björn; Gutierrez, Emilia; Haneca, Kristof; Helama, Samuli; Herzig, Franz; Heussner, Karl-Uwe; Hofmann, Jutta; Janda, Pavel; Kontic, Raymond; Köse, Nesibe; Kyncl, Tomáš; Levanič, Tom; Linderholm, Hans; Manning, Sturt; Melvin, Thomas M; Miles, Daniel; Neuwirth, Burkhard; Nicolussi, Kurt; Nola, Paola; Panayotov, Momchil; Popa, Ionel; Rothe, Andreas; Seftigen, Kristina; Seim, Andrea; Svarva, Helene; Svoboda, Miroslav; Thun, Terje; Timonen, Mauri; Touchan, Ramzi; Trotsiuk, Volodymyr; Trouet, Valerie; Walder, Felix; Ważny, Tomasz; Wilson, Rob; Zang, Christian</p> <p>2015-11-01</p> <p>Climate model projections suggest widespread drying in the Mediterranean Basin and wetting in Fennoscandia in the coming decades largely as a consequence of greenhouse gas forcing of climate. To place these and other "Old World" climate projections into historical perspective based on more complete estimates of natural hydroclimatic variability, we have developed the "Old World Drought Atlas" (OWDA), a set of year-to-year maps of tree-ring reconstructed summer wetness and dryness over Europe and the Mediterranean Basin during the Common Era. The OWDA matches historical accounts of severe drought and wetness with a spatial completeness not previously available. In addition, megadroughts reconstructed over north-central Europe in the 11th and mid-15th centuries reinforce other evidence from North America and Asia that droughts were more severe, extensive, and prolonged over Northern Hemisphere land areas before the 20th century, with an inadequate understanding of their causes. The OWDA provides new data to determine the causes of Old World drought and wetness and attribute past climate variability to forced and/or internal variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4640589','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4640589"><span>Old World megadroughts and pluvials during the Common Era</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Cook, Edward R.; Seager, Richard; Kushnir, Yochanan; Briffa, Keith R.; Büntgen, Ulf; Frank, David; Krusic, Paul J.; Tegel, Willy; van der Schrier, Gerard; Andreu-Hayles, Laia; Baillie, Mike; Baittinger, Claudia; Bleicher, Niels; Bonde, Niels; Brown, David; Carrer, Marco; Cooper, Richard; Čufar, Katarina; Dittmar, Christoph; Esper, Jan; Griggs, Carol; Gunnarson, Björn; Günther, Björn; Gutierrez, Emilia; Haneca, Kristof; Helama, Samuli; Herzig, Franz; Heussner, Karl-Uwe; Hofmann, Jutta; Janda, Pavel; Kontic, Raymond; Köse, Nesibe; Kyncl, Tomáš; Levanič, Tom; Linderholm, Hans; Manning, Sturt; Melvin, Thomas M.; Miles, Daniel; Neuwirth, Burkhard; Nicolussi, Kurt; Nola, Paola; Panayotov, Momchil; Popa, Ionel; Rothe, Andreas; Seftigen, Kristina; Seim, Andrea; Svarva, Helene; Svoboda, Miroslav; Thun, Terje; Timonen, Mauri; Touchan, Ramzi; Trotsiuk, Volodymyr; Trouet, Valerie; Walder, Felix; Ważny, Tomasz; Wilson, Rob; Zang, Christian</p> <p>2015-01-01</p> <p>Climate model projections suggest widespread drying in the Mediterranean Basin and wetting in Fennoscandia in the coming decades largely as a consequence of greenhouse gas forcing of climate. To place these and other “Old World” climate projections into historical perspective based on more complete estimates of natural hydroclimatic variability, we have developed the “Old World Drought Atlas” (OWDA), a set of year-to-year maps of tree-ring reconstructed summer wetness and dryness over Europe and the Mediterranean Basin during the Common Era. The OWDA matches historical accounts of severe drought and wetness with a spatial completeness not previously available. In addition, megadroughts reconstructed over north-central Europe in the 11th and mid-15th centuries reinforce other evidence from North America and Asia that droughts were more severe, extensive, and prolonged over Northern Hemisphere land areas before the 20th century, with an inadequate understanding of their causes. The OWDA provides new data to determine the causes of Old World drought and wetness and attribute past climate variability to forced and/or internal variability. PMID:26601136</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1306152-sensitivity-summer-ensembles-fledgling-superparameterized-mesoscale-convective-systems-cloud-resolving-model-microphysics-grid-configuration','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1306152-sensitivity-summer-ensembles-fledgling-superparameterized-mesoscale-convective-systems-cloud-resolving-model-microphysics-grid-configuration"><span>Sensitivity of summer ensembles of fledgling superparameterized U.S. mesoscale convective systems to cloud resolving model microphysics and grid configuration</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Elliott, Elizabeth J.; Yu, Sungduk; Kooperman, Gabriel J.; ...</p> <p>2016-05-01</p> <p>The sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global-scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger-scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS-likemore » events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP-CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS-like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five-summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one-moment and two-moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP-GCMs. Furthermore, these results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSOD13A..03S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSOD13A..03S"><span>Producing a Climate-Quality Database of Global Upper Ocean Profile Temperatures - The IQuOD (International Quality-controlled Ocean Database) Project.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sprintall, J.; Cowley, R.; Palmer, M. D.; Domingues, C. M.; Suzuki, T.; Ishii, M.; Boyer, T.; Goni, G. J.; Gouretski, V. V.; Macdonald, A. M.; Thresher, A.; Good, S. A.; Diggs, S. C.</p> <p>2016-02-01</p> <p>Historical ocean temperature profile observations provide a critical element for a host of ocean and climate research activities. These include providing initial conditions for seasonal-to-decadal prediction systems, evaluating past variations in sea level and Earth's energy imbalance, ocean state estimation for studying variability and change, and climate model evaluation and development. The International Quality controlled Ocean Database (IQuOD) initiative represents a community effort to create the most globally complete temperature profile dataset, with (intelligent) metadata and assigned uncertainties. With an internationally coordinated effort organized by oceanographers, with data and ocean instrumentation expertise, and in close consultation with end users (e.g., climate modelers), the IQuOD initiative will assess and maximize the potential of an irreplaceable collection of ocean temperature observations (tens of millions of profiles collected at a cost of tens of billions of dollars, since 1772) to fulfil the demand for a climate-quality global database that can be used with greater confidence in a vast range of climate change related research and services of societal benefit. Progress towards version 1 of the IQuOD database, ongoing and future work will be presented. More information on IQuOD is available at www.iquod.org.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp...83F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp...83F"><span>Errors and uncertainties in regional climate simulations of rainfall variability over Tunisia: a multi-model and multi-member approach</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fathalli, Bilel; Pohl, Benjamin; Castel, Thierry; Safi, Mohamed Jomâa</p> <p>2018-02-01</p> <p>Temporal and spatial variability of rainfall over Tunisia (at 12 km spatial resolution) is analyzed in a multi-year (1992-2011) ten-member ensemble simulation performed using the WRF model, and a sample of regional climate hindcast simulations from Euro-CORDEX. RCM errors and skills are evaluated against a dense network of local rain gauges. Uncertainties arising, on the one hand, from the different model configurations and, on the other hand, from internal variability are furthermore quantified and ranked at different timescales using simple spread metrics. Overall, the WRF simulation shows good skill for simulating spatial patterns of rainfall amounts over Tunisia, marked by strong altitudinal and latitudinal gradients, as well as the rainfall interannual variability, in spite of systematic errors. Mean rainfall biases are wet in both DJF and JJA seasons for the WRF ensemble, while they are dry in winter and wet in summer for most of the used Euro-CORDEX models. The sign of mean annual rainfall biases over Tunisia can also change from one member of the WRF ensemble to another. Skills in regionalizing precipitation over Tunisia are season dependent, with better correlations and weaker biases in winter. Larger inter-member spreads are observed in summer, likely because of (1) an attenuated large-scale control on Mediterranean and Tunisian climate, and (2) a larger contribution of local convective rainfall to the seasonal amounts. Inter-model uncertainties are globally stronger than those attributed to model's internal variability. However, inter-member spreads can be of the same magnitude in summer, emphasizing the important stochastic nature of the summertime rainfall variability over Tunisia.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018CliPa..14..101N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018CliPa..14..101N"><span>Climate variability in the subarctic area for the last 2 millennia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nicolle, Marie; Debret, Maxime; Massei, Nicolas; Colin, Christophe; deVernal, Anne; Divine, Dmitry; Werner, Johannes P.; Hormes, Anne; Korhola, Atte; Linderholm, Hans W.</p> <p>2018-01-01</p> <p>To put recent climate change in perspective, it is necessary to extend the instrumental climate records with proxy data from paleoclimate archives. Arctic climate variability for the last 2 millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many types of proxy data archived in the Arctic 2k database v1.1.1. In the North Atlantic and Alaska, the major climatic trend is characterized by long-term cooling interrupted by recent warming that started at the beginning of the 19th century. This cooling is visible in the Siberian region at two sites, warming at the others. The cooling of the Little Ice Age (LIA) was identified from the individual series, but it is characterized by wide-range spatial and temporal expression of climate variability, in contrary to the Medieval Climate Anomaly. The LIA started at the earliest by around AD 1200 and ended at the latest in the middle of the 20th century. The widespread temporal coverage of the LIA did not show regional consistency or particular spatial distribution and did not show a relationship with archive or proxy type either. A focus on the last 2 centuries shows a recent warming characterized by a well-marked warming trend parallel with increasing greenhouse gas emissions. It also shows a multidecadal variability likely due to natural processes acting on the internal climate system on a regional scale. A ˜ 16-30-year cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation, whereas ˜ 20-30- and ˜ 50-90-year periodicities characterize the North Atlantic climate variability, likely in relation with the Atlantic Multidecadal Oscillation. These regional features are probably linked to the sea ice cover fluctuations through ice-temperature positive feedback.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70093572','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70093572"><span>Perception, experience, and indigenous knowledge of climate change and variability: the case of Accra, a sub-Saharan African city</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Codjoe, Samuel N.A.; Owusu, George; Burkett, Virginia</p> <p>2014-01-01</p> <p>Several recent international assessments have concluded that climate change has the potential to reverse the modest economic gains achieved in many developing countries over the past decade. The phenomenon of climate change threatens to worsen poverty or burden populations with additional hardships, especially in poor societies with weak infrastructure and economic well-being. The importance of the perceptions, experiences, and knowledge of indigenous peoples has gained prominence in discussions of climate change and adaptation in developing countries and among international development organizations. Efforts to evaluate the role of indigenous knowledge in adaptation planning, however, have largely focused on rural people and their agricultural livelihoods. This paper presents the results of a study that examines perceptions, experiences, and indigenous knowledge relating to climate change and variability in three communities of metropolitan Accra, which is the capital of Ghana. The study design is based on a three-part conceptual framework and interview process involving risk mapping, mental models, and individual stressor cognition. Most of the residents interviewed in the three communities of urban Accra attributed climate change to the combination of deforestation and the burning of firewood and rubbish. None of the residents associated climate change with fossil fuel emissions from developed countries. Numerous potential adaptation strategies were suggested by the residents, many of which have been used effectively during past drought and flood events. Results suggest that ethnic residential clustering as well as strong community bonds in metropolitan Accra have allowed various groups and long-settled communities to engage in the sharing and transmission of knowledge of weather patterns and trends. Understanding and building upon indigenous knowledge may enhance the design, acceptance, and implementation of climate change adaptation strategies in Accra and urban regions of other developing nations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp.2351D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp.2351D"><span>On unravelling mechanism of interplay between cloud and large scale circulation: a grey area in climate science</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>De, S.; Agarwal, N. K.; Hazra, Anupam; Chaudhari, Hemantkumar S.; Sahai, A. K.</p> <p>2018-04-01</p> <p>The interaction between cloud and large scale circulation is much less explored area in climate science. Unfolding the mechanism of coupling between these two parameters is imperative for improved simulation of Indian summer monsoon (ISM) and to reduce imprecision in climate sensitivity of global climate model. This work has made an effort to explore this mechanism with CFSv2 climate model experiments whose cloud has been modified by changing the critical relative humidity (CRH) profile of model during ISM. Study reveals that the variable CRH in CFSv2 has improved the nonlinear interactions between high and low frequency oscillations in wind field (revealed as internal dynamics of monsoon) and modulates realistically the spatial distribution of interactions over Indian landmass during the contrasting monsoon season compared to the existing CRH profile of CFSv2. The lower tropospheric wind error energy in the variable CRH simulation of CFSv2 appears to be minimum due to the reduced nonlinear convergence of error to the planetary scale range from long and synoptic scales (another facet of internal dynamics) compared to as observed from other CRH experiments in normal and deficient monsoons. Hence, the interplay between cloud and large scale circulation through CRH may be manifested as a change in internal dynamics of ISM revealed from scale interactive quasi-linear and nonlinear kinetic energy exchanges in frequency as well as in wavenumber domain during the monsoon period that eventually modify the internal variance of CFSv2 model. Conversely, the reduced wind bias and proper modulation of spatial distribution of scale interaction between the synoptic and low frequency oscillations improve the eastward and northward extent of water vapour flux over Indian landmass that in turn give feedback to the realistic simulation of cloud condensates attributing improved ISM rainfall in CFSv2.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011WRR....4712528N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011WRR....4712528N"><span>Landscape structure and climate influences on hydrologic response</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nippgen, Fabian; McGlynn, Brian L.; Marshall, Lucy A.; Emanuel, Ryan E.</p> <p>2011-12-01</p> <p>Climate variability and catchment structure (topography, geology, vegetation) have a significant influence on the timing and quantity of water discharged from mountainous catchments. How these factors combine to influence runoff dynamics is poorly understood. In this study we linked differences in hydrologic response across catchments and across years to metrics of landscape structure and climate using a simple transfer function rainfall-runoff modeling approach. A transfer function represents the internal catchment properties that convert a measured input (rainfall/snowmelt) into an output (streamflow). We examined modeled mean response time, defined as the average time that it takes for a water input to leave the catchment outlet from the moment it reaches the ground surface. We combined 12 years of precipitation and streamflow data from seven catchments in the Tenderfoot Creek Experimental Forest (Little Belt Mountains, southwestern Montana) with landscape analyses to quantify the first-order controls on mean response times. Differences between responses across the seven catchments were related to the spatial variability in catchment structure (e.g., slope, flowpath lengths, tree height). Annual variability was largely a function of maximum snow water equivalent. Catchment averaged runoff ratios exhibited strong correlations with mean response time while annually averaged runoff ratios were not related to climatic metrics. These results suggest that runoff ratios in snowmelt dominated systems are mainly controlled by topography and not by climatic variability. This approach provides a simple tool for assessing differences in hydrologic response across diverse watersheds and climate conditions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMPP53D..06P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMPP53D..06P"><span>Southern Ocean Deep-Convection as a Driver of Centennial-to-Millennial-Scale Climate Variability at Southern High Latitudes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pedro, J. B.; Martin, T.; Steig, E. J.; Jochum, M.; Park, W.; Rasmussen, S.</p> <p>2015-12-01</p> <p>Antarctic Isotope Maxima (AIM) are centennial-to-millennial scale warming events observed in Antarctic ice core records from the last glacial period and deglaciation. Mounting evidence links AIM events to parallel variations in atmospheric CO2, Southern Ocean (SO) sea surface temperatures and Antarctic Bottom Water production. According to the prevailing view, AIM events are forced from the North Atlantic by melt-water discharge from ice sheets suppressing the production of North Atlantic Deep Water and associated northward heat transport in the Atlantic. However observations and model studies increasingly suggest that melt-water fluxes have the wrong timing to be invoked as such a trigger. Here, drawing on results form the Kiel Climate Model, we present an alternative hypothesis in which AIM events are forced via internal oscillations in SO deep-convection. The quasi-periodic timescale of deep-convection events is set by heat (buoyancy) accumulation at SO intermediate depths and stochastic variability in sea ice conditions and freshening at the surface. Massive heat release from the SO convective zone drives Antarctic and large-scale southern hemisphere warming via a two-stage process involving changes in the location of Southern Ocean fronts, in the strength and intensity of the Westerlies and in meridional ocean and atmospheric heat flux anomalies. The potential for AIM events to be driven by internal Southern Ocean processes and the identification of time-lags internal to the southern high latitudes challenges conventional views on the North Atlantic as the pacemaker of millennial-scale climate variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFMPP22A..05C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFMPP22A..05C"><span>South American Climate Variability: Remote and Regional Forcing Processes of the Holocene and the LGM</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cook, K. H.</p> <p>2006-12-01</p> <p>An overview of concepts used in studying climate variability is provided as an introduction. Internally generated variability is the result of interactions within a system, while externally forced variability arises when some factor outside of the system causes a change. Distinguishing between the two requires a definition of the boundaries of "the system" considered. Climate variability is also classified according to space and time scales, for example, regional to global space scales and/or intraseasonal, seasonal, interannual, decadal, and millennial time scales. Any of these variability signatures may be internally generated or externally forced. A discussion of some of the climate forcing factors and physical processes thought to be relevant in determining climate variations of the past 20,000 years over South America is presented. An exhaustive treatment is not practical, and there are still many unknowns. Prominent in the literature are studies that discuss the influence of the ITCZ on South American precipitation. Other investigations focus on the South American monsoon dynamics. The physical processes that support these two precipitation systems are quite different, so the modes of variability that they exhibit also differ and it is important to clearly distinguish between them. The ITCZ is zonally elongated, formed by meridional convergence in the tropics. It is largely a structure of the atmosphere over the ocean, and persists throughout the year. Its position and strength vary with SST gradients and the vertical stability of the atmosphere. In contrast, a monsoon system is seasonal, and arises because of the different heat capacities of the land and ocean. It is influenced by land surface features such as vegetation and topography, and SSTs in the vicinity of the continent. Monsoon systems may also vary due to remote and/or large-scale forcing factors such as global sea surface temperature distributions and Hadley and Walker circulations. An example for the LGM climate of South America is presented to distinguish between the variations of ITCZ and monsoon dynamics. Another example presented concerns remote forcing of South American climate from an "intercontinental teleconnection" from Africa. GCM simulations show that summertime precipitation rates in Brazil's Nordeste region would be significantly greater in the absence of the African continent, and precipitation rates over the Amazon basin would be smaller. The generation of a Walker circulation by heating over southern Africa is the cause, and the effect is amplified by land surface feedbacks over South America. The teleconnection is sensitive to the distance between the two continents, to the strength and position of the heating over Africa, and the land surface characteristics over both South America and Africa. The east/west circulation influences the north/south position of the Atlantic ITCZ when asymmetry in surface conditions over Africa displaces the meridional convergence.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29345639','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29345639"><span>Emergent constraint on equilibrium climate sensitivity from global temperature variability.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cox, Peter M; Huntingford, Chris; Williamson, Mark S</p> <p>2018-01-17</p> <p>Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO 2 ) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO 2 . Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the 'likely' range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC 'likely' range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018Natur.553..319C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018Natur.553..319C"><span>Emergent constraint on equilibrium climate sensitivity from global temperature variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cox, Peter M.; Huntingford, Chris; Williamson, Mark S.</p> <p>2018-01-01</p> <p>Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO2) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO2. Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the ‘likely’ range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC ‘likely’ range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC21B0960C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC21B0960C"><span>Improving Decision-Making Activities for Meningitis and Malaria</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ceccato, P.; Trzaska, S.; Perez, C.; Kalashnikova, O. V.; del Corral, J.; Cousin, R.; Blumenthal, M. B.; Connor, S.; Thomson, M. C.</p> <p>2012-12-01</p> <p>Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use, and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular Meningitis and Malaria. In this paper we present the new and improved products that have been developed for monitoring dust, temperature, rainfall and vectorial capacity model for monitoring and forecasting risks of Meningitis and Malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC13D0809V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC13D0809V"><span>Evaluating the ClimEx Single Model large ensemble in comparison with EURO-CORDEX results of heatwave and drought indicators</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>von Trentini, F.; Schmid, F. J.; Braun, M.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.</p> <p>2017-12-01</p> <p>Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several indicators concerning heatwave frequency, duration and mean temperature a well as number and maximum length of dry periods (cons. days <1mm) are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMGC11E..06S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC11E..06S"><span>Food and water security scenarios for East Africa over next 20 years</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shukla, S.; Funk, C. C.; Verdin, J. P.; Peters-Lidard, C. D.</p> <p>2013-12-01</p> <p>Broad areas of East Africa face chronic water and agricultural insecurity. Over the last decade, the region has experienced frequent drought events leading to food security emergencies and even famine in Somalia in 2011. The impact of these drought events, associated with recent declines in rainfall during major growing seasons, has been particularly severe due to the high vulnerability of subsistence agricultural and pastoralist livelihoods, rapid population growth, and the limited availability of resources for agricultural development and climate change adaptation. The Famine Early Warning Systems Network (FEWS NET) is a United States Agency for International Development (USAID) funded activity that brings together international, regional and national partners to provide timely and rigorous early warning and food security information in Africa and other regions of the developing world. To assist USAID with planning agricultural development strategies over the next ten years in East Africa, FEWS NET is partnering with climate scientists and adaptation specialists at regional institutions to study and assess future changes in precipitation and temperature in light of global climate change, natural climate variability, and their related impacts on agricultural and water security in the region. The overarching objective of this study is to provide future scenarios of food and water security (as estimated by trends in soil moisture, evapotranspiration, and runoff) for East Africa. We do so by following two approaches: Constructed Analogs and the Composite Delta Method. In the first approach we downscaled climate projections (precipitation and temperature projections) of long-term Coupled Model Intercomparison Project Phase-5 (CMIP5) experiments over (a) historical (1850-2005) and (b) Representative Concentration Pathway (RCP) 8.5 (2006-2030) periods. Current climate is characterized by two ENSO modes, the intensity of the Pacific Decadal Oscillation, and the strength of the Indo-Pacific warming signal (IPWS). These modes are used in conjunction with CMIP5-estimates of IPWS to project 2030 climate conditions. In the second approach we use the much simpler Composite Delta Method to generate climate projections. Future climate projections are generated by simply altering the mean observed climate to match the mean climate of the climate model projections. Projections of precipitation and temperature from both approaches were then used to drive NASA's FEWS NET Land Data Assimilation System (FLDAS) to simulate the hydrologic variables most relevant to agriculture and water security: runoff, soil moisture and evapotranspiration. These outputs inform 2030 food and water security scenarios for East Africa. Finally we also investigate the impact of precipitation versus temperature changes on agriculture and water security in East Africa. We do so by keeping either one of those forcings constant while using the actual projections of the other variable to generate projections of hydrologic variables as described above.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1361674','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1361674"><span>Finding "Models" in Clouds</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Leung, Ruby</p> <p>2017-05-01</p> <p>Internationally recognized Climate Scientist Ruby Leung is a cloud gazer. But rather than looking for shapes, Ruby’s life’s calling is to develop regional atmospheric models to better predict and understand the effects of global climate change at scales relevant to humans and the environment. Ruby’s accomplishments include developing novel methods for modeling mountain clouds and precipitation in climate models, and improving understanding of hydroclimate variability and change. She also has led efforts to develop regional climate modeling capabilities in the Weather Research and Forecasting model that is widely adopted by scientists worldwide. Ruby is part of a team of PNNLmore » researchers studying the impacts of global warming.« less</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_8 --> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.9943H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.9943H"><span>A Scaling Model for the Anthropocene Climate Variability with Projections to 2100</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hébert, Raphael; Lovejoy, Shaun</p> <p>2017-04-01</p> <p>The determination of the climate sensitivity to radiative forcing is a fundamental climate science problem with important policy implications. We use a scaling model, with a limited set of parameters, which can directly calculate the forced globally-average surface air temperature response to anthropogenic and natural forcings. At timescales larger than an inner scale τ, which we determine as the ocean-atmosphere coupling scale at around 2 years, the global system responds, approximately, linearly, so that the variability may be decomposed into additive forced and internal components. The Ruelle response theory extends the classical linear response theory for small perturbations to systems far from equilibrium. Our model thus relates radiative forcings to a forced temperature response by convolution with a suitable Green's function, or climate response function. Motivated by scaling symmetries which allow for long range dependence, we assume a general scaling form, a scaling climate response function (SCRF) which is able to produce a wide range of responses: a power-law truncated at τ. This allows us to analytically calculate the climate sensitivity at different time scales, yielding a one-to-one relation from the transient climate response to the equilibrium climate sensitivity which are estimated, respectively, as 1.6+0.3-0.2K and 2.4+1.3-0.6K at the 90 % confidence level. The model parameters are estimated within a Bayesian framework, with a fractional Gaussian noise error model as the internal variability, from forcing series, instrumental surface temperature datasets and CMIP5 GCMs Representative Concentration Pathways (RCP) scenario runs. This observation based model is robust and projections for the coming century are made following the RCP scenario 2.6, 4.5 and 8.5, yielding in the year 2100, respectively : 1.5 +0.3)_{-0.2K, 2.3 ± 0.4 K and 4.0 ± 0.6 K at the 90 % confidence level. For comparison, the associated projections from a CMIP5 multi-model ensemble(MME) (32 models) are: 1.7 ± 0.8 K, 2.6 ± 0.8 K and 4.8 ± 1.3 K. Therefore, our projection uncertainty is less than half the structural uncertainty of this CMIP5 MME.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/90175','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/90175"><span>Detection of greenhouse-gas-induced climatic change. Progress report, July 1, 1994--July 31, 1995</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Jones, P.D.; Wigley, T.M.L.</p> <p>1995-07-21</p> <p>The objective of this research is to assembly and analyze instrumental climate data and to develop and apply climate models as a basis for detecting greenhouse-gas-induced climatic change, and validation of General Circulation Models. In addition to changes due to variations in anthropogenic forcing, including greenhouse gas and aerosol concentration changes, the global climate system exhibits a high degree of internally-generated and externally-forced natural variability. To detect the anthropogenic effect, its signal must be isolated from the ``noise`` of this natural climatic variability. A high quality, spatially extensive data base is required to define the noise and its spatial characteristics.more » To facilitate this, available land and marine data bases will be updated and expanded. The data will be analyzed to determine the potential effects on climate of greenhouse gas and aerosol concentration changes and other factors. Analyses will be guided by a variety of models, from simple energy balance climate models to coupled atmosphere ocean General Circulation Models. These analyses are oriented towards obtaining early evidence of anthropogenic climatic change that would lead either to confirmation, rejection or modification of model projections, and towards the statistical validation of General Circulation Model control runs and perturbation experiments.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A33E3234N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A33E3234N"><span>Should anthropogenic warming lead to more frequent cold air outbreaks over the northeastern U.S.?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nicholas, R.</p> <p>2014-12-01</p> <p>For the northeastern United States, Winter 2013-14 was the coldest winter since the late 1970s and perhaps the coldest on record relative to prevailing climatic conditions. Frequent snowstorms and cold air outbreaks led to considerable press coverage and heated scholarly debate over the possible role of anthropogenic climate change in modulating wintertime variability in the northern hemisphere polar jet. While mechanisms have been proposed, to date, the observational record offers no definitive evidence for such a relationship, nor does it conclusively exclude one. To further explore this question, we employ a large, initial conditions ensemble of the Community Earth System Model forced with historical and RCP8.5 emissions. The ensemble effectively samples internal variability in the climate system and is used to assess the potential for forced changes in polar jet variability and the frequency of cold air outbreaks over the northeastern U.S. with projected increases in global mean temperature during the 21st century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.4019Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.4019Z"><span>Response of ENSO amplitude to global warming in CESM large ensemble: uncertainty due to internal variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zheng, Xiao-Tong; Hui, Chang; Yeh, Sang-Wook</p> <p>2018-06-01</p> <p>El Niño-Southern Oscillation (ENSO) is the dominant mode of variability in the coupled ocean-atmospheric system. Future projections of ENSO change under global warming are highly uncertain among models. In this study, the effect of internal variability on ENSO amplitude change in future climate projections is investigated based on a 40-member ensemble from the Community Earth System Model Large Ensemble (CESM-LE) project. A large uncertainty is identified among ensemble members due to internal variability. The inter-member diversity is associated with a zonal dipole pattern of sea surface temperature (SST) change in the mean along the equator, which is similar to the second empirical orthogonal function (EOF) mode of tropical Pacific decadal variability (TPDV) in the unforced control simulation. The uncertainty in CESM-LE is comparable in magnitude to that among models of the Coupled Model Intercomparison Project phase 5 (CMIP5), suggesting the contribution of internal variability to the intermodel uncertainty in ENSO amplitude change. However, the causations between changes in ENSO amplitude and the mean state are distinct between CESM-LE and CMIP5 ensemble. The CESM-LE results indicate that a large ensemble of 15 members is needed to separate the relative contributions to ENSO amplitude change over the twenty-first century between forced response and internal variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPP51C1086N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPP51C1086N"><span>Internal Climatic Influences From Secular To Multi-decadal Scales: Comparison Of NAO Reconstructions.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nicolle, M.; Debret, M.; Massei, N.; de Vernal, A.</p> <p>2017-12-01</p> <p>In the Northern Hemisphere, the North Atlantic Oscillation (NAO) is the major dominant mode of variability in winter atmospheric circulation, with large impacts on temperature, precipitation and storm tracks in the North Atlantic sector. To understand the role of this internal climatic oscillations on the past climate variability, several proxy-based reconstructions of the NAO were published during the last decades. Two of them are available during the past 1,200 years: a first NAO reconstruction published by Trouet et al. (2009) and a second proposed by Ortega et al. (2015). The major discrepancy between the two reconstructions concerns the transition period between the Medieval Climate Anomaly (MCA) and the Little Ice Age. The first NAO reconstruction shows persistent positive phases during the MCA (AD 1000-1300) but this dominant trend is not highlighted in the reconstruction proposed by Ortega et al. (2015), asking the question of the influence of predictors used to reconstruct the NAO signal during the last millennia. In these study, we compare the two NAO reconstructions in order to determine the effect of bi-proxy or multi-proxy approach on the signal reconstructed. Using statistical and wavelet analysis methods, we conclude that the number of predictors used do not have impact on the signal reconstruct. The two reconstructions signals are characterized by similar variabilities expressed from multi-decadal to multi-secular scales. The major trend difference seems to be link to the type of the predictor and particularly the use of Greenland ice cores in the reconstruction proposed in 2015.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC52B..05L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC52B..05L"><span>Regionally dependent summer heat wave response to increased surface temperature in the US</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lopez, H.; Dong, S.; Kirtman, B. P.; Goni, G. J.; Lee, S. K.; Atlas, R. M.; West, R.</p> <p>2017-12-01</p> <p>Climate projections for the 21st Century suggest an increase in the occurrence of heat waves. However, the time it takes for the externally forced signal of climate change to emerge against the background of natural variability (i.e., Time of Emergence, ToE) particularly on the regional scale makes reliable future projection of heat waves challenging. Here, we combine observations and model simulations under present and future climate forcing to assess internal variability versus external forcing in modulating US heat waves. We characterized the most common heat wave patterns over the US by the use of clustering of extreme events by their spatial distribution. For each heat wave cluster, we assess changes in the probability density function (PDF) of summer temperature extremes by modeling the PDF as a stochastically generated skewed (SGS) distribution. The probability of necessary causation for each heat wave cluster was also quantified, allowing to make assessments of heat extreme attribution to anthropogenic climate change. The results suggest that internal variability will dominate heat wave occurrence over the Great Plains with ToE occurring in the 2050s (2070s) and of occurrence of ratio of warm-to-cold extremes of 1.7 (1.7) for the Northern (Southern) Plains. In contrast, external forcing will dominate over the Western (Great Lakes) region with ToE occurring as early as in the 2020s (2030s) and warm-to-cold extremes ratio of 6.4 (10.2), suggesting caution in attributing heat extremes to external forcing due to their regional dependence.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A44B..03H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A44B..03H"><span>The long view: Causes of climate change over the instrumental period</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hegerl, G. C.; Schurer, A. P.; Polson, D.; Iles, C. E.; Bronnimann, S.</p> <p>2016-12-01</p> <p>The period of instrumentally recorded data has seen remarkable changes in climate, with periods of rapid warming, and periods of stagnation or cooling. A recent analysis of the observed temperature change from the instrumental record confirms that most of the warming recorded since the middle of the 20rst century has been caused by human influences, but shows large uncertainty in separating greenhouse gas from aerosol response if accounting for model uncertainty. The contribution by natural forcing and internal variability to the recent warming is estimated to be small, but becomes more important when analysing climate change over earlier or shorter time periods. For example, the enigmatic early 20th century warming was a period of strong climate anomalies, including the US dustbowl drought and exceptional heat waves, and pronounced Arctic warming. Attribution results suggests that about half of the global warming 1901-1950 was forced by greenhouse gases increases, with an anomalously strong contribution by climate variability, and contributions by natural forcing. Long term variations in circulation are important for some regional climate anomalies. Precipitation is important for impacts of climate change and precipitation changes are uncertain in models. Analysis of the instrumental record suggests a human influence on mean and heavy precipitation, and supports climate model estimates of the spatial pattern of precipitation sensitivity to warming. Broadly, and particularly over ocean, wet regions are getting wetter and dry regions are getting drier. In conclusion, the historical record provides evidence for a strong response to external forcings, supports climate models, and raises questions about multi-decadal variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002EGSGA..27.5517S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002EGSGA..27.5517S"><span>Millennial-scale Climate Variations Recorded As Far Back As The Early Pliocene</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Steenbrink, J.; Hilgen, F. J.; Lourens, L. J.</p> <p></p> <p>Quaternary climate proxy records show compelling evidence for climate variability on time scales of a few thousand years. The causes for these millennial-scale or sub- Milankovitch cycles are yet poorly understood, not in the least due to the complex feedback mechanisms of large ice-sheets during the Quaternary. We present evidence of millennial-scale climate variability in Early Pliocene lacustrine sediments from the intramontane Ptolemais Basin in northwestern Greece. The sediments are well ex- posed in a series of open-pit lignite mines and exhibit a distinct m-scale sedimentary cyclicity of alternating lignites and lacustrine marl beds that result from precession- induced variations in climate. A higher-frequency cyclicity is particular prominent within the marl segment of individual cycles. A stratigraphic interval of~115 kyr, cov- ering five precession-induced sedimentary cycles, was studied in nine parallel sections from two quarries located several km apart. Colour reflectance records were used to quantify the within-cycle variability and to determine its lateral continuity. Much of the within-cycle variability could be correlated between the parallel sections, even in fine detail, which suggests that these changes reflect basin-wide variations in environ- mental conditions related to (regional) climate fluctuations. Interbedded volcanic ash beds demonstrate the synchronicity of these fluctuations and spectral analysis of the reflectance time series shows a significant concentration of variability at periods of ~11,~5.5 and~2 kyr. Their occurrence at times before the intensification of the North- ern Hemisphere glaciation suggests that they cannot solely have resulted from internal ice-sheet dynamics. Possible candidates include harmonics or combination tones of the main orbital cycles, variations in solar output or periodic motions of the Earth and moon.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1054032-testing-possible-influence-unknown-climate-forcings-upon-global-temperature-increases-from','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1054032-testing-possible-influence-unknown-climate-forcings-upon-global-temperature-increases-from"><span>Testing for the Possible Influence of Unknown Climate Forcings upon Global Temperature Increases from 1950-2000</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Anderson, Bruce T.; Knight, Jeff R.; Ringer, Mark A.</p> <p>2012-10-15</p> <p>Global-scale variations in the climate system over the last half of the twentieth century, including long-term increases in global-mean near-surface temperatures, are consistent with concurrent human-induced emissions of radiatively active gases and aerosols. However, such consistency does not preclude the possible influence of other forcing agents, including internal modes of climate variability or unaccounted for aerosol effects. To test whether other unknown forcing agents may have contributed to multidecadal increases in global-mean near-surface temperatures from 1950 to 2000, data pertaining to observed changes in global-scale sea surface temperatures and observed changes in radiatively active atmospheric constituents are incorporated into numericalmore » global climate models. Results indicate that the radiative forcing needed to produce the observed long-term trends in sea surface temperatures—and global-mean near-surface temperatures—is provided predominantly by known changes in greenhouse gases and aerosols. Further, results indicate that less than 10% of the long-term historical increase in global-mean near-surface temperatures over the last half of the twentieth century could have been the result of internal climate variability. In addition, they indicate that less than 25%of the total radiative forcing needed to produce the observed long-term trend in global-mean near-surface temperatures could have been provided by changes in net radiative forcing from unknown sources (either positive or negative). These results, which are derived from simple energy balance requirements, emphasize the important role humans have played in modifying the global climate over the last half of the twentieth century.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A33C2378F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A33C2378F"><span>Improving Constraints on Climate System Properties withAdditional Data and New Statistical and Sampling Methods</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Forest, C. E.; Libardoni, A. G.; Sokolov, A. P.; Monier, E.</p> <p>2017-12-01</p> <p>We use the updated MIT Earth System Model (MESM) to derive the joint probability distribution function for Equilibrium Climate sensitivity (S), an effective heat diffusivity (Kv), and the net aerosol forcing (Faer). Using a new 1800-member ensemble of MESM runs, we derive PDFs by comparing model outputs against historical observations of surface temperature and global mean ocean heat content. We focus on how changes in (i) the MESM model, (ii) recent surface temperature and ocean heat content observations, and (iii) estimates of internal climate variability will all contribute to uncertainties. We show that estimates of S increase and Faer is less negative. These shifts result partly from new model forcing inputs but also from including recent temperature records that lead to higher values of S and Kv. We show that the parameter distributions are sensitive to the internal variability in the climate system. When considering these factors, we derive our best estimate for the joint probability distribution for the climate system properties. We estimate the 90-percent confidence intervals for climate sensitivity as 2.7-5.4 oC with a mode of 3.5 oC, for Kv as 1.9-23.0 cm2 s-1 with a mode of 4.41 cm2 s-1, and for Faer as -0.4 - -0.04 Wm-2 with a mode of -0.25 Wm-2. Lastly, we estimate TCR to be between 1.4 and 2.1 oC with a mode of 1.8 oC.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990009996','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990009996"><span>Potential Predictability of the Monsoon Subclimate Systems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yang, Song; Lau, K.-M.; Chang, Y.; Schubert, S.</p> <p>1999-01-01</p> <p>While El Nino/Southern Oscillation (ENSO) phenomenon can be predicted with some success using coupled oceanic-atmospheric models, the skill of predicting the tropical monsoons is low regardless of the methods applied. The low skill of monsoon prediction may be either because the monsoons are not defined appropriately or because they are not influenced significantly by boundary forcing. The latter characterizes the importance of internal dynamics in monsoon variability and leads to many eminent chaotic features of the monsoons. In this study, we analyze results from nine AMIP-type ensemble experiments with the NASA/GEOS-2 general circulation model to assess the potential predictability of the tropical climate system. We will focus on the variability and predictability of tropical monsoon rainfall on seasonal-to-interannual time scales. It is known that the tropical climate is more predictable than its extratropical counterpart. However, predictability is different from one climate subsystem to another within the tropics. It is important to understand the differences among these subsystems in order to increase our skill of seasonal-to-interannual prediction. We assess potential predictability by comparing the magnitude of internal and forced variances as defined by Harzallah and Sadourny (1995). The internal variance measures the spread among the various ensemble members. The forced part of rainfall variance is determined by the magnitude of the ensemble mean rainfall anomaly and by the degree of consistency of the results from the various experiments.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy...49..279D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy...49..279D"><span>The uncertainties and causes of the recent changes in global evapotranspiration from 1982 to 2010</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dong, Bo; Dai, Aiguo</p> <p>2017-07-01</p> <p>Recent studies have shown considerable changes in terrestrial evapotranspiration (ET) since the early 1980s, but the causes of these changes remain unclear. In this study, the relative contributions of external climate forcing and internal climate variability to the recent ET changes are examined. Three datasets of global terrestrial ET and the CMIP5 multi-model ensemble mean ET are analyzed, respectively, to quantify the apparent and externally-forced ET changes, while the unforced ET variations are estimated as the apparent ET minus the forced component. Large discrepancies of the ET estimates, in terms of their trend, variability, and temperature- and precipitation-dependence, are found among the three datasets. Results show that the forced global-mean ET exhibits an upward trend of 0.08 mm day-1 century-1 from 1982 to 2010. The forced ET also contains considerable multi-year to decadal variations during the latter half of the 20th century that are caused by volcanic aerosols. The spatial patterns and interannual variations of the forced ET are more closely linked to precipitation than temperature. After removing the forced component, the global-mean ET shows a trend ranging from -0.07 to 0.06 mm day-1 century-1 during 1982-2010 with varying spatial patterns among the three datasets. Furthermore, linkages between the unforced ET and internal climate modes are examined. Variations in Pacific sea surface temperatures (SSTs) are found to be consistently correlated with ET over many land areas among the ET datasets. The results suggest that there are large uncertainties in our current estimates of global terrestrial ET for the recent decades, and the greenhouse gas (GHG) and aerosol external forcings account for a large part of the apparent trend in global-mean terrestrial ET since 1982, but Pacific SST and other internal climate variability dominate recent ET variations and changes over most regions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EaFut...5..337D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EaFut...5..337D"><span>Climate model uncertainty in impact assessments for agriculture: A multi-ensemble case study on maize in sub-Saharan Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dale, Amy; Fant, Charles; Strzepek, Kenneth; Lickley, Megan; Solomon, Susan</p> <p>2017-03-01</p> <p>We present maize production in sub-Saharan Africa as a case study in the exploration of how uncertainties in global climate change, as reflected in projections from a range of climate model ensembles, influence climate impact assessments for agriculture. The crop model AquaCrop-OS (Food and Agriculture Organization of the United Nations) was modified to run on a 2° × 2° grid and coupled to 122 climate model projections from multi-model ensembles for three emission scenarios (Coupled Model Intercomparison Project Phase 3 [CMIP3] SRES A1B and CMIP5 Representative Concentration Pathway [RCP] scenarios 4.5 and 8.5) as well as two "within-model" ensembles (NCAR CCSM3 and ECHAM5/MPI-OM) designed to capture internal variability (i.e., uncertainty due to chaos in the climate system). In spite of high uncertainty, most notably in the high-producing semi-arid zones, we observed robust regional and sub-regional trends across all ensembles. In agreement with previous work, we project widespread yield losses in the Sahel region and Southern Africa, resilience in Central Africa, and sub-regional increases in East Africa and at the southern tip of the continent. Spatial patterns of yield losses corresponded with spatial patterns of aridity increases, which were explicitly evaluated. Internal variability was a major source of uncertainty in both within-model and between-model ensembles and explained the majority of the spatial distribution of uncertainty in yield projections. Projected climate change impacts on maize production in different regions and nations ranged from near-zero or positive (upper quartile estimates) to substantially negative (lower quartile estimates), highlighting a need for risk management strategies that are adaptive and robust to uncertainty.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5504352','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5504352"><span>Greening of the Sahara suppressed ENSO activity during the mid-Holocene</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Pausata, Francesco S. R.; Zhang, Qiong; Muschitiello, Francesco; Lu, Zhengyao; Chafik, Léon; Niedermeyer, Eva M.; Stager, J. Curt; Cobb, Kim M.; Liu, Zhengyu</p> <p>2017-01-01</p> <p>The evolution of the El Niño-Southern Oscillation (ENSO) during the Holocene remains uncertain. In particular, a host of new paleoclimate records suggest that ENSO internal variability or other external forcings may have dwarfed the fairly modest ENSO response to precessional insolation changes simulated in climate models. Here, using fully coupled ocean-atmosphere model simulations, we show that accounting for a vegetated and less dusty Sahara during the mid-Holocene relative to preindustrial climate can reduce ENSO variability by 25%, more than twice the decrease obtained using orbital forcing alone. We identify changes in tropical Atlantic mean state and variability caused by the momentous strengthening of the West Africa Monsoon (WAM) as critical factors in amplifying ENSO’s response to insolation forcing through changes in the Walker circulation. Our results thus suggest that potential changes in the WAM due to anthropogenic warming may influence ENSO variability in the future as well. PMID:28685758</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28685758','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28685758"><span>Greening of the Sahara suppressed ENSO activity during the mid-Holocene.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Pausata, Francesco S R; Zhang, Qiong; Muschitiello, Francesco; Lu, Zhengyao; Chafik, Léon; Niedermeyer, Eva M; Stager, J Curt; Cobb, Kim M; Liu, Zhengyu</p> <p>2017-07-07</p> <p>The evolution of the El Niño-Southern Oscillation (ENSO) during the Holocene remains uncertain. In particular, a host of new paleoclimate records suggest that ENSO internal variability or other external forcings may have dwarfed the fairly modest ENSO response to precessional insolation changes simulated in climate models. Here, using fully coupled ocean-atmosphere model simulations, we show that accounting for a vegetated and less dusty Sahara during the mid-Holocene relative to preindustrial climate can reduce ENSO variability by 25%, more than twice the decrease obtained using orbital forcing alone. We identify changes in tropical Atlantic mean state and variability caused by the momentous strengthening of the West Africa Monsoon (WAM) as critical factors in amplifying ENSO's response to insolation forcing through changes in the Walker circulation. Our results thus suggest that potential changes in the WAM due to anthropogenic warming may influence ENSO variability in the future as well.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1915479S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1915479S"><span>Long-term (in)stability of the climate-streamflow relationship</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Saft, Margarita; Peel, Murray; Coxon, Gemma; Freer, Jim; Parajka, Juraj; Woods, Ross</p> <p>2017-04-01</p> <p>Land use changes have long been known to alter streamflow production for a given climatic input. Recently, extended shifts in climate were also shown to be capable of altering catchment internal functioning and streamflow production for a given climatic input. This study investigates the stability of climate-streamflow relationships in natural catchments in different regions of the world for the first time, using datasets of natural/reference catchments from Europe, US, and Australia. Changes in climate-streamflow relationships are investigated statistically on the interannual to interdecadal timescale and related to interdecadal climate variability. We compare the frequency and magnitude of shifts in climate-streamflow relationship between different regions, and discuss what any differences in shift frequency and magnitude might be related to. This study draws attention to the issues of catchment vulnerability to changes in external factors, catchment-climate co-evolution, and long-term catchment memory.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUFMPA23A1443H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUFMPA23A1443H"><span>Community-based carbon sequestration in East Africa: Linking science and sustainability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hultman, N. E.</p> <p>2004-12-01</p> <p>International agreements on climate change have set the stage for an expanding market for greenhouse gas emissions reduction credits. Projects that can generate credits for trading are diverse, but one of the more controversial types involve biological carbon sequestration. For several reasons, most of the activity on these "sinks" projects has been in Latin America and Southeast Asia. Yet people in sub-saharan Africa could benefit from properly implemented projects. This poster will discuss estimates of the potential and risks of such projects in East Africa, and will describe in detail a case study located in central Tanzania and now part of the World Bank's BioCarbon Fund portfolio. Understanding climate variability and risk can effectively link international agreements on climate change, local realities of individual projects, and the characteristics of targeted ecosystems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1411037-internal-variability-dynamically-downscaled-climate-over-north-america','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1411037-internal-variability-dynamically-downscaled-climate-over-north-america"><span>Internal variability of a dynamically downscaled climate over North America</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Wang, Jiali; Bessac, Julie; Kotamarthi, Rao</p> <p></p> <p>This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 km and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemblemore » during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late 21st century. However, the IV is larger than the projected changes in precipitation for the mid- and late 21st century.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1429906-internal-variability-dynamically-downscaled-climate-over-north-america','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1429906-internal-variability-dynamically-downscaled-climate-over-north-america"><span>Internal variability of a dynamically downscaled climate over North America</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Wang, Jiali; Bessac, Julie; Kotamarthi, Rao</p> <p></p> <p>This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble duringmore » the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.4539W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.4539W"><span>Internal variability of a dynamically downscaled climate over North America</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth</p> <p>2018-06-01</p> <p>This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_9 --> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy..tmp..673W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy..tmp..673W"><span>Internal variability of a dynamically downscaled climate over North America</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth</p> <p>2017-09-01</p> <p>This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27435236','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27435236"><span>Contributions of natural and anthropogenic radiative forcing to mass loss of Northern Hemisphere mountain glaciers and quantifying their uncertainties.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hirabayashi, Yukiko; Nakano, Kazunari; Zhang, Yong; Watanabe, Satoshi; Tanoue, Masahiro; Kanae, Shinjiro</p> <p>2016-07-20</p> <p>Observational evidence indicates that a number of glaciers have lost mass in the past. Given that glaciers are highly impacted by the surrounding climate, human-influenced global warming may be partly responsible for mass loss. However, previous research studies have been limited to analyzing the past several decades, and it remains unclear whether past glacier mass losses are within the range of natural internal climate variability. Here, we apply an optimal fingerprinting technique to observed and reconstructed mass losses as well as multi-model general circulation model (GCM) simulations of mountain glacier mass to detect and attribute past glacier mass changes. An 8,800-year control simulation of glaciers enabled us to evaluate detectability. The results indicate that human-induced increases in greenhouse gases have contributed to the decreased area-weighted average masses of 85 analyzed glaciers. The effect was larger than the mass increase caused by natural forcing, although the contributions of natural and anthropogenic forcing to decreases in mass varied at the local scale. We also showed that the detection of anthropogenic or natural influences could not be fully attributed when natural internal climate variability was taken into account.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NatSR...629723H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NatSR...629723H"><span>Contributions of natural and anthropogenic radiative forcing to mass loss of Northern Hemisphere mountain glaciers and quantifying their uncertainties</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hirabayashi, Yukiko; Nakano, Kazunari; Zhang, Yong; Watanabe, Satoshi; Tanoue, Masahiro; Kanae, Shinjiro</p> <p>2016-07-01</p> <p>Observational evidence indicates that a number of glaciers have lost mass in the past. Given that glaciers are highly impacted by the surrounding climate, human-influenced global warming may be partly responsible for mass loss. However, previous research studies have been limited to analyzing the past several decades, and it remains unclear whether past glacier mass losses are within the range of natural internal climate variability. Here, we apply an optimal fingerprinting technique to observed and reconstructed mass losses as well as multi-model general circulation model (GCM) simulations of mountain glacier mass to detect and attribute past glacier mass changes. An 8,800-year control simulation of glaciers enabled us to evaluate detectability. The results indicate that human-induced increases in greenhouse gases have contributed to the decreased area-weighted average masses of 85 analyzed glaciers. The effect was larger than the mass increase caused by natural forcing, although the contributions of natural and anthropogenic forcing to decreases in mass varied at the local scale. We also showed that the detection of anthropogenic or natural influences could not be fully attributed when natural internal climate variability was taken into account.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMNH33A1914B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMNH33A1914B"><span>Can Protection Motivation Theory explain farmers'adaptation to Climate change/variability decision making in the Gambia?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bagagnan, A. R.</p> <p>2016-12-01</p> <p>In the Gambia, Changes in the climate pattern has affected and continue to affect the agriculture sector and therefore calling for effective adaptation policies. The present study aimed to explain farmers' adoption of climate change adaptation measure through the protection motivation theory in The Central River Region of The Gambia. Primary data were collected in all the eight communities of the study area. A transect walk was conducted first followed by a survey with 283 informants. The perception variables were referring to the past 20 years while the stated implementation was addressing the current adaptation practices. Results showed that on one hand, most of the perception variables such as severity, ability to withstand, and internal barriers are significantly correlated to protection motivation and on the other hand Protection motivation and stated implementation for water conservation technique are strongly correlated. Structural Equation Modeling confirms the mediation role of Protection motivation between Farmers stated implementation and their perception of climate variability. Decrease in soil water storage capacity, degradation of the quality of soil surface structure, decrease of the length of the growing season are factors that motivate farmers to implement an adaptation measure. Cost of the implementation and farmers' vulnerability are factors that prevent farmers to implement an adaptation measure. The cost of the implementation is the main barrier to farmers `protection motivation. Therefore the study suggested that farmers' awareness about climate change/variability should be increased through farmers' field school and awareness campaigns, farmers' resilience should be improved and adaptation measures should be made accessible to farmers through loans facilities and subsidizes application.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1912919A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1912919A"><span>To what extent can global warming events influence scaling properties of climatic fluctuations in glacial periods?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alberti, Tommaso; Lepreti, Fabio; Vecchio, Antonio; Carbone, Vincenzo</p> <p>2017-04-01</p> <p>The Earth's climate is an extremely unstable complex system consisting of nonlinear and still rather unknown interactions among atmosphere, land surface, ice and oceans. The system is mainly driven by solar irradiance, even if internal components as volcanic eruptions and human activities affect the atmospheric composition thus acting as a driver for climate changes. Since the extreme climate variability is the result of a set of phenomena operating from daily to multi-millennial timescales, with different correlation times, a study of the scaling properties of the system can evidence non-trivial persistent structures, internal or external physical processes. Recently, the scaling properties of the paleoclimate changes have been analyzed by distinguish between interglacial and glacial climates [Shao and Ditlevsen, 2016]. The results show that the last glacial record (20-120 kyr BP) presents some elements of multifractality, while the last interglacial period (0-10 kyr BP), say the Holocene period, seems to be characterized by a mono-fractal structure. This is associated to the absence of Dansgaard-Oeschger (DO) events in the interglacial climate that could be the cause for the absence of multifractality. This hypothesis is supported by the analysis of the period between 18 and 27 kyr BP, i.e. during the Last Glacial Period, in which a single DO event have been registred. Through the Empirical Mode Decomposition (EMD) we were able to detect a timescale separation within the Last Glacial Period (20-120 kyr BP) in two main components: a high-frequency component, related to the occurrence of DO events, and a low-frequency one, associated to the cooling/warming phase switch [Alberti et al., 2014]. Here, we investigate the scaling properties of the climate fluctuations within the Last Glacial Period, where abrupt climate changes, characterized by fast increase of temperature usually called Dansgaard-Oeschger (DO) events, have been particularly pronounced. By using the MultiFractal Detrended Fluctuation Analysis (MF-DFA), we show that a multifractal structure exists for both high- and low-frequency fluctuations in Northern and Southern hemispheres, with different scaling exponents, thus indicating a long-range persistence of the climatic variability within the whole Last Glacial Period. Our results evidence that both DO events and cooling/warming cycles must be considered as processes of the internal component of the Earth's climate, rather than processes related to external forcings. This study should be helpful for investigation of the internal origin of climate changes. References Shao, Z.G. and Ditlevsen, P.D., Nature Commun., 7, 10951, (2016). Alberti, T., Lepreti, F., Vecchio, A., Bevacqua, E., Capparelli, V. and Carbone, V., Clim. Past, 10, 1751 (2014).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H23M..06T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H23M..06T"><span>Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Taner, M. U.; Wi, S.; Brown, C.</p> <p>2017-12-01</p> <p>The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.U23A..04F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.U23A..04F"><span>Agroclimate.Org: Tools and Information for a Climate Resilient Agriculture in the Southeast USA</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fraisse, C.</p> <p>2014-12-01</p> <p>AgroClimate (http://agroclimate.org) is a web-based system developed to help the agricultural industry in the southeastern USA reduce risks associated with climate variability and change. It includes climate related information and dynamic application tools that interact with a climate and crop database system. Information available includes climate monitoring and forecasts combined with information about crop management practices that help increase the resiliency of the agricultural industry in the region. Recently we have included smartphone apps in the AgroClimate suite of tools, including irrigation management and crop disease alert systems. Decision support tools available in AgroClimate include: (a) Climate risk: expected (probabilistic) and historical climate information and freeze risk; (b) Crop yield risk: expected yield based on soil type, planting date, and basic management practices for selected commodities and historical county yield databases; (c) Crop diseases: disease risk monitoring and forecasting for strawberry and citrus; (d) Crop development: monitoring and forecasting of growing degree-days and chill accumulation; (e) Drought: monitoring and forecasting of selected drought indices, (f) Footprints: Carbon and water footprint calculators. The system also provides background information about the main drivers of climate variability and basic information about climate change in the Southeast USA. AgroClimate has been widely used as an educational tool by the Cooperative Extension Services in the region and also by producers. It is now being replicated internationally with version implemented in Mozambique and Paraguay.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMNH51A1853M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMNH51A1853M"><span>Review of Malaria Epidemics in Ethiopia using Enhanced Climate Services (ENACTS)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Muhammad, A.</p> <p>2015-12-01</p> <p>Malaria is a disease directly linked to temperature and rainfall. In Ethiopia, the influence of climate variables on malaria transmission and the subsequent role of ENSO in the rise of malaria incidence are becoming more recognized. Numerous publications attest to the extreme sensitivity of malaria to climate in Ethiopia. The majority of large-scale epidemics in the past were associated with climatic factors such as temperature and rainfall. However, there is limited information on climate variability and ENSO at the district level to aid in public health decision-making. Since 2008, the National Meteorogy Agency (NMA) and the International Research Institute for Climate and Society (IRI) have been collaborating on improving climate services in Ethiopia. This collaboration spurred the implementation of the Enhancing National Climate Services (ENACTS) initiative and the creation of the IRI Data Library (DL) NMA Ethiopia Maproom. ENACTS provides reliable and readily accessible climate data at high resolutions and the Maproom uses ENACTS to build a collection of maps and other figures that monitor climate and societal conditions at present and in the recent past (1981-2010). A recent analysis exploring the relationship of rainfall and temperature ENACTS products to malaria epidemics in proceeding rainy seasons within 12 woredas found above normal temperature anomalies to be more readily associated with epidemics when compared to above normal rainfall anomalies, regardless of the ENSO phase (Figure 1-2).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ArtSa..51..107W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ArtSa..51..107W"><span>Hydrological Excitations of Polar Motion Derived from Different Variables of Fgoals - g2 Climate Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Winska, M.</p> <p>2016-12-01</p> <p>The hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from climate model as well as from GRACE (Gravity Recovery and Climate Experiment) data is discussed here for the period 2002.3-2016.0. The data set used here are Earth Orientation Parameters Combined 04 (EOP C04), Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOAL-g2) and Global Land Data Assimilation System (GLDAS) climate models and GRACE CSR RL05 data for polar motion, hydrological and gravimetric excitation, respectively. Several Hydrological Angular Momentum (HAM) functions are calculated here from the selected variables: precipitation, evaporation, runoff, soil moisture, accumulated snow of the FGOALS and GLDAS climate models as well as from the global mass change fields from GRACE data provided by the International Earth Rotation and Reference System Service (IERS) Global Geophysical Fluids Center (GGFC). The contribution of different HAM excitation functions to achieve the full agreement between geodetic observations and geophysical excitation functions of polar motion is studied here.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017CliPa..13.1901A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017CliPa..13.1901A"><span>The climate of the Common Era off the Iberian Peninsula</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Abrantes, Fátima; Rodrigues, Teresa; Rufino, Marta; Salgueiro, Emília; Oliveira, Dulce; Gomes, Sandra; Oliveira, Paulo; Costa, Ana; Mil-Homens, Mário; Drago, Teresa; Naughton, Filipa</p> <p>2017-12-01</p> <p>The Mediterranean region is a climate hot spot, sensitive not only to global warming but also to water availability. In this work we document major temperature and precipitation changes in the Iberian Peninsula and margin during the last 2000 years and propose an interplay of the North Atlantic internal variability with the three atmospheric circulation modes (ACMs), (North Atlantic Oscillation (NAO), east atlantic (EA) and Scandinavia (SCAND)) to explain the detected climate variability. We present reconstructions of sea surface temperature (SST derived from alkenones) and on-land precipitation (estimated from higher plant n-alkanes and pollen data) in sedimentary sequences recovered along the Iberian Margin between the south of Portugal (Algarve) and the northwest of Spain (Galiza) (36 to 42° N). A clear long-term cooling trend, from 0 CE to the beginning of the 20th century, emerges in all SST records and is considered to be a reflection of the decrease in the Northern Hemisphere summer insolation that began after the Holocene optimum. Multi-decadal/centennial SST variability follows other records from Spain, Europe and the Northern Hemisphere. Warm SSTs throughout the first 1300 years encompass the Roman period (RP), the Dark Ages (DA) and the Medieval Climate Anomaly (MCA). A cooling initiated at 1300 CE leads to 4 centuries of colder SSTs contemporary with the Little Ice Age (LIA), while a climate warming at 1800 CE marks the beginning of the modern/Industrial Era. Novel results include two distinct phases in the MCA: an early period (900-1100 years) characterized by intense precipitation/flooding and warm winters but a cooler spring-fall season attributed to the interplay of internal oceanic variability with a positive phase in the three modes of atmospheric circulation (NAO, EA and SCAND). The late MCA is marked by cooler and relatively drier winters and a warmer spring-fall season consistent with a shift to a negative mode of the SCAND. The Industrial Era reveals a clear difference between the NW Iberia and the Algarve records. While off NW Iberia variability is low, the Algarve shows large-amplitude decadal variability with an inverse relationship between SST and river input. Such conditions suggest a shift in the EA mode, from negative between 1900 and 1970 CE to positive after 1970, while NAO and SCAND remain in a positive phase. The particularly noticeable rise in SST at the Algarve site by the mid-20th century (±1970), provides evidence for a regional response to the ongoing climate warming. The reported findings have implications for decadal-scale predictions of future climate change in the Iberian Peninsula.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1914999M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1914999M"><span>Temporal variability of gravity wave drag - vertical coupling and possible climate links</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Miksovsky, Jiri; Sacha, Petr; Kuchar, Ales; Pisoft, Petr</p> <p>2017-04-01</p> <p>In the atmosphere, the internal gravity waves (IGW) are one of the fastest ways of natural information transfer in the vertical direction. Tropospheric changes that result in modification of sourcing, propagation or breaking conditions for IGWs almost immediately influence the distribution of gravity wave drag in the stratosphere. So far most of the related studies deal with IGW impacts higher in the upper stratospheric/mesospheric region and with the modulation of IGWs by planetary waves. This is most likely due to the fact that IGWs induce highest accelerations in the mesosphere and lower thermosphere region. However, the imposed drag force is much bigger in the stratosphere. In the presented analysis, we have assessed the relationship between the gravity wave activity in the stratosphere and other climatic phenomena through statistical techniques. Multivariable regression has been applied to investigate the IGW-related eastward and northward wind tendencies in the CMAM30-SD data, subject to the explanatory variables involving local circulation characteristics (derived from regional configuration of the thermobaric field) as well as the phases of the large-scale internal climate variability modes (ENSO, NAO, QBO). Our tests have highlighted several geographical areas with statistically significant responses of the orographic gravity waves effect to each of the variability modes under investigation; additional experiments have also indicated distinct signs of nonlinearity in some of the links uncovered. Furthermore, we have also applied composite analysis of displaced and split stratospheric polar vortex events (SPV) from CMAM30-SD to focus on how the strength and occurrence of the IGW hotspots can play a role in SPV occurrence and frequency.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H11P..04B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H11P..04B"><span>The role of internal variability in prolonging the California drought</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Buenning, N. H.; Stott, L. D.</p> <p>2015-12-01</p> <p>The current drought in California has been one of the driest on record. Using atmospheric general circulation models (AGCMs), recent studies have demonstrated that the low precipitation anomalies observed during the first three winters of the current drought are mostly attributable to changes in sea surface temperature (SST) and sea ice forcing. Here we show through AGCM simulations that the fourth and latest winter of the current drought is not attributable to SST and sea ice forcing, but instead a consequence of higher internal variability. Using the Global Spectral Model (GSM) we demonstrate how the surface forcing reproduces dry conditions over California for the first three winters of the current drought, similar to what other models produced. However, when forced with the SST and sea ice conditions for the winter of 2014-2015, GSM robustly simulates high precipitation conditions over California. This significantly differs with observed precipitation anomalies, which suggests a model deficiency or large influence of internal variability within the climate system during the winter of 2014-2015. Ensemble simulations with 234 realizations reveal that the surface forcing created a broader range of precipitation possibilities over California. Thus, the surface forcing caused a greater degree of internal variations, which was driven by a reduced latitudinal temperature gradient and amplified planetary waves over the Pacific. Similar amplified waves are also seen in 21st century climate projections of upper-level geopotential heights, suggesting that 21st century precipitation over California will become more variable and increasingly difficult to predict on seasonal timescales. When an El Nino pattern is applied to the surface forcing the precipitation further increases and the variance amongst model realizations is reduced, which indicates a strong likelihood of an anomalously wet 2015-2016 winter season.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70170271','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70170271"><span>Late Holocene sea level variability and Atlantic Meridional Overturning Circulation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Cronin, Thomas M.; Farmer, Jesse R.; Marzen, R. E.; Thomas, E.; Varekamp, J.C.</p> <p>2014-01-01</p> <p>Pre-twentieth century sea level (SL) variability remains poorly understood due to limits of tide gauge records, low temporal resolution of tidal marsh records, and regional anomalies caused by dynamic ocean processes, notably multidecadal changes in Atlantic Meridional Overturning Circulation (AMOC). We examined SL and AMOC variability along the eastern United States over the last 2000 years, using a SL curve constructed from proxy sea surface temperature (SST) records from Chesapeake Bay, and twentieth century SL-sea surface temperature (SST) relations derived from tide gauges and instrumental SST. The SL curve shows multidecadal-scale variability (20–30 years) during the Medieval Climate Anomaly (MCA) and Little Ice Age (LIA), as well as the twentieth century. During these SL oscillations, short-term rates ranged from 2 to 4 mm yr−1, roughly similar to those of the last few decades. These oscillations likely represent internal modes of climate variability related to AMOC variability and originating at high latitudes, although the exact mechanisms remain unclear. Results imply that dynamic ocean changes, in addition to thermosteric, glacio-eustatic, or glacio-isostatic processes are an inherent part of SL variability in coastal regions, even during millennial-scale climate oscillations such as the MCA and LIA and should be factored into efforts that use tide gauges and tidal marsh sediments to understand global sea level rise.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC33H..08M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC33H..08M"><span>Societal Impacts of Natural Decadal Climate Variability - The Pacemakers of Civilizations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mehta, V. M.</p> <p>2017-12-01</p> <p>Natural decadal climate variability (DCV) is one of the oldest areas of climate research. Building on centuries-long literature, a substantial body of research has emerged in the last two to three decades, focused on understanding causes, mechanisms, and impacts of DCV. Several DCV phenomena - the Pacific Decadal Oscillation (PDO) or the Interdecadal Pacific Oscillation (IPO), tropical Atlantic sea-surface temperature gradient variability (TAG for brevity), West Pacific Warm Pool variability, and decadal variability of El Niño-La Niña events - have been identified in observational records; and are associated with variability of worldwide atmospheric circulations, water vapor transport, precipitation, and temperatures; and oceanic circulations, salinity, and temperatures. Tree-ring based drought index data going back more than 700 years show presence of decadal hydrologic cycles (DHCs) in North America, Europe, and South Asia. Some of these cycles were associated with the rise and fall of civilizations, large-scale famines which killed millions of people, and acted as catalysts for socio-political revolutions. Instrument-measured data confirm presence of such worldwide DHCs associated with DCV phenomena; and show these DCV phenomena's worldwide impacts on river flows, crop productions, inland water-borne transportation, hydro-electricity generation, and agricultural irrigation. Fish catch data also show multiyear to decadal catch variability associated with these DCV phenomena in all oceans. This talk, drawn from my recently-published book (Mehta, V.M., 2017: Natural Decadal Climate Variability: Societal Impacts. CRC Press, Boca Raton, Florida, 326 pp.), will give an overview of worldwide impacts of DCV phenomena, with specific examples of socio-economic-political impacts. This talk will also describe national and international security implications of such societal impacts, and worldwide food security implications. The talk will end with an outline of needed actions to adapt to these impacts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003GPC....36...47S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003GPC....36...47S"><span>Millennial-scale climate variations recorded in Early Pliocene colour reflectance time series from the lacustrine Ptolemais Basin (NW Greece)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Steenbrink, J.; Kloosterboer-van Hoeve, M. L.; Hilgen, F. J.</p> <p>2003-03-01</p> <p>Quaternary climate proxy records show compelling evidence for climate variability on time scales of a few thousand years. The causes for these millennial-scale or sub-Milankovitch cycles are still poorly understood, not least due to the complex feedback mechanisms of large ice sheets during the Quaternary. We present evidence of millennial-scale climate variability in Early Pliocene lacustrine sediments from the intramontane Ptolemais Basin in northwestern Greece. The sediments are well exposed in a series of open-pit lignite mines and exhibit a distinct millennial-scale sedimentary cyclicity of alternating lignites and lacustrine marl beds that resulted from precession-induced variations in climate. The higher-frequency, millennial-scale cyclicity is particularly prominent within the grey-coloured marl segment of individual cycles. A stratigraphic interval of ˜115 ka, covering five precession-induced sedimentary cycles, was studied in nine parallel sections from two open-pit lignite mines located several km apart. High-resolution colour reflectance records were used to quantify the within-cycle variability and to determine its lateral continuity. Much of the within-cycle variability could be correlated between the parallel sections, even in fine detail, which suggests that these changes reflect basin-wide variations in environmental conditions related to (regional) climate fluctuations. Interbedded volcanic ash beds demonstrate the synchronicity of these fluctuations and spectral analysis of the reflectance time series shows a significant concentration of within-cycle variability at periods of ˜11, ˜5.5 and ˜2 ka. The occurrence of variability at such time scales at times before the intensification of the Northern Hemisphere glaciation suggests that they cannot solely have resulted from internal ice-sheet dynamics. Possible candidates include harmonics or combination tones of the main orbital cycles, variations in solar output or periodic motions of the Earth and Moon.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018QSRv..190...20K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018QSRv..190...20K"><span>Centennial-scale vegetation dynamics and climate variability in SE Europe during Marine Isotope Stage 11 based on a pollen record from Lake Ohrid</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kousis, Ilias; Koutsodendris, Andreas; Peyron, Odile; Leicher, Niklas; Francke, Alexander; Wagner, Bernd; Giaccio, Biagio; Knipping, Maria; Pross, Jörg</p> <p>2018-06-01</p> <p>To better understand climate variability during Marine Isotope Stage (MIS) 11, we here present a new, centennial-scale-resolution pollen record from Lake Ohrid (Balkan Peninsula) derived from sediment cores retrieved during an International Continental Scientific Drilling Program (ICDP) campaign. Our palynological data, augmented by quantitative pollen-based climate reconstructions, provide insight into the vegetation dynamics and thus also climate variability in SE Europe during one of the best orbital analogues for the Holocene. Comparison of our palynological results with other proxy data from Lake Ohrid as well as with regional and global climate records shows that the vegetation in SE Europe responded sensitively both to long- and short-term climate change during MIS 11. The chronology of our palynological record is based on orbital tuning, and is further supported by the detection of a new tephra from the Vico volcano, central Italy, dated to 410 ± 2 ka. Our study indicates that MIS 11c (∼424-398 ka) was the warmest interval of MIS 11. The younger part of the interglacial (i.e., MIS 11b-11a; ∼398-367 ka) exhibits a gradual cooling trend passing over into MIS 10. It is characterized by considerable millennial-scale variability as inferred by six abrupt forest-contraction events. Interestingly, the first forest contraction occurred during full interglacial conditions of MIS 11c; this event lasted for ∼1.7 kyrs (406.2-404.5 ka) and was characterized by substantial reductions in winter temperature and annual precipitation. Most notably, it occurred ∼7 ka before the end of MIS 11c and ∼15 ka before the first strong ice-rafted debris event in the North Atlantic. Our findings suggest that millennial-scale climate variability during MIS 11 was established in Southern Europe already during MIS 11c, which is earlier than in the North Atlantic where it is registered only from MIS 11b onwards.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20080722','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20080722"><span>High skill in low-frequency climate response through fluctuation dissipation theorems despite structural instability.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Majda, Andrew J; Abramov, Rafail; Gershgorin, Boris</p> <p>2010-01-12</p> <p>Climate change science focuses on predicting the coarse-grained, planetary-scale, longtime changes in the climate system due to either changes in external forcing or internal variability, such as the impact of increased carbon dioxide. The predictions of climate change science are carried out through comprehensive, computational atmospheric, and oceanic simulation models, which necessarily parameterize physical features such as clouds, sea ice cover, etc. Recently, it has been suggested that there is irreducible imprecision in such climate models that manifests itself as structural instability in climate statistics and which can significantly hamper the skill of computer models for climate change. A systematic approach to deal with this irreducible imprecision is advocated through algorithms based on the Fluctuation Dissipation Theorem (FDT). There are important practical and computational advantages for climate change science when a skillful FDT algorithm is established. The FDT response operator can be utilized directly for multiple climate change scenarios, multiple changes in forcing, and other parameters, such as damping and inverse modelling directly without the need of running the complex climate model in each individual case. The high skill of FDT in predicting climate change, despite structural instability, is developed in an unambiguous fashion using mathematical theory as guidelines in three different test models: a generic class of analytical models mimicking the dynamical core of the computer climate models, reduced stochastic models for low-frequency variability, and models with a significant new type of irreducible imprecision involving many fast, unstable modes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5027332','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5027332"><span>A multicenter study: how do medical students perceive clinical learning climate?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Yilmaz, Nilufer Demiral; Velipasaoglu, Serpil; Ozan, Sema; Basusta, Bilge Uzun; Midik, Ozlem; Mamakli, Sumer; Karaoglu, Nazan; Tengiz, Funda; Durak, Halil İbrahim; Sahin, Hatice</p> <p>2016-01-01</p> <p>Background The relationship between students and instructors is of crucial importance for the development of a positive learning climate. Learning climate is a multifaceted concept, and its measurement is a complicated process. The aim of this cross-sectional study was to determine medical students’ perceptions about the clinical learning climate and to investigate differences in their perceptions in terms of various variables. Methods Medical students studying at six medical schools in Turkey were recruited for the study. All students who completed clinical rotations, which lasted for 3 or more weeks, were included in the study (n=3,097). Data were collected using the Clinical Learning Climate Scale (CLCS). The CLCS (36 items) includes three subscales: clinical environment, emotion, and motivation. Each item is scored using a 5-point Likert scale (1: strongly disagree to 5: strongly agree). Results The response rate for the trainees was 69.67% (n=1,519), and for the interns it was 51.47% (n=917). The mean total CLCS score was 117.20±17.19. The rotation during which the clinical learning climate was perceived most favorably was the Physical Therapy and Rehabilitation rotation (mean score: 137.77). The most negatively perceived rotation was the General Internal Medicine rotation (mean score: 104.31). There were significant differences between mean total scores in terms of trainee/intern characteristics, internal medicine/surgical medicine rotations, and perception of success. Conclusion The results of this study drew attention to certain aspects of the clinical learning climate in medical schools. Clinical teacher/instructor/supervisor, clinical training programs, students’ interactions in clinical settings, self-realization, mood, students’ intrinsic motivation, and institutional commitment are important components of the clinical learning climate. For this reason, the aforementioned components should be taken into consideration in studies aiming to improve clinical learning climate. PMID:27640648</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017NatCo...814991L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017NatCo...814991L"><span>On the discrepancy between observed and CMIP5 multi-model simulated Barents Sea winter sea ice decline</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Dawei; Zhang, Rong; Knutson, Thomas R.</p> <p>2017-04-01</p> <p>This study aims to understand the relative roles of external forcing versus internal climate variability in causing the observed Barents Sea winter sea ice extent (SIE) decline since 1979. We identify major discrepancies in the spatial patterns of winter Northern Hemisphere sea ice concentration trends over the satellite period between observations and CMIP5 multi-model mean externally forced response. The CMIP5 externally forced decline in Barents Sea winter SIE is much weaker than that observed. Across CMIP5 ensemble members, March Barents Sea SIE trends have little correlation with global mean surface air temperature trends, but are strongly anti-correlated with trends in Atlantic heat transport across the Barents Sea Opening (BSO). Further comparison with control simulations from coupled climate models suggests that enhanced Atlantic heat transport across the BSO associated with regional internal variability may have played a leading role in the observed decline in winter Barents Sea SIE since 1979.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMSH43B2814O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMSH43B2814O"><span>Lagged correlations between the NAO and the 11-year solar cycle: forced response or internal variability?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Oehrlein, J.; Chiodo, G.; Polvani, L. M.; Smith, A. K.</p> <p>2017-12-01</p> <p>Recently, the North Atlantic Oscillation has been suggested to respond to the 11-year solar cycle with a lag of a few years. The solar/NAO relationship provides a potential pathway for solar activity to modulate surface climate. However, a short observational record paired with the strong internal variability of the NAO raises questions about the robustness of the claimed solar/NAO relationship. For the first time, we investigate the robustness of the solar/NAO signal in four different reanalysis data sets and long integrations from an ocean-coupled chemistry-climate model forced with the 11-year solar cycle. The signal appears to be robust in the different reanalysis datasets. We also show, for the first time, that many features of the observed signal, such as amplitude, spatial pattern, and lag of 2/3 years, can be accurately reproduced in our model simulations. However, in both the reanalysis and model simulations, we find that this signal is non-stationary. A lagged NAO/solar signal can also be reproduced in two sets of model integrations without the 11-year solar cycle. This suggests that the correlation found in observational data could be the result of internal decadal variability in the NAO and not a response to the solar cycle. This has wide implications towards the interpretation of solar signals in observational data.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC34A..02H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC34A..02H"><span>Contributions of internal climate variability to mitigation of projected future regional sea level rise</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hu, A.; Bates, S. C.</p> <p>2017-12-01</p> <p>Observations indicate that the global mean surface temperature is rising, so does the global mean sea level. Sea level rise (SLR) can impose significant impacts on island and coastal communities, especially when SLR is compounded with storm surges. Here, via analyzing results from two sets of ensemble simulations from the Community Earth System Model version 1, we investigate how the potential SLR benefits through mitigating the future emission scenarios from business as usual to a mild-mitigation over the 21st Century would be affected by internal climate variability. Results show that there is almost no SLR benefit in the near term due to the large SLR variability due to the internal ocean dynamics. However, toward the end of the 21st century, the SLR benefit can be as much as a 26±1% reduction of the global mean SLR due to seawater thermal expansion. Regionally, the benefits from this mitigation for both near and long terms are heterogeneous. They vary from just a 11±5% SLR reduction in Melbourne, Australia to a 35±6% reduction in London. The processes contributing to these regional differences are the coupling of the wind-driven ocean circulation with the decadal scale sea surface temperature mode in the Pacific and Southern Oceans, and the changes of the thermohaline circulation and the mid-latitude air-sea coupling in the Atlantic.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..558....9V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..558....9V"><span>Greenhouse gas scenario sensitivity and uncertainties in precipitation projections for central Belgium</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Van Uytven, E.; Willems, P.</p> <p>2018-03-01</p> <p>Climate change impact assessment on meteorological variables involves large uncertainties as a result of incomplete knowledge on the future greenhouse gas concentrations and climate model physics, next to the inherent internal variability of the climate system. Given that the alteration in greenhouse gas concentrations is the driver for the change, one expects the impacts to be highly dependent on the considered greenhouse gas scenario (GHS). In this study, we denote this behavior as GHS sensitivity. Due to the climate model related uncertainties, this sensitivity is, at local scale, not always that strong as expected. This paper aims to study the GHS sensitivity and its contributing role to climate scenarios for a case study in Belgium. An ensemble of 160 CMIP5 climate model runs is considered and climate change signals are studied for precipitation accumulation, daily precipitation intensities and wet day frequencies. This was done for the different seasons of the year and the scenario periods 2011-2040, 2031-2060, 2051-2081 and 2071-2100. By means of variance decomposition, the total variance in the climate change signals was separated in the contribution of the differences in GHSs and the other model-related uncertainty sources. These contributions were found dependent on the variable and season. Following the time of emergence concept, the GHS uncertainty contribution is found dependent on the time horizon and increases over time. For the most distinct time horizon (2071-2100), the climate model uncertainty accounts for the largest uncertainty contribution. The GHS differences explain up to 18% of the total variance in the climate change signals. The results point further at the importance of the climate model ensemble design, specifically the ensemble size and the combination of climate models, whereupon climate scenarios are based. The numerical noise, introduced at scales smaller than the skillful scale, e.g. at local scale, was not considered in this study.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.1965B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.1965B"><span>Forward modeling of tree-ring data: a case study with a global network</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Breitenmoser, P. D.; Frank, D.; Brönnimann, S.</p> <p>2012-04-01</p> <p>Information derived from tree-rings is one of the most powerful tools presently available for studying past climatic variability as well as identifying fundamental relationships between tree-growth and climate. Climate reconstructions are typically performed by extending linear relationships, established during the overlapping period of instrumental and climate proxy archives into the past. Such analyses, however, are limited by methodological assumptions, including stationarity and linearity of the climate-proxy relationship. We investigate climate and tree-ring data using the Vaganov-Shashkin-Lite (VS-Lite) forward model of tree-ring width formation to examine the relations among actual tree growth and climate (as inferred from the simulated chronologies) to reconstruct past climate variability. The VS-lite model has been shown to produce skill comparable to that achieved using classical dendrochronological statistical modeling techniques when applied on simulations of a network of North American tree-ring chronologies. Although the detailed mechanistic processes such as photosynthesis, storage, or cell processes are not modeled directly, the net effect of the dominating nonlinear climatic controls on tree-growth are implemented into the model by the principle of limiting factors and threshold growth response functions. The VS-lite model requires as inputs only latitude, monthly mean temperature and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree-rings to monthly climate conditions obtained from the 20th century reanalysis project back to 1871. These simulated tree-ring chronologies are compared to the climate-driven variability in worldwide observed tree-ring chronologies from the International Tree Ring Database. Results point toward the suitability of the relationship among actual tree growth and climate (as inferred from the simulated chronologies) for use in global palaeoclimate reconstructions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AMT....11.3021K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AMT....11.3021K"><span>Is it feasible to estimate radiosonde biases from interlaced measurements?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kremser, Stefanie; Tradowsky, Jordis S.; Rust, Henning W.; Bodeker, Greg E.</p> <p>2018-05-01</p> <p>Upper-air measurements of essential climate variables (ECVs), such as temperature, are crucial for climate monitoring and climate change detection. Because of the internal variability of the climate system, many decades of measurements are typically required to robustly detect any trend in the climate data record. It is imperative for the records to be temporally homogeneous over many decades to confidently estimate any trend. Historically, records of upper-air measurements were primarily made for short-term weather forecasts and as such are seldom suitable for studying long-term climate change as they lack the required continuity and homogeneity. Recognizing this, the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) has been established to provide reference-quality measurements of climate variables, such as temperature, pressure, and humidity, together with well-characterized and traceable estimates of the measurement uncertainty. To ensure that GRUAN data products are suitable to detect climate change, a scientifically robust instrument replacement strategy must always be adopted whenever there is a change in instrumentation. By fully characterizing any systematic differences between the old and new measurement system a temporally homogeneous data series can be created. One strategy is to operate both the old and new instruments in tandem for some overlap period to characterize any inter-instrument biases. However, this strategy can be prohibitively expensive at measurement sites operated by national weather services or research institutes. An alternative strategy that has been proposed is to alternate between the old and new instruments, so-called interlacing, and then statistically derive the systematic biases between the two instruments. Here we investigate the feasibility of such an approach specifically for radiosondes, i.e. flying the old and new instruments on alternating days. Synthetic data sets are used to explore the applicability of this statistical approach to radiosonde change management.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1616815L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1616815L"><span>The MedCLIVAR Network</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lionello, Piero; Medclivar Sc, The</p> <p>2014-05-01</p> <p>MedCLIVAR serves as a scientific network to promote interaction among different scientific disciplines and to develop a multidisciplinary vision of the evolution of the Mediterranean climate through studies that integrate atmospheric, marine, and terrestrial climate components at time scales ranging from paleoreconstructions to future climate scenarios. The network deals with scientific issues including past climate variability; connections between the Mediterranean and global climate; the Mediterranean Sea circulation and sea level; feedbacks on the global climate system; and regional responses to greenhouse gas, air pollution, and aerosols. The MedCLIVAR initiative was proposed at the 2003 European Geosciences Union assembly in Nice, France. In 2005, it was endorsed by the International Climate Variability and Predictability (CLIVAR) office. Subsequently, the MedCLIVAR Research Network Project was formally approved by the European Science Foundation and launched in May 2006 for a five year duration. Now MedCLIVAR is continuing with self supporting initiatives, such as the third MedCLIVAR conference, which will be held in June 2014 in Ankara (Turkey) , the publication of a special issue of Regional Environmental Change devoted to the climate of the Mediterranean region, and a newsletter, which is published every six months. More information available in Lionello, P., Gacic, M., Gomis, D., Garcia-Herrera, R., Giorgi, F., Planton, S., Trigo, R., (...), Xoplaki, E. (2012) Program focuses on climate of the Mediterranean region, Eos Trans. AGU 93:105-106</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSPO34D3105A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSPO34D3105A"><span>Variability of Equatorward Transport in the Tropical Southwestern Pacific</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alberty, M. S.; Sprintall, J.; MacKinnon, J. A.; Cravatte, S. E.; Ganachaud, A. S.; Germineaud, C.</p> <p>2016-02-01</p> <p>Situated in the Pacific warm pool, the Solomon Sea is a semi-enclosed sea containing a system of low latitude Western boundary currents that serve as the primary source water for the Equatorial Undercurrent. The variability of equatorward heat and volume transport through the Solomon Sea has the capability to modulate regional and basin-scale climate processes, yet there are few and synoptic observations of these fluxes. Here we present the mean and variability of heat and volume transport out of the Solomon Sea observed during the MoorSPICE experiment. MoorSPICE is the Solomon Sea mooring-based observational component of the Southwest Pacific Ocean Circulation and Climate Experiment (SPICE), an international research project working to observe and improve our understanding of the southwest Pacific Ocean circulation and climate. Arrays of moorings were deployed in the outflow channels of the Solomon Sea for July 2012 until March 2014 to resolve the temperature and velocity fields in each strait. In particular we will discuss the phasing of the observed transport variability for each channel compared to that of the satellite-observed monsoonal wind forcing and annual cycle of the mesoscale eddy field.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSPC11A..07R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSPC11A..07R"><span>Uncertainty in future projections of global and regional marine fisheries catches</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Reygondeau, G.; Cheung, W. W. L.; Froelicher, T. L.; Stock, C. A.; Jones, M. C.; Sarmiento, J. L.</p> <p>2016-02-01</p> <p>Previous studies have projected the global redistribution of potential marine fisheries catches by mid-21st century under climate change, with increases in high latitude regions and pronounced decreases in tropical biomes. However, quantified confidence levels of such projections are not available, rendering it difficult to interpret the associated risk to society. This paper quantifies the confidence of changes in future fish production using a 30-member ensemble simulation of the Geophysical Fluid Dynamics Laboratory ESM2M (representing internal variability of oceanographic conditions), three structural variants of a mechanistic species distribution model (representing uncertainty in fisheries models and different greenhouse gas emission and fishing scenarios (representing scenario uncertainty). We project that total potential catches of 500 exploited fish and invertebrate stocks, that contribute most to regional fisheries catches and their variability, will likely decrease in the 21st century under a `business-as-usual' greenhouse gas emission scenario (RCP8.5). Fishing and it's management remains a main factor determining future fish stocks and their catches. Internal variability of projected ocean conditions, including temperature, oxygen level, pH, net primary production and sea ice contributes substantially to the uncertainty of potential catch projections. Regionally, climate-driven decreases in potential catches in tropical oceans and increases in the Arctic polar regions are projected with higher confidence than other regions, while the direction of changes in most mid-latitude (or temperate) regions is uncertain. Under a stringent greenhouse gas mitigation scenario (RCP 2.6), climate change impacts on potential catches may not emerge from their uncertainties. Overall, this study provides a foundation for quantifying risks of climate change impacts on marine fisheries globally and regionally, and how such risk may be altered by policy interventions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.B41G0390F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.B41G0390F"><span>Reversible and irreversible impacts of greenhouse gas emissions in multi-century projections with the NCAR global coupled carbon cycle-climate model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Froelicher, T. L.; Joos, F.</p> <p>2010-12-01</p> <p>The legacy of historical and the long-term impacts of 21st century greenhouse gas emissions on climate, ocean acidification, and carbon-climate feedbacks are investigated with a coupled carbon cycle-climate model. Emission commitment scenarios with zero emissions after year 2100 and 21st century emissions of 1,800, 900, and 0 gigatons of carbon are run up to year 2500. The reversibility and irreversibility of impacts is quantified by comparing anthropogenically-forced regional changes with internal, unforced climate variability. We show that the influence of historical emissions and of non-CO2 agents is largely reversible on the regional scale. Forced changes in surface temperature and precipitation become smaller than internal variability for most land and ocean grid cells in the absence of future carbon emissions. In contrast, continued carbon emissions over the 21st century cause irreversible climate change on centennial to millennial timescales in most regions and impacts related to ocean acidification and sea level rise continue to aggravate for centuries even if emissions are stopped in year 2100. Undersaturation of the Arctic surface ocean with respect to aragonite, a mineral form of calcium carbonate secreted by marine organisms, is imminent and remains widespread. The volume of supersaturated water providing habitat to calcifying organisms is reduced from preindustrial 40 to 25% in 2100 and to 10% in 2300 for the high emission case. We conclude that emission trading schemes, related to the Kyoto Process,should not permit trading between emissions of relatively short-lived agents and CO2 given the irreversible impacts of anthropogenic carbon emissions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ClDy...35.1439F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ClDy...35.1439F"><span>Reversible and irreversible impacts of greenhouse gas emissions in multi-century projections with the NCAR global coupled carbon cycle-climate model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Frölicher, Thomas L.; Joos, Fortunat</p> <p>2010-12-01</p> <p>The legacy of historical and the long-term impacts of 21st century greenhouse gas emissions on climate, ocean acidification, and carbon-climate feedbacks are investigated with a coupled carbon cycle-climate model. Emission commitment scenarios with zero emissions after year 2100 and 21st century emissions of 1,800, 900, and 0 gigatons of carbon are run up to year 2500. The reversibility and irreversibility of impacts is quantified by comparing anthropogenically-forced regional changes with internal, unforced climate variability. We show that the influence of historical emissions and of non-CO2 agents is largely reversible on the regional scale. Forced changes in surface temperature and precipitation become smaller than internal variability for most land and ocean grid cells in the absence of future carbon emissions. In contrast, continued carbon emissions over the 21st century cause irreversible climate change on centennial to millennial timescales in most regions and impacts related to ocean acidification and sea level rise continue to aggravate for centuries even if emissions are stopped in year 2100. Undersaturation of the Arctic surface ocean with respect to aragonite, a mineral form of calcium carbonate secreted by marine organisms, is imminent and remains widespread. The volume of supersaturated water providing habitat to calcifying organisms is reduced from preindustrial 40 to 25% in 2100 and to 10% in 2300 for the high emission case. We conclude that emission trading schemes, related to the Kyoto Process, should not permit trading between emissions of relatively short-lived agents and CO2 given the irreversible impacts of anthropogenic carbon emissions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/10165499','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/10165499"><span>Detection of greenhouse-gas-induced climatic change. Progress report, 1 December 1991--30 June 1994</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Wigley, T.M.L.; Jones, P.D.</p> <p>1994-07-01</p> <p>In addition to changes due to variations in greenhouse gas concentrations, the global climate system exhibits a high degree of internally-generated and externally-forced natural variability. To detect the enhanced greenhouse effect, its signal must be isolated from the ``noise`` of this natural climatic variability. A high quality, spatially extensive data base is required to define the noise and its spatial characteristics. To facilitate this, available land and marine data bases will be updated and expanded. The data will be analyzed to determine the potential effects on climate of greenhouse gas concentration changes and other factors. Analyses will be guided bymore » a variety of models, from simple energy balance climate models to ocean General Circulation Models. Appendices A--G contain the following seven papers: (A) Recent global warmth moderated by the effects of the Mount Pinatubo eruption; (B) Recent warming in global temperature series; (C) Correlation methods in fingerprint detection studies; (D) Balancing the carbon budget. Implications for projections of future carbon dioxide concentration changes; (E) A simple model for estimating methane concentration and lifetime variations; (F) Implications for climate and sea level of revised IPCC emissions scenarios; and (G) Sulfate aerosol and climatic change.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27329411','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27329411"><span>Quantitative Estimation of the Climatic Effects of Carbon Transferred by International Trade.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wei, Ting; Dong, Wenjie; Moore, John; Yan, Qing; Song, Yi; Yang, Zhiyong; Yuan, Wenping; Chou, Jieming; Cui, Xuefeng; Yan, Xiaodong; Wei, Zhigang; Guo, Yan; Yang, Shili; Tian, Di; Lin, Pengfei; Yang, Song; Wen, Zhiping; Lin, Hui; Chen, Min; Feng, Guolin; Jiang, Yundi; Zhu, Xian; Chen, Juan; Wei, Xin; Shi, Wen; Zhang, Zhiguo; Dong, Juan; Li, Yexin; Chen, Deliang</p> <p>2016-06-22</p> <p>Carbon transfer via international trade affects the spatial pattern of global carbon emissions by redistributing emissions related to production of goods and services. It has potential impacts on attribution of the responsibility of various countries for climate change and formulation of carbon-reduction policies. However, the effect of carbon transfer on climate change has not been quantified. Here, we present a quantitative estimate of climatic impacts of carbon transfer based on a simple CO2 Impulse Response Function and three Earth System Models. The results suggest that carbon transfer leads to a migration of CO2 by 0.1-3.9 ppm or 3-9% of the rise in the global atmospheric concentrations from developed countries to developing countries during 1990-2005 and potentially reduces the effectiveness of the Kyoto Protocol by up to 5.3%. However, the induced atmospheric CO2 concentration and climate changes (e.g., in temperature, ocean heat content, and sea-ice) are very small and lie within observed interannual variability. Given continuous growth of transferred carbon emissions and their proportion in global total carbon emissions, the climatic effect of traded carbon is likely to become more significant in the future, highlighting the need to consider carbon transfer in future climate negotiations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27265871','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27265871"><span>Safety climate, emotional exhaustion and job satisfaction among Brazilian paediatric professional nurses.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Alves, D F S; Guirardello, E B</p> <p>2016-09-01</p> <p>International studies indicate that job satisfaction and burnout interfere with the safety climate and quality of care. However, no evidence of such relationships is available for Brazilian paediatric hospitals. To assess the correlation and predictive effect of emotional exhaustion and job satisfaction on the perception of professional nurses at paediatric hospitals regarding safety climate and quality of care. Cross-sectional correlational design. The study was conducted with registered nurses, technician and assistant nurses from two Brazilian paediatric hospitals over 3 months in 2013-2014 using instruments to assess safety climate, quality of care, job satisfaction and emotional exhaustion. Data related to 267 professional nurses from 15 inpatient wards and 3 intensive care units were analysed. Overall, the respondents exhibited moderate emotional exhaustion, were satisfied with their jobs and considered the quality of care as good. However, the respondents exhibited low concordance as to the positive perception of the safety climate. The variables, emotional exhaustion and job satisfaction, exhibited significant correlations with safety climate and were considered predictive of the latter. Emotional exhaustion and job satisfaction among professional nurses influence the safety climate at paediatric hospitals. Investments to reduce emotional exhaustion and to improve job satisfaction among professional nurses allocated to paediatric hospitals might contribute to the patients' safety. © 2016 International Council of Nurses.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp...92D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp...92D"><span>Breakdown of NAO reproducibility into internal versus externally-forced components: a two-tier pilot study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Douville, Hervé; Ribes, A.; Tyteca, S.</p> <p>2018-03-01</p> <p>Assessing the ability of atmospheric models to capture observed climate variations when driven by observed sea surface temperature (SST), sea ice concentration (SIC) and radiative forcings is a prerequisite for the feasibility of near term climate predictions. Here we achieve ensembles of global atmospheric simulations to assess and attribute the reproducibility of the boreal winter atmospheric circulation against the European Centre for Medium Range Forecasts (ECMWF) twentieth century reanalysis (ERA20C). Our control experiment is driven by the observed SST/SIC from the Atmospheric Model Intercomparison Project. It is compared to a similar ensemble performed with the ECMWF model as a first step toward ERA20C. Moreover, a two-tier methodology is used to disentangle externally-forced versus internal variations in the observed SST/SIC boundary conditions and run additional ensembles allowing us to attribute the observed atmospheric variability. The focus is mainly on the North Atlantic Oscillation (NAO) variability which is more reproducible in our model than in the ECMWF model. This result is partly due to the simulation of a positive NAO trend across the full 1920-2014 integration period. In line with former studies, this trend might be mediated by a circumglobal teleconnection mechanism triggered by increasing precipitation over the tropical Indian Ocean (TIO). Surprisingly, this response is mainly related to the internal SST variability and is not found in the ECMWF model driven by an alternative SST dataset showing a weaker TIO warming in the first half of the twentieth century. Our results may reconcile the twentieth century observations with the twenty-first century projections of the NAO. They should be however considered with caution given the limited size of our ensembles, the possible influence of other sources of NAO variability, and the uncertainties in the tropical SST trend and breakdown between internal versus externally-forced variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017198','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017198"><span>Improving Decision-Making Activities for Meningitis and Malaria</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ceccato, Pietro; Trzaska, Sylwia; Garcia-Pando, Carlos Perez; Kalashnikova, Olga; del Corral, John; Cousin, Remi; Blumenthal, M. Benno; Bell, Michael; Connor, Stephen J.; Thomson, Madeleine C.</p> <p>2013-01-01</p> <p>Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular meningitis and malaria. In this paper, we present the new and improved products that have been developed for: (i) estimating dust aerosol for forecasting risks of meningitis and (ii) for monitoring temperature and rainfall and integrating them into a vectorial capacity model for forecasting risks of malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map Room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28504631','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28504631"><span>[Climate change, floods and health intervention].</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Furu, Peter; Tellier, Siri; Vestergaard, Lasse S</p> <p>2017-05-15</p> <p>Climate change and variability are considered some of the biggest threats to human health in the 21st century. Extreme weather events such as floods and storms are examples of natural hazards resulting in highest number of disasters and with considerable mortality and morbidity among vulnerable communities. A coordinated, well-planned management of health interventions must be taken for timely action in the response, recovery, prevention and preparedness phases of disasters. Roles and responsibilities of international as well as national organizations and authorities are discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhDT.......164G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhDT.......164G"><span>Quantifying the Influence of Dynamics Across Scales on Regional Climate Uncertainty in Western North America</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Goldenson, Naomi L.</p> <p></p> <p>Uncertainties in climate projections at the regional scale are inevitably larger than those for global mean quantities. Here, focusing on western North American regional climate, several approaches are taken to quantifying uncertainties starting with the output of global climate model projections. Internal variance is found to be an important component of the projection uncertainty up and down the west coast. To quantify internal variance and other projection uncertainties in existing climate models, we evaluate different ensemble configurations. Using a statistical framework to simultaneously account for multiple sources of uncertainty, we find internal variability can be quantified consistently using a large ensemble or an ensemble of opportunity that includes small ensembles from multiple models and climate scenarios. The latter offers the advantage of also producing estimates of uncertainty due to model differences. We conclude that climate projection uncertainties are best assessed using small single-model ensembles from as many model-scenario pairings as computationally feasible. We then conduct a small single-model ensemble of simulations using the Model for Prediction Across Scales with physics from the Community Atmosphere Model Version 5 (MPAS-CAM5) and prescribed historical sea surface temperatures. In the global variable resolution domain, the finest resolution (at 30 km) is in our region of interest over western North America and upwind over the northeast Pacific. In the finer-scale region, extreme precipitation from atmospheric rivers (ARs) is connected to tendencies in seasonal snowpack in mountains of the Northwest United States and California. In most of the Cascade Mountains, winters with more AR days are associated with less snowpack, in contrast to the northern Rockies and California's Sierra Nevadas. In snowpack observations and reanalysis of the atmospheric circulation, we find similar relationships between frequency of AR events and winter season snowpack in the western United States. In spring, however, there is not a clear relationship between number of AR days and seasonal mean snowpack across the model ensemble, so caution is urged in interpreting the historical record in the spring season. Finally, the representation of the El Nino Southern Oscillation (ENSO)--an important source of interannual climate predictability in some regions--is explored in a large single-model ensemble using ensemble Empirical Orthogonal Functions (EOFs) to find modes of variance across the entire ensemble at once. The leading EOF is ENSO. The principal components (PCs) of the next three EOFs exhibit a lead-lag relationship with the ENSO signal captured in the first PC. The second PC, with most of its variance in the summer season, is the most strongly cross-correlated with the first. This approach offers insight into how the model considered represents this important atmosphere-ocean interaction. Taken together these varied approaches quantify the implications of climate projections regionally, identify processes that make snowpack water resources vulnerable, and seek insight into how to better simulate the large-scale climate modes controlling regional variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..557..448L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..557..448L"><span>The cumulative effects of forest disturbance and climate variability on streamflow components in a large forest-dominated watershed</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Qiang; Wei, Xiaohua; Zhang, Mingfang; Liu, Wenfei; Giles-Hansen, Krysta; Wang, Yi</p> <p>2018-02-01</p> <p>Assessing how forest disturbance and climate variability affect streamflow components is critical for watershed management, ecosystem protection, and engineering design. Previous studies have mainly evaluated the effects of forest disturbance on total streamflow, rarely with attention given to its components (e.g., base flow and surface runoff), particularly in large watersheds (>1000 km2). In this study, the Upper Similkameen River watershed (1810 km2), an international watershed situated between Canada and the USA, was selected to examine how forest disturbance and climate variability interactively affect total streamflow, baseflow, and surface runoff. Baseflow was separated using a combination of the recursive digital filter method and conductivity mass balance method. Time series analysis and modified double mass curves were then employed to quantitatively separate the relative contributions of forest disturbance and climate variability to each streamflow component. Our results showed that average annual baseflow and baseflow index (baseflow/streamflow) were 113.3 ± 35.6 mm year-1 and 0.27 for 1954-2013, respectively. Forest disturbance increased annual streamflow, baseflow, and surface runoff of 27.7 ± 13.7 mm, 7.4 ± 3.6 mm, and 18.4 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 27.0 ± 23.0%, 29.2 ± 23.1%, and 25.7 ± 23.4%, respectively. In contrast, climate variability decreased them by 74.9 ± 13.7 mm, 17.9 ± 3.6 mm, and 53.3 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 73.0 ± 23.0%, 70.8 ± 23.1% and 73.1 ± 23.4%, respectively. Despite working in opposite ways, the impacts of climate variability on annual streamflow, baseflow, and surface runoff were of a much greater magnitude than forest disturbance impacts. This study has important implications for the protection of aquatic habitat, engineering design, and watershed planning in the context of future forest disturbance and climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMGC43B0929J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMGC43B0929J"><span>How Does The Climate Change?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jones, R. N.</p> <p>2011-12-01</p> <p>In 1997, maximum temperature in SE Australia shifted up by 0.8°C at pH0<0.01. Rainfall decreased by 13% in 1997-2010 compared to 1900-1996. Statistically significant shifts also occur in impact indicators: baumé levels in winegrapes shift >21 days earlier from 1998, streamflow records decrease by 30-70% from 1997 and annual mean forest fire danger index increased by 38% from 1997. Despite catastrophic fires killing 178 people in early 2009, the public remains unaware of this large change in their exposure. When regional temperature was separated into internally and externally forced components, the latter component was found to warm in two steps, in 1968-73 and 1997. These dates coincide with shifts in zonal mean temperature (24-44S; Figure 1). Climate model output shows similar step and trend behavior. Tests run on zonal, hemispheric and global mean temperature observations found shifts in all regions. 1997 marks a shift in global temperature of 0.3°C at pH0<0.01. Similar shifts occur in long-term tide gauge records around the globe (e.g., Figure 2) and in ocean heat content. The prevailing paradigm for how climate variables change is signal-noise construct combining a smooth signal with variations caused by internal climate variability. There seems to be no sound theoretical basis for this assumption. On the contrary, complex system behavior would suggest non-linear responses to externally forced change, especially at the regional scale. Some of our most basic assumptions about how climate changes may need to be re-examined.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC42B..05K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC42B..05K"><span>Real-time monitoring of smallholder farmer responses to intra-seasonal climate variability in central Kenya</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Krell, N.; Evans, T. P.; Estes, L. D.; Caylor, K. K.</p> <p>2017-12-01</p> <p>While international metrics of food security and water availability are generated as spatial averages at the regional to national levels, climate variability impacts are differentially felt at the household level. This project investigated scales of variability of climate impacts on smallholder farmers using social and environmental data in central Kenya. Using sub-daily real-time environmental measurements to monitor smallholder agriculture, we investigated how changes in seasonal precipitation affected food security around Laikipia county from September 2015 to present. We also conducted SMS-based surveys of over 700 farmers to understand farmers' decision-making within the growing season. Our results highlight field-scale heterogeneity in biophysical and social factors governing crop yields using locally sensed real-time environmental data and weekly farmer-reported information about planting, harvesting, irrigation, and crop yields. Our preliminary results show relationships between changes in seasonal precipitation, NDVI, and soil moisture related to crop yields and decision-making at several scales. These datasets present a unique opportunity to collect highly spatially and temporally resolved information from data-poor regions at the household level.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1713557E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1713557E"><span>Roosevelt Island Climate Evolution Project (RICE): A 65 Kyr ice core record of black carbon aerosol deposition to the Ross Ice Shelf, West Antarctica.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Edwards, Ross; Bertler, Nancy; Tuohy, Andrea; Neff, Peter; Proemse, Bernedette; Feiteng, Wang; Goodwin, Ian; Hogan, Chad</p> <p>2015-04-01</p> <p>Emitted by fires, black carbon aerosols (rBC) perturb the atmosphere's physical and chemical properties and are climatically active. Sedimentary charcoal and other paleo-fire records suggest that rBC emissions have varied significantly in the past due to human activity and climate variability. However, few paleo rBC records exist to constrain reconstructions of the past rBC atmospheric distribution and its climate interaction. As part of the international Roosevelt Island Climate Evolution (RICE) project, we have developed an Antarctic rBC ice core record spanning the past ~65 Kyr. The RICE deep ice core was drilled from the Roosevelt Island ice dome in West Antarctica from 2011 to 2013. The high depth resolution (~ 1 cm) record was developed using a single particle intracavity laser-induced incandescence soot photometer (SP2) coupled to an ice core melter system. The rBC record displays sub-annual variability consistent with both austral dry-season and summer biomass burning. The record exhibits significant decadal to millennial-scale variability consistent with known changes in climate. Glacial rBC concentrations were much lower than Holocene concentrations with the exception of several periods of abrupt increases in rBC. The transition from glacial to interglacial rBC concentrations occurred over a much longer time relative to other ice core climate proxies such as water isotopes and suggests . The protracted increase in rBC during the transition may reflected Southern hemisphere ecosystem / fire regime changes in response to hydroclimate and human activity.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26302149','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26302149"><span>A Bayesian model for quantifying the change in mortality associated with future ozone exposures under climate change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Alexeeff, Stacey E; Pfister, Gabriele G; Nychka, Doug</p> <p>2016-03-01</p> <p>Climate change is expected to have many impacts on the environment, including changes in ozone concentrations at the surface level. A key public health concern is the potential increase in ozone-related summertime mortality if surface ozone concentrations rise in response to climate change. Although ozone formation depends partly on summertime weather, which exhibits considerable inter-annual variability, previous health impact studies have not incorporated the variability of ozone into their prediction models. A major source of uncertainty in the health impacts is the variability of the modeled ozone concentrations. We propose a Bayesian model and Monte Carlo estimation method for quantifying health effects of future ozone. An advantage of this approach is that we include the uncertainty in both the health effect association and the modeled ozone concentrations. Using our proposed approach, we quantify the expected change in ozone-related summertime mortality in the contiguous United States between 2000 and 2050 under a changing climate. The mortality estimates show regional patterns in the expected degree of impact. We also illustrate the results when using a common technique in previous work that averages ozone to reduce the size of the data, and contrast these findings with our own. Our analysis yields more realistic inferences, providing clearer interpretation for decision making regarding the impacts of climate change. © 2015, The International Biometric Society.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28428539','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28428539"><span>Separating decadal global water cycle variability from sea level rise.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hamlington, B D; Reager, J T; Lo, M-H; Karnauskas, K B; Leben, R R</p> <p>2017-04-20</p> <p>Under a warming climate, amplification of the water cycle and changes in precipitation patterns over land are expected to occur, subsequently impacting the terrestrial water balance. On global scales, such changes in terrestrial water storage (TWS) will be reflected in the water contained in the ocean and can manifest as global sea level variations. Naturally occurring climate-driven TWS variability can temporarily obscure the long-term trend in sea level rise, in addition to modulating the impacts of sea level rise through natural periodic undulation in regional and global sea level. The internal variability of the global water cycle, therefore, confounds both the detection and attribution of sea level rise. Here, we use a suite of observations to quantify and map the contribution of TWS variability to sea level variability on decadal timescales. In particular, we find that decadal sea level variability centered in the Pacific Ocean is closely tied to low frequency variability of TWS in key areas across the globe. The unambiguous identification and clean separation of this component of variability is the missing step in uncovering the anthropogenic trend in sea level and understanding the potential for low-frequency modulation of future TWS impacts including flooding and drought.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B33J..01G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B33J..01G"><span>Global Land Product Validation Protocols: An Initiative of the CEOS Working Group on Calibration and Validation to Evaluate Satellite-derived Essential Climate Variables</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Guillevic, P. C.; Nickeson, J. E.; Roman, M. O.; camacho De Coca, F.; Wang, Z.; Schaepman-Strub, G.</p> <p>2016-12-01</p> <p>The Global Climate Observing System (GCOS) has specified the need to systematically produce and validate Essential Climate Variables (ECVs). The Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) and in particular its subgroup on Land Product Validation (LPV) is playing a key coordination role leveraging the international expertise required to address actions related to the validation of global land ECVs. The primary objective of the LPV subgroup is to set standards for validation methods and reporting in order to provide traceable and reliable uncertainty estimates for scientists and stakeholders. The Subgroup is comprised of 9 focus areas that encompass 10 land surface variables. The activities of each focus area are coordinated by two international co-leads and currently include leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR), vegetation phenology, surface albedo, fire disturbance, snow cover, land cover and land use change, soil moisture, land surface temperature (LST) and emissivity. Recent additions to the focus areas include vegetation indices and biomass. The development of best practice validation protocols is a core activity of CEOS LPV with the objective to standardize the evaluation of land surface products. LPV has identified four validation levels corresponding to increasing spatial and temporal representativeness of reference samples used to perform validation. Best practice validation protocols (1) provide the definition of variables, ancillary information and uncertainty metrics, (2) describe available data sources and methods to establish reference validation datasets with SI traceability, and (3) describe evaluation methods and reporting. An overview on validation best practice components will be presented based on the LAI and LST protocol efforts to date.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPA43B2227H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPA43B2227H"><span>Allocation of a global carbon budget consistent with the future emergence of regional climate signals</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Harrington, L. J.; Frame, D. J.</p> <p>2016-12-01</p> <p>Understanding how the signal of anthropogenic climate warming emerges from the noise of internal variability is of crucial societal importance. An emerging body of evidence suggests there are substantive disparities between those countries which are expected to experience the most rapid emergence of climate change, and those countries which are responsible for the majority of cumulative CO2 emissions to date. Here, we demonstrate how a global carbon budget for keeping global warming below a specified threshold could be distributed at a national level, if those countries which experience the emergence of regional climate signals most rapidly were able to emit proportionally greater amounts of CO2 per capita. The potential implications and limitations of this approach are also discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1512041M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1512041M"><span>VALUE - Validating and Integrating Downscaling Methods for Climate Change Research</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maraun, Douglas; Widmann, Martin; Benestad, Rasmus; Kotlarski, Sven; Huth, Radan; Hertig, Elke; Wibig, Joanna; Gutierrez, Jose</p> <p>2013-04-01</p> <p>Our understanding of global climate change is mainly based on General Circulation Models (GCMs) with a relatively coarse resolution. Since climate change impacts are mainly experienced on regional scales, high-resolution climate change scenarios need to be derived from GCM simulations by downscaling. Several projects have been carried out over the last years to validate the performance of statistical and dynamical downscaling, yet several aspects have not been systematically addressed: variability on sub-daily, decadal and longer time-scales, extreme events, spatial variability and inter-variable relationships. Different downscaling approaches such as dynamical downscaling, statistical downscaling and bias correction approaches have not been systematically compared. Furthermore, collaboration between different communities, in particular regional climate modellers, statistical downscalers and statisticians has been limited. To address these gaps, the EU Cooperation in Science and Technology (COST) action VALUE (www.value-cost.eu) has been brought into life. VALUE is a research network with participants from currently 23 European countries running from 2012 to 2015. Its main aim is to systematically validate and develop downscaling methods for climate change research in order to improve regional climate change scenarios for use in climate impact studies. Inspired by the co-design idea of the international research initiative "future earth", stakeholders of climate change information have been involved in the definition of research questions to be addressed and are actively participating in the network. The key idea of VALUE is to identify the relevant weather and climate characteristics required as input for a wide range of impact models and to define an open framework to systematically validate these characteristics. Based on a range of benchmark data sets, in principle every downscaling method can be validated and compared with competing methods. The results of this exercise will directly provide end users with important information about the uncertainty of regional climate scenarios, and will furthermore provide the basis for further developing downscaling methods. This presentation will provide background information on VALUE and discuss the identified characteristics and the validation framework.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..12.3406R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..12.3406R"><span>Climate change hampers endangered species through intensified moisture-related plant stresses</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>(Ruud) Bartholomeus, R. P.; (Flip) Witte, J. P. M.; (Peter) van Bodegom, P. M.; (Jos) van Dam, J. C.; (Rien) Aerts, R.</p> <p>2010-05-01</p> <p>With recent climate change, extremes in meteorological conditions are forecast and observed to increase globally, and to affect vegetation composition. More prolonged dry periods will alternate with more intensive rainfall events, both within and between years, which will change soil moisture dynamics. In temperate climates, soil moisture, in concert with nutrient availability and soil acidity, is the most important environmental filter in determining local plant species composition, as it determines the availability of both oxygen and water to plant roots. These resources are indispensable for meeting the physiological demands of plants. The consequences of climate change for our natural environment are among the most pressing issues of our time. The international research community is beginning to realise that climate extremes may be more powerful drivers of vegetation change and species extinctions than slow-and-steady climatic changes, but the causal mechanisms of such changes are presently unknown. The roles of amplitudes in water availability as drivers of vegetation change have been particularly elusive owing to the lack of integration of the key variables involved. Here we show that the combined effect of increased rainfall variability, temperature and atmospheric CO2-concentration will lead to an increased variability in both wet and dry extremes in stresses faced by plants (oxygen and water stress, respectively). We simulated these plant stresses with a novel, process-based approach, incorporating in detail the interacting processes in the soil-plant-atmosphere interface. In order to quantify oxygen and water stress with causal measures, we focused on interacting meteorological, soil physical, microbial, and plant physiological processes in the soil-plant-atmosphere system. The first physiological process inhibited at high soil moisture contents is plant root respiration, i.e. oxygen consumption in the roots, which responds to increased temperatures. High soil moisture contents hamper oxygen transport from the atmosphere, through the soil - where part of the oxygen additionally disappears by soil microbial oxygen consumption - and to the root cells. Reduced respiration negatively affects the energy supply to plant metabolism. Plant transpiration, which responds to increased temperatures and atmospheric CO2-concentrations, is the first physiological process that will be inhibited by low soil moisture contents, negatively affecting both photosynthesis and cooling. As both the supply and demand of oxygen and water depend strongly on the prevailing meteorological conditions, both oxygen and water stress were calculated dynamically in time to capture climate change effects. We demonstrate that increased rainfall variability in interaction with predicted changes in temperature and CO2, affects soil moisture conditions and plant oxygen and water demands such, that both oxygen stress and water stress will intensify due to climate change. Moreover, these stresses will increasingly coincide, causing variable stress conditions. These variable stress conditions were found to decrease future habitat suitability, especially for plant species that are presently endangered. The future existence of such species is thus at risk by climate change, which has direct implications for policies to maintain endangered species, as applied by international nature management organisations (e.g. IUCN). Our integrated mechanistic analysis of two stresses combined, which has never been done so far, reveals large impacts of climate change on species extinctions and thereby on biodiversity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1910281K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1910281K"><span>The Roles of Climate Change and El Niño in the Record Low Rainfall in October 2015 in Tasmania, Australia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Karoly, David; Black, Mitchell; Grose, Michael; King, Andrew</p> <p>2017-04-01</p> <p>The island state of Tasmania, in southeast Australia, received record low average rainfall of 21 mm in October 2015, 17% of the 1961-90 normal. This had major impacts across the state, affecting agriculture and hydroelectric power generation and preconditioning the landscape for major bushfires the following summer. Rainfall in Tasmania is normally high throughout the year, with variations in Austral spring associated with mean sea level pressure (MSLP) and circulation variations due to El Niño, the Indian Ocean dipole (IOD), and the southern annular mode (SAM). Spring rainfall is declining and projected to decrease further in Tasmania We have investigated the roles of anthropogenic climate change, the 2015/16 El Niño, and internal atmospheric variability on this record low October rainfall using observational data, regional climate simulations driven by specified sea surface temperatures (SSTs) from the weather@home Australia and New Zealand (w@h ANZ) project, and coupled climate model simulations from the Coupled Model Intercomparison Project phase 5. Anthropogenic climate change and the strong El Niño in 2015 very likely increased the chances of breaking the previous record low rainfall in 1965. In terms of contributions to the magnitude of this rainfall deficit, internal atmospheric variability as indicated by the Pacific-South American MSLP pattern was likely the main contributor, with El Niño next and a smaller but significant contribution from anthropogenic climate change. In this case, it was the MSLP and circulation changes associated with anthropogenic climate change in the Southern Hemisphere middle and high latitudes and not the thermodynamic effects of anthropogenic climate change that contributed to this event. Karoly, D. J., M.T. Black, M.R. Grose and A. D. King (2016) The roles of climate change and El Niño in the record low rainfall in October 2015 in Tasmania, Australia [in "Explaining Extremes of 2015 from a Climate Perspective"]. Bull. Am. Met. Soc., 97, S127-S130.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.9787B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.9787B"><span>From the Last Interglacial to the Anthropocene: Modelling a Complete Glacial Cycle (PalMod)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brücher, Tim; Latif, Mojib</p> <p>2017-04-01</p> <p>We will give a short overview and update on the current status of the national climate modelling initiative PalMod (Paleo Modelling, www.palmod.de). PalMod focuses on the understanding of the climate system dynamics and its variability during the last glacial cycle. The initiative is funded by the German Federal Ministry of Education and Research (BMBF) and its specific topics are: (i) to identify and quantify the relative contributions of the fundamental processes which determined the Earth's climate trajectory and variability during the last glacial cycle, (ii) to simulate with comprehensive Earth System Models (ESMs) the climate from the peak of the last interglacial - the Eemian warm period - up to the present, including the changes in the spectrum of variability, and (iii) to assess possible future climate trajectories beyond this century during the next millennia with sophisticated ESMs tested in such a way. The research is intended to be conducted over a period of 10 years, but with shorter funding cycles. PalMod kicked off in February 2016. The first phase focuses on the last deglaciation (app. the last 23.000 years). From the ESM perspective PalMod pushes forward model development by coupling ESM with dynamical ice sheet models. Computer scientists work on speeding up climate models using different concepts (like parallelisation in time) and one working group is dedicated to perform a comprehensive data synthesis to validate model performance. The envisioned approach is innovative in three respects. First, the consortium aims at simulating a full glacial cycle in transient mode and with comprehensive ESMs which allow full interactions between the physical and biogeochemical components of the Earth system, including ice sheets. Second, we shall address climate variability during the last glacial cycle on a large range of time scales, from interannual to multi-millennial, and attempt to quantify the relative contributions of external forcing and processes internal to the Earth system to climate variability at different time scales. Third, in order to achieve a higher level of understanding of natural climate variability at time scales of millennia, its governing processes and implications for the future climate, we bring together three different research communities: the Earth system modeling community, the proxy data community and the computational science community. The consortium consists of 18 partners including all major modelling centers within Germany. The funding comprises approximately 65 PostDoc positions and more than 120 scientists are involved. PalMod is coordinated at the Helmholtz Centre for Ocean Research Kiel (GEOMAR).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18441780','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18441780"><span>CO2 embodied in international trade with implications for global climate policy.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Peters, Glen P; Hertwich, Edgar G</p> <p>2008-03-01</p> <p>The flow of pollution through international trade flows has the ability to undermine environmental policies, particularly for global pollutants. In this article we determine the CO2 emissions embodied in international trade among 87 countries for the year 2001. We find that globally there are over 5.3 Gt of CO2 embodied in trade and that Annex B countries are net importers of CO2 emissions. Depending on country characteristics--such as size variables and geographic location--there are considerable variations in the embodied emissions. We argue that emissions embodied in trade may have a significant impact on participation in and effectiveness of global climate policies such as the Kyoto Protocol. We discuss several policy options to reduce the impact of trade in global climate policy. If countries take binding commitments as a part of a coalition, instead of as individual countries, then the impacts of trade can be substantially reduced. Adjusting emission inventories for trade gives a more consistent description of a country's environmental pressures and circumvents many trade related issues. It also gives opportunities to exploit trade as a means of mitigating emissions. Not least, a better understanding of the role that trade plays in a country's economic and environmental development will help design more effective and participatory climate policy post-Kyoto.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20713736','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20713736"><span>Accelerated warming of the Southern Ocean and its impacts on the hydrological cycle and sea ice.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Liu, Jiping; Curry, Judith A</p> <p>2010-08-24</p> <p>The observed sea surface temperature in the Southern Ocean shows a substantial warming trend for the second half of the 20th century. Associated with the warming, there has been an enhanced atmospheric hydrological cycle in the Southern Ocean that results in an increase of the Antarctic sea ice for the past three decades through the reduced upward ocean heat transport and increased snowfall. The simulated sea surface temperature variability from two global coupled climate models for the second half of the 20th century is dominated by natural internal variability associated with the Antarctic Oscillation, suggesting that the models' internal variability is too strong, leading to a response to anthropogenic forcing that is too weak. With increased loading of greenhouse gases in the atmosphere through the 21st century, the models show an accelerated warming in the Southern Ocean, and indicate that anthropogenic forcing exceeds natural internal variability. The increased heating from below (ocean) and above (atmosphere) and increased liquid precipitation associated with the enhanced hydrological cycle results in a projected decline of the Antarctic sea ice.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.U24A..09T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.U24A..09T"><span>Science and Strategic - Climate Implications</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tindall, J. A.; Moran, E. H.</p> <p>2008-12-01</p> <p>Energy of weather systems greatly exceeds energy produced and used by humans. Variation in this energy causes climate variability potentially resulting in local, national, and/or global catastrophes beyond our ability to deter the loss of life and economic destabilization. Large scale natural disasters routinely result in shortages of water, disruption of energy supplies, and destruction of infrastructure. The resulting unforeseen and disastrous events occurring beyond national emergency preparation, as related to climate variability, could insight civil unrest due to dwindling and/or inaccessible resources necessary for survival. Lack of these necessary resources in impacted countries often leads to wars. Climate change coupled with population growth, which exposes more of the population to potential risks associated with climate and environmental change, demands faster technological response. Understanding climate/associated environmental changes, the relation to human activity and behavior, and including this in national and international emergency/security management plans would alleviate shortcomings in our present and future technological status. The scale of environmental change will determine the potential magnitude of civil unrest at the local, national, and/or global level along with security issues at each level. Commonly, security issues related to possible civil unrest owing to temporal environmental change is not part of a short and/or long-term strategy, yet recent large-scale disasters are reminders that system failures (as in hurricane Katrina) include acknowledged breaches to individual, community, and infrastructure security. Without advance planning and management concerning environmental change, oncoming and climate related events will intensify the level of devastation and human catastrophe. Depending upon the magnitude and period of catastrophic events and/or environmental changes, destabilization of agricultural systems, energy supplies, and other lines of commodities often results in severely unbalanced supply and demand ratios, which eventually affect the entire global community. National economies potentially risk destabilization, which is especially important since economics plays a major role in strategic planning. This presentation will address these issues and the role that science can play in human sustainability and local, national, and international security.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC41F..01B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC41F..01B"><span>The Grand Challenges of WCRP and the Climate Observing System of the Future</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brasseur, G. P.</p> <p>2017-12-01</p> <p>The successful implementation the Paris agreement on climate change (COP21) calls for a well-designed global monitoring system of essential climate variables, climate processes and Earth system budgets. The Grand Challenges implemented by the World Climate Research Programme (WCRP) provide an opportunity to investigate issues of high societal relevance, directly related to sea level rise, droughts, floods, extreme heat events, food security, and fresh water availability. These challenges would directly benefit from a well-designed suite of systematic climate observations. Quantification of the evolution of the global energy, water and carbon budgets as well as the development and the production of near-term and regional climate predictions require that a comprehensive, focused, multi-platform observing system (satellites, ground-based and in situ observations) be established in an international context. This system must be accompanied by the development of climate services that should translate and disseminate scientific outcomes as actionable information for users and stakeholders.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H21F1436K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H21F1436K"><span>Relative controls of external and internal variability on time-variable transit time distributions, and the importance of StorAge Selection function approaches</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kim, M.; Pangle, L. A.; Cardoso, C.; Lora, M.; Meira, A.; Volkmann, T. H. M.; Wang, Y.; Harman, C. J.; Troch, P. A. A.</p> <p>2015-12-01</p> <p>Transit time distributions (TTDs) are an efficient way of characterizing complex transport dynamics of a hydrologic system. Time-invariant TTD has been studied extensively, but TTDs are time-varying under unsteady hydrologic systems due to both external variability (e.g., time-variability in fluxes), and internal variability (e.g., time-varying flow pathways). The use of "flow-weighted time" has been suggested to account for the effect of external variability on TTDs, but neglects the role of internal variability. Recently, to account both types of variability, StorAge Selection (SAS) function approaches were developed. One of these approaches enables the transport characteristics of a system - how the different aged water in the storage is sampled by the outflow - to be parameterized by time-variable probability distribution called the rank SAS (rSAS) function, and uses it directly to determine the time-variable TTDs resulting from a given timeseries of fluxes in and out of a system. Unlike TTDs, the form of the rSAS function varies only due to changes in flow pathways, but is not affected by the timing of fluxes alone. However, the relation between physical mechanisms and the time-varying rSAS functions are not well understood. In this study, relative effects of internal and external variability on the TTDs are examined using observations from a homogeneously packed 1 m3 sloping soil lysimeter. The observations suggest the importance of internal variability on TTDs, and reinforce the need to account for this variability using time-variable rSAS functions. Furthermore, the relative usefulness of two other formulations of SAS functions and the mortality rate (which plays a similar role to SAS functions in the McKendrick-von Foerster model of age-structured population dynamics) are also discussed. Finally, numerical modeling is used to explore the role of internal and external variability for hydrologic systems with diverse geomorphic and climate characteristics. This works will give an insight that which approach (or SAS function) is preferable under different conditions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1615680L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1615680L"><span>Global Framework for Climate Services (GFCS): status of implementation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lucio, Filipe</p> <p>2014-05-01</p> <p>The GFCS is a global partnership of governments and UN and international agencies that produce and use climate information and services. WMO, which is leading the initiative in collaboration with UN ISDR, WHO, WFP, FAO, UNESCO, UNDP and other UN and international partners are pooling their expertise and resources in order to co-design and co-produce knowledge, information and services to support effective decision making in response to climate variability and change in four priority areas (agriculture and fod security, water, health and disaster risk reduction). To address the entire value chain for the effective production and application of climate services the GFCS main components or pillars are being implemented, namely: • User Interface Platform — to provide ways for climate service users and providers to interact to identify needs and capacities and improve the effectiveness of the Framework and its climate services; • Climate Services Information System — to produce and distribute climate data, products and information according to the needs of users and to agreed standards; • Observations and Monitoring - to generate the necessary data for climate services according to agreed standards; • Research, Modelling and Prediction — to harness science capabilities and results and develop appropriate tools to meet the needs of climate services; • Capacity Building — to support the systematic development of the institutions, infrastructure and human resources needed for effective climate services. Activities are being implemented in various countries in Africa, the Caribbean and South pacific Islands. This paper will provide details on the status of implementation of the GFCS worldwider.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011ClDy...37.1293P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011ClDy...37.1293P"><span>Diagnosing GCM errors over West Africa using relaxation experiments. Part I: summer monsoon climatology and interannual variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pohl, Benjamin; Douville, Hervé</p> <p>2011-10-01</p> <p>The CNRM atmospheric general circulation model Arpege-Climat is relaxed towards atmospheric reanalyses outside the 10°S-32°N 30°W-50°E domain in order to disentangle the regional versus large-scale sources of climatological biases and interannual variability of the West African monsoon (WAM). On the one hand, the main climatological features of the monsoon, including the spatial distribution of summer precipitation, are only weakly improved by the nudging, thereby suggesting the regional origin of the Arpege-Climat biases. On the other hand, the nudging technique is relatively efficient to control the interannual variability of the WAM dynamics, though the impact on rainfall variability is less clear. Additional sensitivity experiments focusing on the strong 1994 summer monsoon suggest that the weak sensitivity of the model biases is not an artifact of the nudging design, but the evidence that regional physical processes are the main limiting factors for a realistic simulation of monsoon circulation and precipitation in the Arpege-Climat model. Sensitivity experiments to soil moisture boundary conditions are also conducted and highlight the relevance of land-atmosphere coupling for the amplification of precipitation biases. Nevertheless, the land surface hydrology is not the main explanation for the model errors that are rather due to deficiencies in the atmospheric physics. The intraseasonal timescale and the model internal variability are discussed in a companion paper.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014APS..MARG40005C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014APS..MARG40005C"><span>Causes and implications of the growing divergence between climate model simulations and observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Curry, Judith</p> <p>2014-03-01</p> <p>For the past 15+ years, there has been no increase in global average surface temperature, which has been referred to as a 'hiatus' in global warming. By contrast, estimates of expected warming in the first several decades of 21st century made by the IPCC AR4 were 0.2C/decade. This talk summarizes the recent CMIP5 climate model simulation results and comparisons with observational data. The most recent climate model simulations used in the AR5 indicate that the warming stagnation since 1998 is no longer consistent with model projections even at the 2% confidence level. Potential causes for the model-observation discrepancies are discussed. A particular focus of the talk is the role of multi-decadal natural internal variability on the climate variability of the 20th and early 21st centuries. The ``stadium wave'' climate signal is described, which propagates across the Northern Hemisphere through a network of ocean, ice, and atmospheric circulation regimes that self-organize into a collective tempo. The stadium wave hypothesis provides a plausible explanation for the hiatus in warming and helps explain why climate models did not predict this hiatus. Further, the new hypothesis suggests how long the hiatus might last. Implications of the hiatus are discussed in context of climate model sensitivity to CO2 forcing and attribution of the warming that was observed in the last quarter of the 20th century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.H53C0939Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.H53C0939Y"><span>Climate and Cryosphere (CliC) Project and its Interest in Arctic Hydrology Research</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, D.; Prowse, T. D.; Steffen, K.; Ryabinin, V.</p> <p>2009-12-01</p> <p>The cryosphere is an important and dynamic component of the global climate system. The global cryosphere is changing rapidly, with changes in the Polar Regions receiving particular attention during the International Polar Year 2007-2008. The Climate and Cryosphere (CliC) Project is a core project of the World Climate Research Programme (WCRP) and is co-sponsored by WCRP, SCAR (Scientific Committee for Antarctic Research) and IASC (International Committee for Antarctic Research). The principal goal of CliC is to assess and quantify the impacts that climatic variability and change have on components of the cryosphere and the consequences of these impacts for the climate system. To achieve its objectives, CliC coordinates international and regional projects, partners with other organizations in joint initiatives, and organizes panels and working groups to lead and coordinate advanced research aimed at closing identified gaps in scientific knowledge about climate and cryosphere. The terrestrial cryosphere includes land areas where snow cover, lake- and river-ice, glaciers and ice caps, permafrost and seasonally frozen ground and solid precipitation occur. The main task of this theme is to improve estimates and quantify the uncertainty of water balance and related energy flux components in cold climate regions. This includes precipitation (both solid and liquid) distribution, properties of snow, snow melt, evapotranspiration, sublimation, water movement through frozen and unfrozen ground, water storage in watersheds, river- and lake-ice properties and processes, and river runoff. The focus of this theme includes two specific issues: the role of permafrost and frozen ground in the carbon balance, and precipitation in cold climates. Hydrological studies of cold regions will provide a key contribution to the new theme crosscut, which focuses on the cryospheric input to the freshwater balance of the Arctic. This presentation will provide an overview and update of recent developments of cold region hydrometeorology research activities and future challenges in arctic hydrology and climate change investigations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JAMES...9.1595P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JAMES...9.1595P"><span>An advanced stochastic weather generator for simulating 2-D high-resolution climate variables</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo</p> <p>2017-07-01</p> <p>A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H24D..01H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H24D..01H"><span>Internal versus external controls on age variability: Definitions, origins and implications in a changing climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Helton, A. M.; Poole, G. C.; Payn, R. A.; Izurieta, C.; Wright, M.; Bernhardt, E. S.; Stanford, J. A.</p> <p>2014-12-01</p> <p>The unsteadiness of stream water age is now well established, but the controls on the age dynamics, and the adequate representation and prediction of those dynamics, are not. A basic distinction can be made between internal variability that arises from changes in the proportions of flow moving through the diverse flow pathways of a hydrologic system, and external variability that arises from the stochasticity of inputs and outputs (such as precipitation and streamflow). In this talk I will show how these two types of age variability can be formally defined and distinguished within the framework of rank StorAge Selection (rSAS) functions. Internal variability implies variations in time in the rSAS function, while external variability does not. This leads naturally to the definition of several modes of internal variability, reflecting generic ways that system flowpaths may be rearranged. This rearrangement may be induced by fluctuations in the system state (such as catchment wetness), or by longer-term changes in catchment structure (such as land use change). One type of change, the 'inverse storage effect' is characterized by an increase in the release of young water from the system in response to an increase in overall system storage. This effect can be seen in many hydrologic settings, and has important implications for the effect of altered hydroclimatic conditions on solute transport through a landscape. External variability, such as increased precipitation, can induce a decrease in mean transit time (and vice versa), but this effect is greatly enhanced if accompanied by an internal shift in flow pathways that increases the relative importance of younger water. These effects will be illustrated using data from field and experimental studies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H24D..01H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H24D..01H"><span>Internal versus external controls on age variability: Definitions, origins and implications in a changing climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Harman, C. J.</p> <p>2015-12-01</p> <p>The unsteadiness of stream water age is now well established, but the controls on the age dynamics, and the adequate representation and prediction of those dynamics, are not. A basic distinction can be made between internal variability that arises from changes in the proportions of flow moving through the diverse flow pathways of a hydrologic system, and external variability that arises from the stochasticity of inputs and outputs (such as precipitation and streamflow). In this talk I will show how these two types of age variability can be formally defined and distinguished within the framework of rank StorAge Selection (rSAS) functions. Internal variability implies variations in time in the rSAS function, while external variability does not. This leads naturally to the definition of several modes of internal variability, reflecting generic ways that system flowpaths may be rearranged. This rearrangement may be induced by fluctuations in the system state (such as catchment wetness), or by longer-term changes in catchment structure (such as land use change). One type of change, the 'inverse storage effect' is characterized by an increase in the release of young water from the system in response to an increase in overall system storage. This effect can be seen in many hydrologic settings, and has important implications for the effect of altered hydroclimatic conditions on solute transport through a landscape. External variability, such as increased precipitation, can induce a decrease in mean transit time (and vice versa), but this effect is greatly enhanced if accompanied by an internal shift in flow pathways that increases the relative importance of younger water. These effects will be illustrated using data from field and experimental studies.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19860021711','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19860021711"><span>Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hoffert, M. I.</p> <p>1986-01-01</p> <p>Terrestrial climatic effects associated with solar variability have been proposed for at least a century, but could not be assessed quantitatively owing to observational uncertainities in solar flux variations. Measurements from 1980 to 1984 by the Active Cavity Radiometer Irradiance Monitor (ACRIM), capable of resolving fluctuations above the sensible atmosphere less than 0.1% of the solar constant, permit direct albeit preliminary assessments of solar forcing effects on global temperatures during this period. The global temperature response to ACRIM-measured fluctuations was computed from 1980 to 1985 using the NYU transient climate model including thermal inertia effects of the world ocean; and compared the results with observations of recent temperature trends. Monthly mean ACRIM-driven global surface temperature fluctuations computed with the climate model are an order of magnitude smaller, of order 0.01 C. In constrast, global mean surface temperature observations indicate an approx. 0.1 C increase during this period. Solar variability is therefore likely to have been a minor factor in global climate change during this period compared with variations in atmospheric albedo, greenhouse gases and internal self-inducedoscillations. It was not possible to extend the applicability of the measured flux variations to longer periods since a possible correlation of luminosity with solar annual activity is not supported by statistical analysis. The continuous monitoring of solar flux by satellite-based instruments over timescales of 20 years or more comparable to timescales for thermal relaxation of the oceans and of the solar cycle itself is needed to resolve the question of long-term solar variation effects on climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H14F..05V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H14F..05V"><span>Perspectives on Hydro-Climatic Change in Rivers Sourced From the Khangai Mountains, Mongolia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Venable, N. B.; Fassnacht, S. R.; Tumenjargal, S.; Batbuyan, B.; Odgarav, J.; Sukhbataar, J.; Fernandez-Gimenez, M.; Adyabadam, G.</p> <p>2012-12-01</p> <p>Patterns of pastoralism have shaped the Mongolian countryside throughout history. These patterns are largely dictated by seasonal and extreme climate and water conditions. While change has always been a part of the traditional herder lifestyle, the magnitude and variety of impacts imposed by natural and human-induced changes in the last few decades has increased, negatively affecting the coupled natural-human systems of Mongolia. Regional hydrologic impacts from increased mining, irrigation, urbanization, and climate change are challenging to measure and model due to sparse and relatively short meteorological and hydrological records. Characterization of the variability inherent in Mongolian hydrological systems in the international literature remains limited. To quantify recent changes to these systems, several river basins near the Khangai Mountains were analyzed. These basins adjoin and include community-based managed and non-managed grazing lands under study as part of an ongoing National Science Foundation Coupled Natural and Human Systems (NSF-CNH) project. Statistically significant increasing temperatures and decreasing streamflows in the study areas support herder's perceptions of hydro-climatic changes and variability. The results of basin characterization combined with water balance modeling and trend analyses illustrate the future potential for further change in these hydro-climatic systems. Alternate land-uses and herder lifestyle modifications may amplify impacts from climatic change. Recent fieldwork also revealed complex surface-groundwater interactions in some areas that may affect model outcomes. Future explorations of longer-term variability through the use of proxies and the development of hydrologic scenarios will place the current basin analyses in context to more fully assess possible impacts to the hydrologic-human systems of Mongolia.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008ClDy...30..113D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008ClDy...30..113D"><span>Evaluation of uncertainties in the CRCM-simulated North American climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>de Elía, Ramón; Caya, Daniel; Côté, Hélène; Frigon, Anne; Biner, Sébastien; Giguère, Michel; Paquin, Dominique; Harvey, Richard; Plummer, David</p> <p>2008-02-01</p> <p>This work is a first step in the analysis of uncertainty sources in the RCM-simulated climate over North America. Three main sets of sensitivity studies were carried out: the first estimates the magnitude of internal variability, which is needed to evaluate the significance of changes in the simulated climate induced by any model modification. The second is devoted to the role of CRCM configuration as a source of uncertainty, in particular the sensitivity to nesting technique, domain size, and driving reanalysis. The third study aims to assess the relative importance of the previously estimated sensitivities by performing two additional sensitivity experiments: one, in which the reanalysis driving data is replaced by data generated by the second generation Coupled Global Climate Model (CGCM2), and another, in which a different CRCM version is used. Results show that the internal variability, triggered by differences in initial conditions, is much smaller than the sensitivity to any other source. Results also show that levels of uncertainty originating from liberty of choices in the definition of configuration parameters are comparable among themselves and are smaller than those due to the choice of CGCM or CRCM version used. These results suggest that uncertainty originated by the CRCM configuration latitude (freedom of choice among domain sizes, nesting techniques and reanalysis dataset), although important, does not seem to be a major obstacle to climate downscaling. Finally, with the aim of evaluating the combined effect of the different uncertainties, the ensemble spread is estimated for a subset of the analysed simulations. Results show that downscaled surface temperature is in general more uncertain in the northern regions, while precipitation is more uncertain in the central and eastern US.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A21F0212H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A21F0212H"><span>Is "Warm Arctic, Cold Continent" A Fingerprint Pattern of Climate Change?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hoerling, M. P.; Sun, L.; Perlwitz, J.</p> <p>2015-12-01</p> <p>Cold winters and cold waves have recently occurred in Europe, central Asia and the Midwest to eastern United States, even as global mean temperatures set record highs and Arctic amplification of surface warming continued. Since 1979, Central Asia winter temperatures have in fact declined. Conjecture has it that more cold extremes over the mid-latitude continents should occur due to global warming and the impacts of Arctic sea ice loss. A Northern Hemisphere temperature signal termed the "Warm Arctic, Cold Continent" pattern has thus been surmised. Here we use a multi-model approach to test the hypothesis that such a pattern is indeed symptomatic of climate change. Diagnosis of a large model ensemble of historical climate simulations shows some individual realizations to yield cooling trends over Central Asia, but importantly the vast majority show warming. The observed cooling has thus likely been a low probability state of internal variability, not a fingerprint of forced climate change. We show that daily temperature variations over continents decline in winter due to global warming, and cold waves become less likely. This is partly related to diminution of Arctic cold air reservoirs due to warming-induced sea ice loss. Nonetheless, we find some evidence and present a physical basis that Arctic sea ice loss alone can induce a winter cooling over Central Asia, though with a magnitude that is appreciably smaller than the overall radiative-forced warming signal. Our results support the argument that recent cooling trends over central Asia, and cold extreme events over the winter continents, have principally resulted from atmospheric internal variability and have been neither a forced response to Arctic seas ice loss nor a symptom of global warming. The paradigm of climate change is thus better expressed as "Warm Arctic, Warm Continent" for the NH winter.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010111482','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010111482"><span>Constraints on Variability of Brightness and Surface Magnetism on Time Scales of Decades to Centuries in the Sun and Sun-Like Stars: A Source of Potential Terrestrial Climate Variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Baliunas, Sallie L.; Sharber, James (Technical Monitor)</p> <p>2001-01-01</p> <p>These four points summarize our work to date. (1) Conciliation of solar and stellar photometric variability. Previous research by us and colleagues suggested that the Sun might at present be showing unusually low photometric variability compared to other sun-like stars. Those early results would question the suitability of the technique of using sun-like stars as proxies for solar irradiance change on time scales of decades to centuries. However, our results indicate the contrary: the Sun's observed short-term (seasonal) and longterm (year-to-year) brightness variations closely agree with observed brightness variations in stars of similar mass and age. (2) We have demonstrated an inverse correlation between the global temperature of the terrestrial lower troposphere, inferred from the NASA Microwave Sounding Unit (MSU) radiometers, and the total area of the Sun covered by coronal holes from January 1979 to present (up to May 2000). Variable fluxes of either solar charged particles or cosmic rays, or both, may influence the terrestrial tropospheric temperature. The geographical pattern of the correlation is consistent with our interpretation of an extra-terrestrial charged particle forcing. (3) Possible climate mechanism amplifying the impact of solar ultraviolet irradiance variations. The key points of our proposed climate hypersensitivity mechanism are: (a) The Sun is more variable in the UV (ultraviolet) than in the visible. However, the increased UV irradiance is mainly absorbed in the lower stratosphere/upper troposphere rather than at the surface. (b) Absorption in the stratosphere raises the temperature moderately around the vicinity of the tropopause, and tends to stabilize the atmosphere against vertical convective/diffusive transport, thus decreasing the flux of heat and moisture carried upward from surface. (c) The decrease in the upward convection of heat and moisture tends to raise the surface temperature because a drier upper atmosphere becomes less cloudy, which in turn allows more solar radiation to reach the Earth's surface. (4) Natural variability in an ocean-atmosphere climate model. We use a 14-region, 6-layer, global thermo-hydrodynamic ocean-atmosphere model to study natural climate variability. All the numerical experiments were performed with no change in the prescribed external boundary conditions (except for the seasonal cycle of the Sun's tilt angle). Therefore, the observed inter-annual variability is of an internal kind. The model results are helpful toward the understanding of the role of nonlinearity in climate change. We have demonstrated a range of possible climate behaviors using our newly developed ocean-atmosphere model. These include climate configurations with no interannual variability, with multi-year periodicities, with continuous chaos, or with chaotically occuring transitions between two discrete substrates. These possible modes of climate behavior are all possible for the real climate, as well as the model. We have shown that small temporary climate influences can trigger shifts both in the mean climate, and among these different types of behavior. Such shifts are not only theoretically plausible, as shown here and elsewhere; they are omnipresent in the climate record on time scales from several years to the age of the Earth. This has two apparently opposite implications for the possibility of anthropogenic global warming. First, any warming which might occur as a result of human influence would be only a fraction of the small-to-large unpredictable natural changes and changes which result from other external causes. On the other hand, small temporary influences such as human influence do have the potential of causing large permanent shifts in mean climate and interannual variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19800023527','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19800023527"><span>On the dynamic forcing of short-term climate fluctuations by feedback mechanisms</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Reiter, E. R.</p> <p>1979-01-01</p> <p>Various internal feedback mechanisms in the ocean atmosphere system were studied. A variability pattern of sea surface temperature with a quasibiennial oscillation (QBO) was detected off the coast of Senegal, in the Gulf of Guinea and even in the Gulf Stream as it leaves the North American continental shelf. Possible physical connections between some of these QBO's were pointed out by a hypothetical feedback model. Interaction of a QBO with the annual cycle may lead to beating frequencies resembling climatic trends of a duration of several years.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC53A0503A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC53A0503A"><span>Climate Risk Management and Decision Support Tools for the Agriculture Sector in Lao PDR, Bangladesh, and Indonesia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Allis, E. C.; Greene, A. M.; Cousin, R.</p> <p>2014-12-01</p> <p>We describe a comprehensive project for developing climate information and decision support / climate risk management tools in Lao PDR, Bangladesh and Indonesia. Mechanisms are developed for bringing the benefits of these tools to both policy makers and poor rural farmers, with the goal of enabling better management, at the farm level, of the risks associated with climate variability and change. The project comprises several interwoven threads, differentially applied in the different study regions. These include data management and quality control, development of seasonal forecast capabilities, use of dynamic cropping calendars and climate advisories, the development of longer-term climate information for both past and future and a weather index insurance component. Stakeholder engagement and capacity building served as reinforcing and complementary elements to all components. In this talk we will provide a project overview, show how the various components fit together and describe some lessons learned in this attempt to promote the uptake of actionable climate information from farmer to policy level. The applied research project was led by the International Research Institute for Climate and Society (IRI) at Columbia University with funding from the International Fund for Agriculture Development (IFAD) and in close collaboration with our regional partners at the Centre for Climate Risk and Opportunity Management in Southeast Asia Pacific (at Bogor Agricultural University in Indonesia), Indonesia's National Agency for Meteorology, Climatology and Geophysics (BMKG), Lao PDR's National Agriculture and Forestry Research Institute (NAFRI), Laotian Department of Meteorology and Hydrology (DMH), WorldFish Center, Bangladesh Meteorology Department (BMD), and CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMNH52A..03R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMNH52A..03R"><span>Development of a Climate Prediction Market</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roulston, M. S.</p> <p>2017-12-01</p> <p>Winton, a global investment firm, is planning to establish a prediction market for climate. This prediction market will allow participants to place bets on global climate up to several decades in the future. Winton is pursuing this endeavour as part of its philanthropy that funds scientific research and the communication of scientific ideas. The Winton Climate Prediction Market will be based in the U.K. It will be structured as an online gambling site subject to the regulation of the Gambling Commission. Unlike existing betting sites, the Climate Prediction Market will be subsidized: a central market maker will inject money into the market. This is in contrast to traditional bookmakers or betting exchanges who set odds in their favour or charge commissions to make a profit. The philosophy of a subsidized prediction market is that the party seeking information should fund the market, rather than the participants who provide the information. The initial market will allow bets to be placed on the atmospheric concentration of carbon dioxide and the global mean temperature anomaly. It will thus produce implied forecasts of carbon dioxide concentration as well as global temperatures. If the initial market is successful, additional markets could be added which target other climate variables, such as regional temperatures or sea-level rise. These markets could be sponsored by organizations that are interested in predictions of the specific climate variables. An online platform for the Climate Prediction Market has been developed and has been tested internally at Winton.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ESD.....7..597R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ESD.....7..597R"><span>Comment on "Scaling regimes and linear/nonlinear responses of last millennium climate to volcanic and solar forcing" by S. Lovejoy and C. Varotsos (2016)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rypdal, Kristoffer; Rypdal, Martin</p> <p>2016-07-01</p> <p>Lovejoy and Varotsos (2016) (L&V) analyse the temperature response to solar, volcanic, and solar plus volcanic forcing in the Zebiak-Cane (ZC) model, and to solar and solar plus volcanic forcing in the Goddard Institute for Space Studies (GISS) E2-R model. By using a simple wavelet filtering technique they conclude that the responses in the ZC model combine subadditively on timescales from 50 to 1000 years. Nonlinear response on shorter timescales is claimed by analysis of intermittencies in the forcing and the temperature signal for both models. The analysis of additivity in the ZC model suffers from a confusing presentation of results based on an invalid approximation, and from ignoring the effect of internal variability. We present tests without this approximation which are not able to detect nonlinearity in the response, even without accounting for internal variability. We also demonstrate that internal variability will appear as subadditivity if it is not accounted for. L&V's analysis of intermittencies is based on a mathematical result stating that the intermittencies of forcing and response are the same if the response is linear. We argue that there are at least three different factors that may invalidate the application of this result for these data. It is valid only for a power-law response function; it assumes power-law scaling of structure functions of forcing as well as temperature signal; and the internal variability, which is strong at least on the short timescales, will exert an influence on temperature intermittence which is independent of the forcing. We demonstrate by a synthetic example that the differences in intermittencies observed by L&V easily can be accounted for by these effects under the assumption of a linear response. Our conclusion is that the analysis performed by L&V does not present valid evidence for a detectable nonlinear response in the global temperature in these climate models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1363911-detection-accelerated-sea-level-rise-imminent','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1363911-detection-accelerated-sea-level-rise-imminent"><span>Is the detection of accelerated sea level rise imminent?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Fasullo, J. T.; Nerem, R. S.; Hamlington, B.</p> <p>2016-08-10</p> <p>Global mean sea level rise estimated from satellite altimetry provides a strong constraint on climate variability and change and is expected to accelerate as the rates of both ocean warming and cryospheric mass loss increase over time. In stark contrast to this expectation however, current altimeter products show the rate of sea level rise to have decreased from the first to second decades of the altimeter era. Here, a combined analysis of altimeter data and specially designed climate model simulations shows the 1991 eruption of Mt Pinatubo to likely have masked the acceleration that would have otherwise occurred. This maskingmore » arose largely from a recovery in ocean heat content through the mid to late 1990 s subsequent to major heat content reductions in the years following the eruption. As a result, a consequence of this finding is that barring another major volcanic eruption, a detectable acceleration is likely to emerge from the noise of internal climate variability in the coming decade.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1363911','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1363911"><span>Is the detection of accelerated sea level rise imminent?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Fasullo, J. T.; Nerem, R. S.; Hamlington, B.</p> <p></p> <p>Global mean sea level rise estimated from satellite altimetry provides a strong constraint on climate variability and change and is expected to accelerate as the rates of both ocean warming and cryospheric mass loss increase over time. In stark contrast to this expectation however, current altimeter products show the rate of sea level rise to have decreased from the first to second decades of the altimeter era. Here, a combined analysis of altimeter data and specially designed climate model simulations shows the 1991 eruption of Mt Pinatubo to likely have masked the acceleration that would have otherwise occurred. This maskingmore » arose largely from a recovery in ocean heat content through the mid to late 1990 s subsequent to major heat content reductions in the years following the eruption. As a result, a consequence of this finding is that barring another major volcanic eruption, a detectable acceleration is likely to emerge from the noise of internal climate variability in the coming decade.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018E%26ES..140a2051N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018E%26ES..140a2051N"><span>Effects of Hydrological Parameters on Palm Oil Fresh Fruit Bunch Yield)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nda, M.; Adnan, M. S.; Suhadak, M. A.; Zakaria, M. S.; Lopa, R. T.</p> <p>2018-04-01</p> <p>Climate change effects and variability have been studied by many researchers in diverse geophysical fields. Malaysia produces large volume of palm oil, the effects of climate change on hydrological parameters (rainfall and precipitation) could have adverse effects on palm oil fresh fruit bunch (FFB) production with implications at both local and international market. It is important to understand the effects of climate change on crop yield to adopt new cultivation techniques and guaranteeing food security globally. Based on this background, the paper’s objective is to investigate the effects of rainfall and temperature pattern on crop yield (FFB) within five years period (2013 - 2017) at Batu Pahat District. The Man - Kendall rank technique (trend test) and statistical analyses (correlation and regression) were applied to the dataset used for the study. The results reveal that there are variabilities in rainfall and temperature from one month to the other and the statistical analysis reveals that the hydrological parameters have an insignificant effect on crop yield.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.8712D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.8712D"><span>Towards an integrated set of surface meterological observations for climate science and applications</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dunn, Robert; Thorne, Peter</p> <p>2017-04-01</p> <p>We cannot predict what is not observed, and we cannot analyse what is not archived. To meet current scientific and societal demands, as well as future requirements for climate services, it is vital that the management and curation of land-based meteorological data holdings is improved. A comprehensive global set of data holdings, of known provenance, integrated across both climate variable and timescale are required to meet the wide range of user needs. Presently, the land-based holdings are highly fractured into global, region and national holdings for different variables and timescales, from a variety of sources, and in a mixture of formats. We present a high level overview, based on broad community input, of the steps that are required to bring about this integration and progress towards such a database. Any long-term, international, program creating such an integrated database will transform the our collective ability to provide societally relevant research, analysis and predictions across the globe.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9241E..1RH','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9241E..1RH"><span>Collaboration pathway(s) using new tools for optimizing operational climate monitoring from space</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.</p> <p>2014-10-01</p> <p>Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the needs of decision makers, scientific investigators and global users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent (2014) rulebased decision engine modeling runs that targeted optimizing the intended NPOESS architecture, becomes a surrogate for global operational climate monitoring architecture(s). This rule-based systems tools provide valuable insight for Global climate architectures, through the comparison and evaluation of alternatives considered and the exhaustive range of trade space explored. A representative optimization of Global ECV's (essential climate variables) climate monitoring architecture(s) is explored and described in some detail with thoughts on appropriate rule-based valuations. The optimization tools(s) suggest and support global collaboration pathways and hopefully elicit responses from the audience and climate science shareholders.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1413219L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1413219L"><span>Do GCM's predict the climate.... Or the low frequency weather?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lovejoy, S.; Schertzer, D.; Varon, D.</p> <p>2012-04-01</p> <p>Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500 - 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT vary in power law manners ≈ Δt**H the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale (Δt). At longer scales Δt >τw (≈ 10 days) H changes sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime. In this regime, the spectrum is a relatively flat "plateau", it's variability is low, stable, corresponding to our usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, once again H>0, so that the variability increases with scale: the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, to define "climate states" as fluctuations at scale τc and then "climate change" as the fluctuations at longer periods (Δt>τc). We show that the intermediate low frequency weather regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched so that only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by stochastic cascade models of weather, but also by control runs (i.e. without climate forcing) of GCM based climate forecasting systems including those of the Institut Pierre Simon Laplace (Paris) and the Earth Forecasting System (Hamburg). In order for these systems to go beyond simply predicting low frequency weather i.e. in order for them to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. Using statistical scaling techniques we examine the scale dependence of fluctuations from forced and unforced GCM outputs, including from the ECHO-G and EFS simulations in the Millenium climate reconstruction project and compare this with data, multiproxies and paleo data. Our general conclusion is that the models systematically underestimate the multidecadal, multicentennial scale variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMGC32B..04B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC32B..04B"><span>An integrated, indicator framework for assessing large-scale variations and change in seasonal timing and phenology (Invited)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Betancourt, J. L.; Weltzin, J. F.</p> <p>2013-12-01</p> <p>As part of an effort to develop an Indicator System for the National Climate Assessment (NCA), the Seasonality and Phenology Indicators Technical Team (SPITT) proposed an integrated, continental-scale framework for understanding and tracking seasonal timing in physical and biological systems. The framework shares several metrics with the EPA's National Climate Change Indicators. The SPITT framework includes a comprehensive suite of national indicators to track conditions, anticipate vulnerabilities, and facilitate intervention or adaptation to the extent possible. Observed, modeled, and forecasted seasonal timing metrics can inform a wide spectrum of decisions on federal, state, and private lands in the U.S., and will be pivotal for international efforts to mitigation and adaptation. Humans use calendars both to understand the natural world and to plan their lives. Although the seasons are familiar concepts, we lack a comprehensive understanding of how variability arises in the timing of seasonal transitions in the atmosphere, and how variability and change translate and propagate through hydrological, ecological and human systems. For example, the contributions of greenhouse warming and natural variability to secular trends in seasonal timing are difficult to disentangle, including earlier spring transitions from winter (strong westerlies) to summer (weak easterlies) patterns of atmospheric circulation; shifts in annual phasing of daily temperature means and extremes; advanced timing of snow and ice melt and soil thaw at higher latitudes and elevations; and earlier start and longer duration of the growing and fire seasons. The SPITT framework aims to relate spatiotemporal variability in surface climate to (1) large-scale modes of natural climate variability and greenhouse gas-driven climatic change, and (2) spatiotemporal variability in hydrological, ecological and human responses and impacts. The hierarchical framework relies on ground and satellite observations, and includes metrics of surface climate seasonality, seasonality of snow and ice, land surface phenology, ecosystem disturbance seasonality, and organismal phenology. Recommended metrics met the following requirements: (a) easily measured by day-of-year, number of days, or in the case of species migrations, by the latitude of the observation on a given date; (b) are observed or can be calculated across a high density of locations in many different regions of the U.S.; and (c) unambiguously describe both spatial and temporal variability and trends in seasonal timing that are climatically driven. The SPITT framework is meant to provide climatic and strategic guidance for the growth and application of seasonal timing and phenological monitoring efforts. The hope is that additional national indicators based on observed phenology, or evidence-based algorithms calibrated with observational data, will evolve with sustained and broad-scale monitoring of climatically sensitive species and ecological processes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4354156','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4354156"><span>Climate variation explains a third of global crop yield variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.</p> <p>2015-01-01</p> <p>Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC52A..05C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC52A..05C"><span>Climate and Population Health Vulnerabilities to Vector-Borne Diseases: Increasing Resilience Under Climate Change Conditions in Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ceccato, P.; McDonald, K. C.; Podest, E.; De La Torre Juarez, M.; Kruczkiewicz, A.; Lessel, J.; Jensen, K.; Thomson, M. C.</p> <p>2014-12-01</p> <p>The International Research Institute for Climate and Society (IRI), the City University of New York (CUNY) and NASA Jet Propulsion Laboratory (JPL) in collaboration with NASA SERVIR are developing tools to monitor climate variables (precipitation, temperature, vegetation, water bodies, inundation) that help projects in Africa to increase resilience to climate change for vector-borne diseases (i.e. malaria, trypanosomiasis, leishmaniasis, and schistosomiasis). Through the development of new products to monitor precipitation, water bodies and inundation, IRI, CUNY and JPL provide tools and capacity building to research communities, ministries of health and World Health Organization in Africa to: 1) Develop research teams' ability to appropriately use climate data as part of their research 2) Enable research teams and ministries to integrate climate information into social and economic drivers of vulnerability and opportunities for adaptation to climate change 3) Inform better policies and programs for climate change adaptation. This oral presentation will demonstrate how IRI, CUNY, and JPL developed new products, tools and capacity building to achieve the three objectives mentioned above.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JGRD..123.3483M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JGRD..123.3483M"><span>Drought Persistence Errors in Global Climate Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moon, H.; Gudmundsson, L.; Seneviratne, S. I.</p> <p>2018-04-01</p> <p>The persistence of drought events largely determines the severity of socioeconomic and ecological impacts, but the capability of current global climate models (GCMs) to simulate such events is subject to large uncertainties. In this study, the representation of drought persistence in GCMs is assessed by comparing state-of-the-art GCM model simulations to observation-based data sets. For doing so, we consider dry-to-dry transition probabilities at monthly and annual scales as estimates for drought persistence, where a dry status is defined as negative precipitation anomaly. Though there is a substantial spread in the drought persistence bias, most of the simulations show systematic underestimation of drought persistence at global scale. Subsequently, we analyzed to which degree (i) inaccurate observations, (ii) differences among models, (iii) internal climate variability, and (iv) uncertainty of the employed statistical methods contribute to the spread in drought persistence errors using an analysis of variance approach. The results show that at monthly scale, model uncertainty and observational uncertainty dominate, while the contribution from internal variability is small in most cases. At annual scale, the spread of the drought persistence error is dominated by the statistical estimation error of drought persistence, indicating that the partitioning of the error is impaired by the limited number of considered time steps. These findings reveal systematic errors in the representation of drought persistence in current GCMs and suggest directions for further model improvement.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170005278&hterms=water+supply&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dwater%2Bsupply','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170005278&hterms=water+supply&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dwater%2Bsupply"><span>The Potential for Snow to Supply Human Water Demand in the Present and Future</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mankin, Justin S.; Viviroli, Daniel; Singh, Deepti; Hoekstra, Arjen Y.; Diffenbaugh, Noah S.</p> <p>2015-01-01</p> <p>Runoff from snowmelt is regarded as a vital water source for people and ecosystems throughout the Northern Hemisphere (NH). Numerous studies point to the threat global warming poses to the timing and magnitude of snow accumulation and melt. But analyses focused on snow supply do not show where changes to snowmelt runoff are likely to present the most pressing adaptation challenges, given sub-annual patterns of human water consumption and water availability from rainfall. We identify the NH basins where present spring and summer snowmelt has the greatest potential to supply the human water demand that would otherwise be unmet by instantaneous rainfall runoff. Using a multi-model ensemble of climate change projections, we find that these basins - which together have a present population of approx. 2 billion people - are exposed to a 67% risk of decreased snow supply this coming century. Further, in the multi-model mean, 68 basins (with a present population of more than 300 million people) transition from having sufficient rainfall runoff to meet all present human water demand to having insufficient rainfall runoff. However, internal climate variability creates irreducible uncertainty in the projected future trends in snow resource potential, with about 90% of snow-sensitive basins showing potential for either increases or decreases over the near-term decades. Our results emphasize the importance of snow for fulfilling human water demand in many NH basins, and highlight the need to account for the full range of internal climate variability in developing robust climate risk management decisions.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ERL....13e5006T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ERL....13e5006T"><span>Evaluating the accuracy of climate change pattern emulation for low warming targets</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tebaldi, Claudia; Knutti, Reto</p> <p>2018-05-01</p> <p>Global climate policy is increasingly debating the value of very low warming targets, yet not many experiments conducted with global climate models in their fully coupled versions are currently available to help inform studies of the corresponding impacts. This raises the question whether a map of warming or precipitation change in a world 1.5 °C warmer than preindustrial can be emulated from existing simulations that reach higher warming targets, or whether entirely new simulations are required. Here we show that also for this type of low warming in strong mitigation scenarios, climate change signals are quite linear as a function of global temperature. Therefore, emulation techniques amounting to linear rescaling on the basis of global temperature change ratios (like simple pattern scaling) provide a viable way forward. The errors introduced are small relative to the spread in the forced response to a given scenario that we can assess from a multi-model ensemble. They are also small relative to the noise introduced into the estimates of the forced response by internal variability within a single model, which we can assess from either control simulations or initial condition ensembles. Challenges arise when scaling inadvertently reduces the inter-model spread or suppresses the internal variability, both important sources of uncertainty for impact assessment, or when the scenarios have very different characteristics in the composition of the forcings. Taking advantage of an available suite of coupled model simulations under low-warming and intermediate scenarios, we evaluate the accuracy of these emulation techniques and show that they are unlikely to represent a substantial contribution to the total uncertainty.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.7922D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.7922D"><span>Sensitivity of the regional climate in the Middle East and North Africa to volcanic perturbations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dogar, Muhammad Mubashar; Stenchikov, Georgiy; Osipov, Sergey; Wyman, Bruce; Zhao, Ming</p> <p>2017-08-01</p> <p>The Middle East and North Africa (MENA) regional climate appears to be extremely sensitive to volcanic eruptions. Winter cooling after the 1991 Pinatubo eruption far exceeded the mean hemispheric temperature anomaly, even causing snowfall in Israel. To better understand MENA climate variability, the climate responses to the El Chichón and Pinatubo volcanic eruptions are analyzed using observations, NOAA/National Centers for Environmental Prediction Climate Forecast System Reanalysis, and output from the Geophysical Fluid Dynamics Laboratory's High-Resolution Atmospheric Model. A multiple regression analysis both for the observations and the model output is performed on seasonal summer and winter composites to separate out the contributions from climate trends, El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian summer monsoon, and volcanic aerosols. Strong regional temperature and precipitation responses over the MENA region are found in both winter and summer. The model and the observations both show that a positive NAO amplifies the MENA volcanic winter cooling. In boreal summer, the patterns of changing temperature and precipitation suggest a weakening and southward shift of the Intertropical Convergence Zone, caused by volcanic surface cooling and weakening of the Indian and West African monsoons. The model captures the main features of the climate response; however, it underestimates the total cooling, especially in winter, and exhibits a different spatial pattern of the NAO climate response in MENA compared to the observations. The conducted analysis sheds light on the internal mechanisms of MENA climate variability and helps to selectively diagnose the model deficiencies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1810336','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1810336"><span>Solar influence on climate during the past millennium: Results from transient simulations with the NCAR Climate System Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Ammann, Caspar M.; Joos, Fortunat; Schimel, David S.; Otto-Bliesner, Bette L.; Tomas, Robert A.</p> <p>2007-01-01</p> <p>The potential role of solar variations in modulating recent climate has been debated for many decades and recent papers suggest that solar forcing may be less than previously believed. Because solar variability before the satellite period must be scaled from proxy data, large uncertainty exists about phase and magnitude of the forcing. We used a coupled climate system model to determine whether proxy-based irradiance series are capable of inducing climatic variations that resemble variations found in climate reconstructions, and if part of the previously estimated large range of past solar irradiance changes could be excluded. Transient simulations, covering the published range of solar irradiance estimates, were integrated from 850 AD to the present. Solar forcing as well as volcanic and anthropogenic forcing are detectable in the model results despite internal variability. The resulting climates are generally consistent with temperature reconstructions. Smaller, rather than larger, long-term trends in solar irradiance appear more plausible and produced modeled climates in better agreement with the range of Northern Hemisphere temperature proxy records both with respect to phase and magnitude. Despite the direct response of the model to solar forcing, even large solar irradiance change combined with realistic volcanic forcing over past centuries could not explain the late 20th century warming without inclusion of greenhouse gas forcing. Although solar and volcanic effects appear to dominate most of the slow climate variations within the past thousand years, the impacts of greenhouse gases have dominated since the second half of the last century. PMID:17360418</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EnMan..57..976K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EnMan..57..976K"><span>Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun</p> <p>2016-05-01</p> <p>Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26796698','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26796698"><span>Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; Zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun</p> <p>2016-05-01</p> <p>Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMNG51A1652L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMNG51A1652L"><span>Do GCM's Predict the Climate.... Or the Low Frequency Weather?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lovejoy, S.; Varon, D.; Schertzer, D. J.</p> <p>2011-12-01</p> <p>Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500- 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT ≈ ΔtH the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale. At longer scales Δt >τw (≈ 10 days) they change sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime the spectrum is a relatively flat "plateau", it's variability is that of the usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, again H>0, the variability again increases with scale. This is the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, "climate states", as fluctuations at scale τc and "climate change" as the fluctuations at longer periods >τc). We show that the intermediate regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched, only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by weather cascade models, but also by control runs (i.e. without climate forcing) of GCM's (including IPSL and ECHAM GCM's). In order for GCM's to go beyond simply predicting this low frequency weather so as to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. We examine this using wavelet analyses of forced and unforced GCM outputs, including the ECHO-G simulation used in the Millenium project. For example, we find that climate scenarios with large CO2 increases do give rise to a climate regime but that Hc>1 i.e. much larger than that of natural variability which for temperatures has Hc≈0.4. In comparison, the (largely volcanic) forcing of the ECHO-G Millenium simulation is fairly realistic (Hc≈0.4), although it is not clear that this mechanism can explain the even lower frequency variability found in the paleotemperature series, nor is it clear that this is compatible with low frequency solar or orbital forcings.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ERL.....9f4028V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ERL.....9f4028V"><span>Market-oriented ethanol and corn-trade policies can reduce climate-induced US corn price volatility</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Verma, Monika; Hertel, Thomas; Diffenbaugh, Noah</p> <p>2014-05-01</p> <p>Agriculture is closely affected by climate. Over the past decade, biofuels have emerged as another important factor shaping the agricultural sector. We ask whether the presence of the US ethanol sector can play a role in moderating increases in US corn price variability, projected to occur in response to near-term global warming. Our findings suggest that the answer to this question depends heavily on the underlying forces shaping the ethanol industry. If mandate-driven, there is little doubt that the presence of the corn-ethanol sector will exacerbate price volatility. However, if market-driven, then the emergence of the corn-ethanol sector can be a double-edged sword for corn price volatility, possibly cushioning the impact of increased climate driven supply volatility, but also inheriting volatility from the newly integrated energy markets via crude oil price fluctuations. We find that empirically the former effect dominates, reducing price volatility by 27%. In contrast, mandates on ethanol production increase future price volatility by 54% in under future climate after 2020. We also consider the potential for liberalized international corn trade to cushion corn price volatility in the US. Our results suggest that allowing corn to move freely internationally serves to reduce the impact of near-term climate change on US corn price volatility by 8%.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950033761&hterms=1606&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3D%2526%25231606','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950033761&hterms=1606&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3D%2526%25231606"><span>The global climate of December 1992-February 1993. Part 2: Large-scale variability across the tropical western Pacific during TOGA COARE</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gutzler, D. S.; Kiladis, G. N.; Meehl, G. A.; Weickmann, K. M.; Wheeler, M.</p> <p>1994-01-01</p> <p>Recently, scientists from more than a dozen countries carried out the field phase of a project called the Coupled-Atmosphere Response Experiment (COARE), devoted to describing the ocean-atmosphere system of the western Pacific near-equatorial warm pool. The project was conceived, organized, and funded under the auspices of the International Tropical Ocean Global Atmosphere (TOGA) Program. Although COARE consisted of several field phases, including a year-long atmospheric enhanced monitoring period (1 July 1992 -- 30 June 1993), the heart of COARE was its four-month Intensive Observation Period (IOP) extending from 1 Nov. 1992 through 28 Feb. 1993. An overview of large-scale variability during COARE is presented. The weather and climate observed in the IOP is placed into context with regard to large-scale, low-frequency fluctuations of the ocean-atmosphere system. Aspects of tropical variability beginning in Aug. 1992 and extending through Mar. 1993, with some sounding data for Apr. 1993 are considered. Variability over the large-scale sounding array (LSA) and the intensive flux array (IFA) is emphasized.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150002729','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150002729"><span>Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Little, Christopher M.; Horton, Radley M.; Kopp, Robert E.; Oppenheimer, Michael; Yip, Stan</p> <p>2015-01-01</p> <p>The representative concentration pathway (RCP) simulations included in phase 5 of the Coupled Model Intercomparison Project (CMIP5) quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ because of 1) forcing, 2) the representation of the climate system in atmosphere-ocean general circulation models (AOGCMs), and 3) the presence of unforced (internal) variability. Global and local sea level rise projections derived from these simulations, and the emergence of distinct responses to the four RCPs depend on the relative magnitude of these sources of uncertainty at different lead times. Here, the uncertainty in CMIP5 projections of sea level is partitioned at global and local scales, using a 164-member ensemble of twenty-first-century simulations. Local projections at New York City (NYSL) are highlighted. The partition between model uncertainty, scenario uncertainty, and internal variability in global mean sea level (GMSL) is qualitatively consistent with that of surface air temperature, with model uncertainty dominant for most of the twenty-first century. Locally, model uncertainty is dominant through 2100, with maxima in the North Atlantic and the Arctic Ocean. The model spread is driven largely by 4 of the 16 AOGCMs in the ensemble; these models exhibit outlying behavior in all RCPs and in both GMSL and NYSL. The magnitude of internal variability varies widely by location and across models, leading to differences of several decades in the local emergence of RCPs. The AOGCM spread, and its sensitivity to model exclusion and/or weighting, has important implications for sea level assessments, especially if a local risk management approach is utilized.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1810887A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1810887A"><span>Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy</p> <p>2016-04-01</p> <p>The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample from the full range of uncertainties associated with all parts of the simulation chain, from global climate models with simulations of natural climate variability, through regional climate downscaling, and on to modeling of affected hydrologic processes and downstream water resources impacts. This talk will present part of the work underway now both to reveal and reduce some important uncertainties and to develop explicit guidance for future generation of quantitative hydroclimatic storylines. Topics will include: 1- model structural and parameter-set limitations of some methods widely used to quantify climate impacts to hydrologic processes [Gutmann et al., 2014; Newman et al., 2015]; 2- development and evaluation of new, spatially consistent, U.S. national-scale climate downscaling and hydrologic simulation capabilities directly relevant at the multiple scales of water-resource decision-making [Newman et al., 2015; Mizukami et al., 2015; Gutmann et al., 2016]; and 3- development and evaluation of advanced streamflow forecasting methods to reduce and represent integrated uncertainties in a tractable way [Wood et al., 2014; Wood et al., 2015]. A key focus will be areas where climatologic and hydrologic science is currently under-developed to inform decisions - or is perhaps wrongly scaled or misapplied in practice - indicating the need for additional fundamental science and interpretation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018PCE...105..104A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018PCE...105..104A"><span>Signature of present and projected climate change at an urban scale: The case of Addis Ababa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arsiso, Bisrat Kifle; Mengistu Tsidu, Gizaw; Stoffberg, Gerrit Hendrik</p> <p>2018-06-01</p> <p>Understanding climate change and variability at an urban scale is essential for water resource management, land use planning, development of adaption plans, mitigation of air and water pollution. However, there are serious challenges to meet these goals due to unavailability of observed and/or simulated high resolution spatial and temporal climate data. The statistical downscaling of general circulation climate model, for instance, is usually driven by sparse observational data hindering the use of downscaled data to investigate urban scale climate variability and change in the past. Recently, these challenges are partly resolved by concerted international effort to produce global and high spatial resolution climate data. In this study, the 1 km2 high resolution NIMR-HadGEM2-AO simulations for future projections under Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios and gridded observations provided by Worldclim data center are used to assess changes in rainfall, minimum and maximum temperature expected under the two scenarios over Addis Ababa city. The gridded 1 km2 observational data set for the base period (1950-2000) is compared to observation from a meteorological station in the city in order to assess its quality for use as a reference (baseline) data. The comparison revealed that the data set has a very good quality. The rainfall anomalies under RCPs scenarios are wet in the 2030s (2020-2039), 2050s (2040-2069) and 2080s (2070-2099). Both minimum and maximum temperature anomalies under RCPs are successively getting warmer during these periods. Thus, the projected changes under RCPs scenarios show a general increase in rainfall and temperatures with strong variabilities in rainfall during rainy season implying level of difficulty in water resource use and management as well as land use planning and management.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPP11F..03L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPP11F..03L"><span>A synthesis of Plio-Pleistocene leaf wax biomarker records of hydrological variation in East Africa and their relationship with hominin evolution</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lupien, R.; Russell, J. M.; Campisano, C. J.; Feibel, C. S.; Deino, A. L.; Kingston, J.; Potts, R.; Cohen, A. S.</p> <p>2017-12-01</p> <p>Climate change is thought to play a critical role in human evolution. However, the mechanisms behind this relationship are difficult to test due to a lack of long, high-quality paleoclimate records from hominin fossil locales. We improve the understanding of this relationship by examining Plio-Pleistocene lake sediment cores from East Africa that were drilled by the Hominin Sites and Paleolakes Drilling Project, an international effort to study the environment in which our hominin ancestors evolved and dispersed. We have analyzed organic geochemical signals of climate from drill cores from Ethiopia and Kenya spanning the Pliocene to recent time (from north to south: paleolake Hadar, Lake Turkana, Lake Baringo, and paleolake Koora). Specifically, we analyzed the hydrogen isotopic composition of terrestrial leaf waxes, which records changes in regional atmospheric circulation and hydrology. We reconstructed quantitative records of rainfall amount at each of the study sites, which host sediment spanning different geologic times and regions. By compiling these records, we test hominin evolutionary hypotheses as well as crucial questions about climate trend and variability. We find that there is a gradual or step-wise enrichment in δDwax, signifying a trend from a wet to dry climate, from the Pliocene to the Pleistocene, perhaps implying an influence of global temperature, ice sheet extent, and/or atmospheric greenhouse gas concentrations on East African climate. However, the shift is small relative to the amplitude of orbital-scale isotopic variations. The records indicate a strong influence of eccentricity-modulated orbital precession, and imply that local insolation effects are the likely cause of East African precipitation. Several of the intervals of high isotopic variability coincide with key hominin fossil or technological transitions, suggesting that climate variability plays a key role in hominin evolution.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC11E..05A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC11E..05A"><span>Building Quantitative Hydrologic Storylines from Process-based Models for Managing Water Resources in the U.S. Under Climate-changed Futures</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arnold, J.; Gutmann, E. D.; Clark, M. P.; Nijssen, B.; Vano, J. A.; Addor, N.; Wood, A.; Newman, A. J.; Mizukami, N.; Brekke, L. D.; Rasmussen, R.; Mendoza, P. A.</p> <p>2016-12-01</p> <p>Climate change narratives for water-resource applications must represent the change signals contextualized by hydroclimatic process variability and uncertainty at multiple scales. Building narratives of plausible change includes assessing uncertainties across GCM structure, internal climate variability, climate downscaling methods, and hydrologic models. Work with this linked modeling chain has dealt mostly with GCM sampling directed separately to either model fidelity (does the model correctly reproduce the physical processes in the world?) or sensitivity (of different model responses to CO2 forcings) or diversity (of model type, structure, and complexity). This leaves unaddressed any interactions among those measures and with other components in the modeling chain used to identify water-resource vulnerabilities to specific climate threats. However, time-sensitive, real-world vulnerability studies typically cannot accommodate a full uncertainty ensemble across the whole modeling chain, so a gap has opened between current scientific knowledge and most routine applications for climate-changed hydrology. To close that gap, the US Army Corps of Engineers, the Bureau of Reclamation, and the National Center for Atmospheric Research are working on techniques to subsample uncertainties objectively across modeling chain components and to integrate results into quantitative hydrologic storylines of climate-changed futures. Importantly, these quantitative storylines are not drawn from a small sample of models or components. Rather, they stem from the more comprehensive characterization of the full uncertainty space for each component. Equally important from the perspective of water-resource practitioners, these quantitative hydrologic storylines are anchored in actual design and operations decisions potentially affected by climate change. This talk will describe part of our work characterizing variability and uncertainty across modeling chain components and their interactions using newly developed observational data, models and model outputs, and post-processing tools for making the resulting quantitative storylines most useful in practical hydrology applications.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3857548','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3857548"><span>A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.</p> <p>2013-01-01</p> <p>We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1711823O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1711823O"><span>Future Projections of Air Temperature and Precipitation for the CORDEX-MENA Domain by Using RegCM4.3.5</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ozturk, Tugba; Turp, M. Tufan; Türkeş, Murat; Kurnaz, M. Levent</p> <p>2015-04-01</p> <p>In this study, the projected changes for the periods of 2016 - 2035, 2046 - 2065, and 2081 - 2100 in the seasonal averages of air temperature and precipitation variables with respect to the reference period of 1981 - 2000 were examined for the Middle East and North Africa region. In this context, Regional Climate Model (RegCM4.3.5) of ICTP (International Centre for Theoretical Physics) was run by using two different global climate models. MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology and HadGEM2 of the Met Office Hadley Centre were dynamically downscaled to 50 km for the CORDEX-MENA domain. The projections were realized according to the RCP4.5 and the RCP8.5 emission scenarios of the IPCC (Intergovernmental Panel of Climate Change).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=329395&keyword=climate%20change&subject=climate%20change%20research&showcriteria=2&fed_org_id=111&datebeginpublishedpresented=12/13/2011&dateendpublishedpresented=12/13/2016&sortby=pubdateyear','PESTICIDES'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=329395&keyword=climate%20change&subject=climate%20change%20research&showcriteria=2&fed_org_id=111&datebeginpublishedpresented=12/13/2011&dateendpublishedpresented=12/13/2016&sortby=pubdateyear"><span>Climate change impacts on human exposures to air pollution ...</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.epa.gov/pesticides/search.htm">EPA Pesticide Factsheets</a></p> <p></p> <p></p> <p>This is an abstract for a presentations at the Annual Conference of the International Society on Exposure Science and Environmental Epidemiology. This presentation will serve as an introduction to the symposium. As we consider the potential health impacts of a warming planet, the relationships between climate change and air pollutants become increasingly important to understand. These relationships are complex and highly variable, causing a variety of environmental impacts at local, regional and global scales. Human exposures and health impacts for air pollutants have the potential to be altered by changes in climate through multiple factors that drive population exposures to these pollutants. Research on this topic will provide both state and local governments with the tools and scientific knowledge base to undertake any necessary adaptation of the air pollution regulations and/or public health management systems in the face of climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A43L..08R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A43L..08R"><span>Characterizing the "Time of Emergence" of Air Quality Climate Penalties</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rothenberg, D. A.; Garcia-Menendez, F.; Monier, E.; Solomon, S.; Selin, N. E.</p> <p>2017-12-01</p> <p>By driving not only local changes in temperature, but also precipitation and regional-scale changes in seasonal circulation patterns, climate change can directly and indirectly influence changes in air quality and its extremes. These changes - often referred to as "climate penalties" - can have important implications for human health, which is often targeted when assessing the potential co-benefits of climate policy. But because climate penalties are driven by slow, spatially-varying, temporal changes in the climate system, their emergence in the real world should also have a spatio-temporal component following regional variability in background air quality. In this work, we attempt to estimate the spatially-varying "time of emergence" of climate penalty signals by using an ensemble modeling framework based on the MIT Integrated Global System Model (MIT IGSM). With this framework we assess three climate policy scenarios assuming three different underlying climate sensitivities, and conduct a 5-member ensemble for each case to capture internal variability within the model. These simulations are used to drive offline chemical transport modeling (using CAM-Chem and GEOS-Chem). In these simulations, we find that the air quality response to climate change can vary dramatically across different regions of the globe. To analyze these regionally-varying climate signals, we employ a hierarchical clustering technique to identify regions with similar seasonal patterns of air quality change. Our simulations suggest that the earliest emergence of ozone climate penalties would occur in Southern Europe (by 2035), should the world neglect climate change and rely on a "business-as-usual" emissions policy. However, even modest climate policy dramatically pushes back the time of emergence of these penalties - to beyond 2100 - across most of the globe. The emergence of climate-forced changes in PM2.5 are much more difficult to detect, partially owing to the large role that changes in the frequency and spatial distribution of precipitation play in limiting the accumulation and duration of particulate pollution episodes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMED31E..07T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMED31E..07T"><span>Impacts Of Global/Regional Climate Changes On Environment And Health: Need For Integrated Research And Education Collaboration (Invited)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tuluri, F.</p> <p>2013-12-01</p> <p>The realization of long term changes in climate in research community has to go beyond the comfort zone through climate literacy in academics. Higher education on climate change is the platform to bring together the otherwise disconnected factors such as effective discovery, decision making, innovation, interdisciplinary collaboration, Climate change is a complex process that may be due to natural internal processes within the climate system, or to variations in natural or anthropogenic (human-driven) external forcing. Global climate change indicates a change in either the mean state of the climate or in its variability, persisting for several decades or longer. This includes changes in average weather conditions on Earth, such as a change in average global temperature, as well as changes in how frequently regions experience heat waves, droughts, floods, storms, and other extreme weather. It is important to examine the effects of climate variations on human health and disorders in order to take preventive measures. Similarly, the influence of climate changes on animal management practices, pests and pest management systems, and high value crops such as citrus and vegetables is also equally important for investigation. New genetic agricultural varieties must be explored, and pilot studies should examine biotechnology transfer. Recent climate model improvements have resulted in an enhanced ability to simulate many aspects of climate variability and extremes. However, they are still characterized by systematic errors and limitations in accurately simulating more precisely regional climate conditions. The present situations warrant developing climate literacy on the synergistic impacts of environmental change, and improve development, testing and validation of integrated stress impacts through computer modeling. In the present study we present a detailed study of the current status on the impacts of global/regional climate changes on environment and health with a view to highlighting the need for integrated research and education collaboration at national and global level.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUFMPP21A1372D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUFMPP21A1372D"><span>A High-Resolution Record of Holocene Climate Variability from a Western Canadian Coastal Inlet</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dallimore, A.; Thomson, R. E.; Enkin, R. J.; Kulikov, E. A.; Bertram, M. A.; Wright, C. A.; Southon, J. R.; Barrie, J. V.; Baker, J.; Pienitz, R.; Calvert, S. E.; Chang, A. S.; Pedersen, T. F.</p> <p>2004-12-01</p> <p>Conditions within the Pacific Ocean have a major effect on the climate of northwestern North America. High resolution records of present and past northeast Pacific climate are revealed in our multi-disciplinary study of annually laminated marine sediments from anoxic coastal inlets of British Columbia. Past climate conditions for the entire Holocene are recorded in the sediment record contained in a 40 meter, annually laminated marine sediment core taken in Effingham Inlet, on the west coast of Vancouver Island, British Columbia, from the French ship the Marion Dufresne, as part of the international IMAGES program. By combining our eight year continuous instrument record of modern coastal ocean dynamics and climate with high-resolution analysis of depositional processes, we have been able to develop proxy measurements of past climatic and oceanographic changes on annual to millennial time scales. Results indicate that regional climate has oscillated on a variety of time scales throughout the Holocene. At times, climatic change has been dramatically rapid. We are also developing digital methods for statistical time-series analyses of physical sediment properties through the Holocene in order to obtain a more objective quantitative approach for detecting cyclicity in our data. Results of the time series analysis of lamination thickness reveals statistically significant spectral peaks of climate scale variability at established decadal to century time scales. These in turn may be related to solar cycles and quasi-cyclical ocean processes such as the Pacific Decadal Oscillation. However, the annually laminated time series are periodically interrupted by massive mud intervals which are related to bottom currents and at times paleo-seismic events, illustrating the need for a full understanding of modern oceanographic and sedimentation processes, so an accurate proxy record of past climate can be established.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AdAtS..35..757W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AdAtS..35..757W"><span>Climate Change of 4°C GlobalWarming above Pre-industrial Levels</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Xiaoxin; Jiang, Dabang; Lang, Xianmei</p> <p>2018-07-01</p> <p>Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4°C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4°C global warming will occur is 2084. Based on the median results of models that project a 4°C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-tonoise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5°C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the intermodel consistency is better for temperature than for precipitation.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12.1137K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12.1137K"><span>Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.</p> <p>2018-04-01</p> <p>The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statistical predictors available in real time.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012CliPD...8.5455K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012CliPD...8.5455K"><span>On the origin of multi-decadal to centennial Greenland temperature anomalies over the past 800 yr</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kobashi, T.; Shindell, D. T.; Kodera, K.; Box, J. E.; Nakaegawa, T.; Kawamura, K.</p> <p>2012-11-01</p> <p>The surface temperature of the Greenland ice sheet is among the most important climate variables for assessing how climate change may impact human societies associated with accelerating sea level rise. However, the causes of multi-decadal-to-centennial temperature changes in Greenland are not well understood, largely owing to short observational records. To examine the causes of the Greenland temperature variability, we calculated the Greenland temperature anomalies (GTA(G-NH)) over the past 800 yr by subtracting the standardised NH temperature from the standardised Greenland temperature. It decomposes the Greenland temperature variation into background climate (NH); Polar amplification; and Regional variability (GTA(G-NH)). The Central Greenland polar amplification factor as expressed by the variance ratio = Greenland/NH is 2.6 over the past 161 yr, and 3.3-4.2 over the past 800 yr. The GTA explains 31-35% of the variation of Greenland temperature in the multi-decadal-to-centennial time scale over the past 800 yr. Another orthogonal component of the Greenland and NH temperatures, GTP(G+NH) (Greenland temperature plus = standardized Greenland temperature + standardized NH temperature) exhibited the multi-decadal variations that were likely induced by large volcanic eruptions, increasing greenhouse gasses, and internal variation of climate. We found that the GTA(G-NH) has been influenced by solar-induced changes in atmospheric circulation patterns such as those produced by North Atlantic Oscillation/Arctic Oscillation (NAO/AO). Climate modelling indicates that the anomaly is also likely linked to solar-paced changes in the Atlantic meridional overturning circulation (AMOC) and to associated changes in northward oceanic heat transport.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ems..confE..97A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ems..confE..97A"><span>HIST-EU - a dataset of European relevance, a database to enable long-term climate variability studies on regional scale</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Auer, I.; Böhm, R.; Ganekind, M.; Schöner, W.; Nemec, J.; Chimani, B.</p> <p>2010-09-01</p> <p>Instrumental time series of different climate elements are an important requisite for climate and climate impact studies. Long-term time series can improve our understanding of climate change during the instrumental period. During recent decades a number of national and international initiatives in European countries have significantly increased the number of existing long-term instrumental series; however a publically available data base covering Europe has not been created so far. For the "Greater Alpine Region" (4-19 deg E, 43-49 deg N, 0-3500m asl) the HISTALP data base has been established consisting of monthly homogenised temperature, pressure, precipitation, sunshine and cloudiness records. The data set may be described as follows: Long-term (fully exploiting the potential of systematically measured data). dense (network density adequate in respect to the spatial coherence of the given climate element) quality improved (outliers removed, gaps filled) homogenised (earlier sections adjusted to the recent state of the measuring site) multiple (covering more than one climate element) user friendly (well described and kept in different modes for different applications) HIST-EU is inteded to be a data set of European relevance allowing studying climate variability on regional scale. It focuses on data collection, data recovery and rescue, and homogenizing. HIST-EU will use the infrastructure of HISTALP (www.zamg.ac.at/histalp) and will allow free or restricted data access due to the regulations of data providers. HIST-EU will be carried out under the umbrella of ECSN/EUMETNET.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2689003','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2689003"><span>Selecting global climate models for regional climate change studies</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Pierce, David W.; Barnett, Tim P.; Santer, Benjamin D.; Gleckler, Peter J.</p> <p>2009-01-01</p> <p>Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures. PMID:19439652</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC11H1116C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC11H1116C"><span>Climate and Health Vulnerability to Vector-Borne Diseases: Increasing Resilience under Climate Change Conditions in Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ceccato, P.</p> <p>2015-12-01</p> <p>The International Research Institute for Climate and Society (IRI), the City University of New York (CUNY) and NASA Jet Propulsion Laboratory (JPL) in collaboration with NASA SERVIR are developing tools to monitor climate variables (precipitation, temperature, vegetation, water bodies, inundation) that help projects in Africa to increase resilience to climate change for vector-borne diseases ( malaria, trypanosomiasis, leishmaniasis, and schistosomiasis). Through the development of new products to monitor precipitation, water bodies and inundation, IRI, CUNY and JPL provide tools and capacity building to research communities; ministries of health; the WMO Global Framework for Climate and Services; and World Health Organization in Africa to: 1) Develop research teams' ability to appropriately use climate data as part of their research 2) Enable research teams and ministries to integrate climate information into social and economic drivers of vulnerability and opportunities for adaptation to climate change 3) Inform better policies and programs for climate change adaptation. This oral presentation will demonstrate how IRI, CUNY, and JPL developed new products, tools and capacity building to achieve the three objectives mentioned above with examples in South Africa, Zimbabwe, Tanzania and Malawi.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012GeoRL..39.8502N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012GeoRL..39.8502N"><span>Observations reveal external driver for Arctic sea-ice retreat</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Notz, Dirk; Marotzke, Jochem</p> <p>2012-04-01</p> <p>The very low summer extent of Arctic sea ice that has been observed in recent years is often casually interpreted as an early-warning sign of anthropogenic global warming. For examining the validity of this claim, previously IPCC model simulations have been used. Here, we focus on the available observational record to examine if this record allows us to identify either internal variability, self-acceleration, or a specific external forcing as the main driver for the observed sea-ice retreat. We find that the available observations are sufficient to virtually exclude internal variability and self-acceleration as an explanation for the observed long-term trend, clustering, and magnitude of recent sea-ice minima. Instead, the recent retreat is well described by the superposition of an externally forced linear trend and internal variability. For the externally forced trend, we find a physically plausible strong correlation only with increasing atmospheric CO2 concentration. Our results hence show that the observed evolution of Arctic sea-ice extent is consistent with the claim that virtually certainly the impact of an anthropogenic climate change is observable in Arctic sea ice already today.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp...35H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp...35H"><span>Uncertainty in Indian Ocean Dipole response to global warming: the role of internal variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hui, Chang; Zheng, Xiao-Tong</p> <p>2018-01-01</p> <p>The Indian Ocean Dipole (IOD) is one of the leading modes of interannual sea surface temperature (SST) variability in the tropical Indian Ocean (TIO). The response of IOD to global warming is quite uncertain in climate model projections. In this study, the uncertainty in IOD change under global warming, especially that resulting from internal variability, is investigated based on the community earth system model large ensemble (CESM-LE). For the IOD amplitude change, the inter-member uncertainty in CESM-LE is about 50% of the intermodel uncertainty in the phase 5 of the coupled model intercomparison project (CMIP5) multimodel ensemble, indicating the important role of internal variability in IOD future projection. In CESM-LE, both the ensemble mean and spread in mean SST warming show a zonal positive IOD-like (pIOD-like) pattern in the TIO. This pIOD-like mean warming regulates ocean-atmospheric feedbacks of the interannual IOD mode, and weakens the skewness of the interannual variability. However, as the changes in oceanic and atmospheric feedbacks counteract each other, the inter-member variability in IOD amplitude change is not correlated with that of the mean state change. Instead, the ensemble spread in IOD amplitude change is correlated with that in ENSO amplitude change in CESM-LE, reflecting the close inter-basin relationship between the tropical Pacific and Indian Ocean in this model.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70021775','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70021775"><span>The sensitivity of terrestrial carbon storage to historical climate variability and atmospheric CO2 in the United States</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Tian, H.; Melillo, J.M.; Kicklighter, D.W.; McGuire, A.D.; Helfrich, J.</p> <p>1999-01-01</p> <p>We use the Terrestrial Ecosystem Model (TEM, Version 4.1) and the land cover data set of the international geosphere-biosphere program to investigate how increasing atmospheric CO2 concentration and climate variability during 1900-1994 affect the carbon storage of terrestrial ecosystems in the conterminous USA, and how carbon storage has been affected by land-use change. The estimates of TEM indicate that over the past 95 years a combination of increasing atmospheric CO2 with historical temperature and precipitation variability causes a 4.2% (4.3 Pg C) decrease in total carbon storage of potential vegetation in the conterminous US, with vegetation carbon decreasing by 7.2% (3.2 Pg C) and soil organic carbon decreasing by 1.9% (1.1 Pg C). Several dry periods including the 1930s and 1950s are responsible for the loss of carbon storage. Our factorial experiments indicate that precipitation variability alone decreases total carbon storage by 9.5%. Temperature variability alone does not significantly affect carbon storage. The effect of CO2 fertilization alone increases total carbon storage by 4.4%. The effects of increasing atmospheric CO2 and climate variability are not additive. Interactions among CO2, temperature and precipitation increase total carbon storage by 1.1%. Our study also shows substantial year-to-year variations in net carbon exchange between the atmosphere and terrestrial ecosystems due to climate variability. Since the 1960s, we estimate these terrestrial ecosystems have acted primarily as a sink of atmospheric CO2 as a result of wetter weather and higher atmospheric CO2 concentrations. For the 1980s, we estimate the natural terrestrial ecosystems, excluding cropland and urban areas, of the conterminous US have accumulated 78.2 Tg C yr-1 because of the combined effect of increasing atmospheric CO2 and climate variability. For the conterminous US, we estimate that the conversion of natural ecosystems to cropland and urban areas has caused a 18.2% (17.7 Pg C) reduction in total carbon storage from that estimated for potential vegetation. The carbon sink capacity of natural terrestrial ecosystems in the conterminous US is about 69% of that estimated for potential vegetation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A51M..02B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A51M..02B"><span>Forced vs unforced drivers of Atlantic SST variability - linking forced role to magnitude of aerosol forcing</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Booth, B.; Dunstone, N.; Halloran, P. R.; Andrews, T.; Bellouin, N.; Martin, E. R.</p> <p>2014-12-01</p> <p>Historical variations in North Atlantic SSTs have been a key driver of regional climate change - linked to drought frequency in the Sahel, Amazon and American Mid-West, rainfall and heat waves in Europe and frequency of Atlantic tropical storms. Traditionally these SST variations were deemed to arise from internally generated ocean variability. We present results from recent studies (Booth et al, 2012, Dunstone, 2013) that identify a mechanism via which volcanic and industrial aerosols could explain a large fraction of observed Atlantic variability, and its associated climate impacts. This work has prompted a lot of subsequent discussion about the relative contribution of ocean generated and external forced variability in the Atlantic. Here we present new results, that extend this earlier work, by looking at forced variability in the CMIP5 modelling context. This provides new insights into the potential externally forced role aerosols may play in the real world. CMIP5 models that represent aerosol-cloud interactions tend to have stronger correlations to observed variations in SSTs, but disagree on the magnitude of forced variability that they explain. We can link this contribution to the magnitude of aerosol forcing in each of these models - a factor that is both dependent on the aerosol parameterisation and the representation of boundary layer cloud in this region. This suggests that whether aerosols have played a larger or smaller role in historical Atlantic variability is tied to whether aerosols have a larger or smaller aerosol forcing (particularly indirect) in the real world. This in turn suggests that benefits of reducing current aerosol uncertainty are likely to extend beyond better estimates of global forcing, to providing a clearer picture of the past aerosol driven role in historical regional climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ESD.....7..797R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ESD.....7..797R"><span>Revisiting ocean carbon sequestration by direct injection: a global carbon budget perspective</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Reith, Fabian; Keller, David P.; Oschlies, Andreas</p> <p>2016-11-01</p> <p>In this study we look beyond the previously studied effects of oceanic CO2 injections on atmospheric and oceanic reservoirs and also account for carbon cycle and climate feedbacks between the atmosphere and the terrestrial biosphere. Considering these additional feedbacks is important since backfluxes from the terrestrial biosphere to the atmosphere in response to reducing atmospheric CO2 can further offset the targeted reduction. To quantify these dynamics we use an Earth system model of intermediate complexity to simulate direct injection of CO2 into the deep ocean as a means of emissions mitigation during a high CO2 emission scenario. In three sets of experiments with different injection depths, we simulate a 100-year injection period of a total of 70 Gt<mspace linebreak="nobreak" width="0.125em"/>C and follow global carbon cycle dynamics over another 900 years. In additional parameter perturbation runs, we varied the default terrestrial photosynthesis CO2 fertilization parameterization by ±50 % in order to test the sensitivity of this uncertain carbon cycle feedback to the targeted atmospheric carbon reduction through direct CO2 injections. Simulated seawater chemistry changes and marine carbon storage effectiveness are similar to previous studies. As expected, by the end of the injection period avoided emissions fall short of the targeted 70 Gt<mspace linebreak="nobreak" width="0.125em"/>C by 16-30 % as a result of carbon cycle feedbacks and backfluxes in both land and ocean reservoirs. The target emissions reduction in the parameter perturbation simulations is about 0.2 and 2 % more at the end of the injection period and about 9 % less to 1 % more at the end of the simulations when compared to the unperturbed injection runs. An unexpected feature is the effect of the model's internal variability of deep-water formation in the Southern Ocean, which, in some model runs, causes additional oceanic carbon uptake after injection termination relative to a control run without injection and therefore with slightly different atmospheric CO2 and climate. These results of a model that has very low internal climate variability illustrate that the attribution of carbon fluxes and accounting for injected CO2 may be very challenging in the real climate system with its much larger internal variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19920062192&hterms=Thorndike&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DThorndike','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19920062192&hterms=Thorndike&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DThorndike"><span>A toy model linking atmospheric thermal radiation and sea ice growth</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Thorndike, A. S.</p> <p>1992-01-01</p> <p>A simplified analytical model of sea ice growth is presented where the atmosphere is in thermal radiative equilibrium with the ice. This makes the downwelling longwave radiation reaching the ice surface an internal variable rather than a specified forcing. Analytical results demonstrate how the ice state depends on properties of the ice and on the externally specified climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A53D2286S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A53D2286S"><span>Internally Generated and Externally Forced Multidecadal Oceanic Modes and their Influence on the Summer Rainfall over East Asia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Si, D.; Hu, A.</p> <p>2017-12-01</p> <p>The interdecadal oceanic variabilities can be generated from both internal and external processes, and these variabilities can significantly modulate our climate on global and regional scale, such as the warming slowdown in the early 21st century, and the rainfall in East Asia. By analyzing simulations from a unique Community Earth System Model (CESM) Large Ensemble (CESM_LE) project, we show that the Interdecadal Pacific Oscillation (IPO) is primarily an internally generated oceanic variability, while the Atlantic Multidecadal Oscillation (AMO) may be an oceanic variability generated by internal oceanic processes and modulated by external forcings in the 20th century. Although the observed relationship between IPO and the Yangtze-Huaihe River valley (YHRV) summer rainfall in China is well simulated in both the preindustrial control and 20th century ensemble, none of the 20th century ensemble members can reproduce the observed time evolution of both IPO and YHRV due to the unpredictable nature of IPO on multidecade timescale. On the other hand, although CESM_LE cannot reproduce the observed relationship between AMO and Huanghe River valley (HRV) summer rainfall of China in the preindustrial control simulation, this relationship in the 20th century simulations is well reproduced, and the chance to reproduce the observed time evolution of both AMO and HRV rainfall is about 30%, indicating the important role of the interaction between the internal processes and the external forcing to realistically simulate the AMO and HRV rainfall.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23032279','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23032279"><span>Climate information for public health: the role of the IRI climate data library in an integrated knowledge system.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>del Corral, John; Blumenthal, M Benno; Mantilla, Gilma; Ceccato, Pietro; Connor, Stephen J; Thomson, Madeleine C</p> <p>2012-09-01</p> <p>Public health professionals are increasingly concerned about the potential impact of climate variability and change on health outcomes. Protecting public health from the vagaries of climate requires new working relationships between the public health sector and the providers of climate data and information. The Climate Information for Public Health Action initiative at the International Research Institute for Climate and Society (IRI) is designed to increase the public health community's capacity to understand, use and demand appropriate climate data and climate information to mitigate the public health impacts of the climate. Significant challenges to building the capacity of health professionals to use climate information in research and decision-making include the difficulties experienced by many in accessing relevant and timely quality controlled data and information in formats that can be readily incorporated into specific analysis with other data sources. We present here the capacities of the IRI climate data library and show how we have used it to build an integrated knowledge system in the support of the use of climate and environmental information in climate-sensitive decision-making with respect to health. Initiated as an aid facilitating exploratory data analysis for climate scientists, the IRI climate data library has emerged as a powerful tool for interdisciplinary researchers focused on topics related to climate impacts on society, including health.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24910517','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24910517"><span>A century of variation in the dependence of Greenland iceberg calving on ice sheet surface mass balance and regional climate change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bigg, G R; Wei, H L; Wilton, D J; Zhao, Y; Billings, S A; Hanna, E; Kadirkamanathan, V</p> <p>2014-06-08</p> <p>Iceberg calving is a major component of the total mass balance of the Greenland ice sheet (GrIS). A century-long record of Greenland icebergs comes from the International Ice Patrol's record of icebergs (I48N) passing latitude 48° N, off Newfoundland. I48N exhibits strong interannual variability, with a significant increase in amplitude over recent decades. In this study, we show, through a combination of nonlinear system identification and coupled ocean-iceberg modelling, that I48N's variability is predominantly caused by fluctuation in GrIS calving discharge rather than open ocean iceberg melting. We also demonstrate that the episodic variation in iceberg discharge is strongly linked to a nonlinear combination of recent changes in the surface mass balance (SMB) of the GrIS and regional atmospheric and oceanic climate variability, on the scale of the previous 1-3 years, with the dominant causal mechanism shifting between glaciological (SMB) and climatic (ocean temperature) over time. We suggest that this is a change in whether glacial run-off or under-ice melting is dominant, respectively. We also suggest that GrIS calving discharge is episodic on at least a regional scale and has recently been increasing significantly, largely as a result of west Greenland sources.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2000BAMS...81.2121B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2000BAMS...81.2121B"><span>Global Impacts and Regional Actions: Preparing for the 1997-98 El Niño.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Buizer, James L.; Foster, Josh; Lund, David</p> <p>2000-09-01</p> <p>It has been estimated that severe El Niño-related flooding and droughts in Africa, Latin America, North America, and Southeast Asia resulted in more than 22 000 lives lost and in excess of $36 billion in damages during 1997-98. As one of the most severe events this century, the 1997-98 El Niño was unique not only in terms of physical magnitude, but also in terms of human response. This response was made possible by recent advances in climate-observing and forecasting systems, creation and dissemination of forecast information by institutions such as the International Research Institute for Climate Prediction and NOAA's Climate Prediction Center, and individuals in climate-sensitive sectors willing to act on forecast information by incorporating it into their decision-making. The supporting link between the forecasts and their practical application was a product of efforts by several national and international organizations, and a primary focus of the United States National Oceanic and Atmospheric Administration Office of Global Programs (NOAA/OGP).NOAA/OGP over the last decade has supported pilot projects in Latin America, the Caribbean, the South Pacific, Southeast Asia, and Africa to improve transfer of forecast information to climate sensitive sectors, study linkages between climate and human health, and distribute climate information products in certain areas. Working with domestic and international partners, NOAA/OGP helped organize a total of 11 Climate Outlook Fora around the world during the 1997-98 El Niño. At each Outlook Forum, climatologists and meteorologists created regional, consensus-based, seasonal precipitation forecasts and representatives from climate-sensitive sectors discussed options for applying forecast information. Additional ongoing activities during 1997-98 included research programs focused on the social and economic impacts of climate change and the regional manifestations of global-scale climate variations and their effect on decision-making in climate-sensitive sectors in the United States.The overall intent of NOAA/OGP's activities was to make experimental forecast information broadly available to potential users, and to foster a learning process on how seasonal-to-interannual forecasts could be applied in sectors susceptible to climate variability. This process allowed users to explore the capabilities and limitations of climate forecasts currently available, and forecast producers to receive feedback on the utility of their products. Through activities in which NOAA/OGP and its partners were involved, it became clear that further application of forecast information will be aided by improved forecast accuracy and detail, creation of common validation techniques, continued training in forecast generation and application, alternate methods for presenting forecast information, and a systematic strategy for creation and dissemination of forecast products.The overall intent of NOAA/OGP's activities was to make experimental forecast information broadly available to potential users, and to foster a learning process on how seasonal-to-interannual forecasts could be applied in sectors susceptible to climate variability. This process allowed users to explore the capabilities and limitations of climate forecasts currently available, and forecast producers to receive feedback on the utility of their products. Through activities in which NOAA/OGP and its partners were involved, it became clear that further application of forecast information will be aided by improved forecast accuracy and detail, creation of common validation techniques, continued training in forecast generation and application, alternate methods for presenting forecast information, and a systematic strategy for creation and dissemination of forecast products.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020033732','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020033732"><span>Variability of Clouds Over a Solar Cycle</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yung, Yuk L.</p> <p>2002-01-01</p> <p>One of the most controversial aspects of climate studies is the debate over the natural and anthropogenic causes of climate change. Historical data strongly suggest that the Little Ice Age (from 1550 to 1850 AD when the mean temperature was colder by about 1 C) was most likely caused by variability of the sun and not greenhouse molecules (e.g., CO2). However, the known variability in solar irradiance and modulation of cosmic rays provides too little energy, by many orders of magnitude, to lead to climate changes in the troposphere. The conjecture is that there is a 'trigger mechanism'. This idea may now be subjected to a quantitative test using recent global datasets. Using the best available modern cloud data from International Satellite Cloud Climatology Project (ISCCP), Svensmark and Friis-Christensen found a correlation of a large variation (3-4%) in global cloud cover with the solar cycle. The work has been extended by Svensmark and Marsh and Svensmark. The implied forcing on climate is an order of magnitude greater than any previous claims. Are clouds the long sought trigger mechanism? This discovery is potentially so important that it should be corroborated by an independent database, and, furthermore, it must be shown that alternative explanations (i.e., El Nino) can be ruled out. We used the ISCCP data in conjunction with the Total Ozone Mapping Spectrometer (TOMS) data to carry out in in depth study of the cloud trigger mechanism.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.6916S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.6916S"><span>Indian Ocean zonal mode activity in 20th century observations and simulations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sendelbeck, Anja; Mölg, Thomas</p> <p>2016-04-01</p> <p>The Indian Ocean zonal mode (IOZM) is a coupled ocean-atmosphere system with anomalous cooling in the east, warming in the west and easterly wind anomalies, resulting in a complete reversal of the climatological zonal sea surface temperature (SST) gradient. The IOZM has a strong influence on East African climate by causing anomalously strong October - December (OND) precipitation. Using observational data and historical CMIP5 (Coupled Model Intercomparison Project phase 5) model output, the September - November (SON) dipole mode index (DMI), OND East African precipitation and SON zonal wind index (ZWI) are calculated. We pay particular attention to detrending SSTs for calculating the DMI, which seems to have been neglected in some published research. The ZWI is defined as the area-averaged zonal wind component at 850 hPa over the central Indian Ocean. Regression analysis is used to evaluate the models' capability to represent the IOZM and its impact on east African climate between 1948 and 2005. Simple correlations are calculated between SST, zonal wind and precipitation to show their interdependence. High correlation in models implies a good representation of the influence of IOZM on East African climate variability and our goal is to detect the models with the highest correlation coefficients. In future research, these model data might be used to investigate the impact of IOZM on the East African climate variability in the late 20's century with regard to anthropogenic causes and internal variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp...63M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp...63M"><span>The Little Ice Age was 1.0-1.5 °C cooler than current warm period according to LOD and NAO</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mazzarella, Adriano; Scafetta, Nicola</p> <p>2018-02-01</p> <p>We study the yearly values of the length of day (LOD, 1623-2016) and its link to the zonal index (ZI, 1873-2003), the Northern Atlantic oscillation index (NAO, 1659-2000) and the global sea surface temperature (SST, 1850-2016). LOD is herein assumed to be mostly the result of the overall circulations occurring within the ocean-atmospheric system. We find that LOD is negatively correlated with the global SST and with both the integral function of ZI and NAO, which are labeled as IZI and INAO. A first result is that LOD must be driven by a climatic change induced by an external (e.g. solar/astronomical) forcing since internal variability alone would have likely induced a positive correlation among the same variables because of the conservation of the Earth's angular momentum. A second result is that the high correlation among the variables implies that the LOD and INAO records can be adopted as global proxies to reconstruct past climate change. Tentative global SST reconstructions since the seventeenth century suggest that around 1700, that is during the coolest period of the Little Ice Age (LIA), SST could have been about 1.0-1.5 °C cooler than the 1950-1980 period. This estimated LIA cooling is greater than what some multiproxy global climate reconstructions suggested, but it is in good agreement with other more recent climate reconstructions including those based on borehole temperature data.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25229494','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25229494"><span>Cholera and shigellosis: different epidemiology but similar responses to climate variability.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cash, Benjamin A; Rodó, Xavier; Emch, Michael; Yunus, Md; Faruque, Abu S G; Pascual, Mercedes</p> <p>2014-01-01</p> <p>Comparative studies of the associations between different infectious diseases and climate variability, such as the El Niño-Southern Oscillation, are lacking. Diarrheal illnesses, particularly cholera and shigellosis, provide an important opportunity to apply a comparative approach. Cholera and shigellosis have significant global mortality and morbidity burden, pronounced differences in transmission pathways and pathogen ecologies, and there is an established climate link with cholera. In particular, the specific ecology of Vibrio cholerae is often invoked to explain the sensitivity of that disease to climate. The extensive surveillance data of the International Center for Diarrheal Disease Research, Bangladesh are used here to revisit the known associations between cholera and climate, and to address their similarity to previously unexplored patterns for shigellosis. Monthly case data for both the city of Dhaka and a rural area known as Matlab are analyzed with respect to their association with El Niño and flooding. Linear correlations are examined between flooding and cumulative cases, as well as for flooding and El Niño. Rank-correlation maps are also computed between disease cases in the post-monsoon epidemic season and sea surface temperatures in the Pacific. Similar climate associations are found for both diseases and both locations. Increased cases follow increased monsoon flooding and increased sea surface temperatures in the preceding winter corresponding to an El Niño event. The similarity in association patterns suggests a systemic breakdown in population health with changing environmental conditions, in which climate variability acts primarily through increasing the exposure risk of the human population. We discuss these results in the context of the on-going debate on the relative importance of the environmental reservoir vs. secondary transmission, as well as the implications for the use of El Niño as an early indicator of flooding and enteric disease risk.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4168003','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4168003"><span>Cholera and Shigellosis: Different Epidemiology but Similar Responses to Climate Variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Cash, Benjamin A.; Rodó, Xavier; Emch, Michael; Yunus, Md.; Faruque, Abu S. G.; Pascual, Mercedes</p> <p>2014-01-01</p> <p>Background Comparative studies of the associations between different infectious diseases and climate variability, such as the El Niño-Southern Oscillation, are lacking. Diarrheal illnesses, particularly cholera and shigellosis, provide an important opportunity to apply a comparative approach. Cholera and shigellosis have significant global mortality and morbidity burden, pronounced differences in transmission pathways and pathogen ecologies, and there is an established climate link with cholera. In particular, the specific ecology of Vibrio cholerae is often invoked to explain the sensitivity of that disease to climate. Methods and Findings The extensive surveillance data of the International Center for Diarrheal Disease Research, Bangladesh are used here to revisit the known associations between cholera and climate, and to address their similarity to previously unexplored patterns for shigellosis. Monthly case data for both the city of Dhaka and a rural area known as Matlab are analyzed with respect to their association with El Niño and flooding. Linear correlations are examined between flooding and cumulative cases, as well as for flooding and El Niño. Rank-correlation maps are also computed between disease cases in the post-monsoon epidemic season and sea surface temperatures in the Pacific. Similar climate associations are found for both diseases and both locations. Increased cases follow increased monsoon flooding and increased sea surface temperatures in the preceding winter corresponding to an El Niño event. Conclusions The similarity in association patterns suggests a systemic breakdown in population health with changing environmental conditions, in which climate variability acts primarily through increasing the exposure risk of the human population. We discuss these results in the context of the on-going debate on the relative importance of the environmental reservoir vs. secondary transmission, as well as the implications for the use of El Niño as an early indicator of flooding and enteric disease risk. PMID:25229494</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3178611','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3178611"><span>Causes and Consequences of Past and Projected Scandinavian Summer Temperatures, 500–2100 AD</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Büntgen, Ulf; Raible, Christoph C.; Frank, David; Helama, Samuli; Cunningham, Laura; Hofer, Dominik; Nievergelt, Daniel; Verstege, Anne; Timonen, Mauri; Stenseth, Nils Chr.; Esper, Jan</p> <p>2011-01-01</p> <p>Tree rings dominate millennium-long temperature reconstructions and many records originate from Scandinavia, an area for which the relative roles of external forcing and internal variation on climatic changes are, however, not yet fully understood. Here we compile 1,179 series of maximum latewood density measurements from 25 conifer sites in northern Scandinavia, establish a suite of 36 subset chronologies, and analyse their climate signal. A new reconstruction for the 1483–2006 period correlates at 0.80 with June–August temperatures back to 1860. Summer cooling during the early 17th century and peak warming in the 1930s translate into a decadal amplitude of 2.9°C, which agrees with existing Scandinavian tree-ring proxies. Climate model simulations reveal similar amounts of mid to low frequency variability, suggesting that internal ocean-atmosphere feedbacks likely influenced Scandinavian temperatures more than external forcing. Projected 21st century warming under the SRES A2 scenario would, however, exceed the reconstructed temperature envelope of the past 1,500 years. PMID:21966436</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20180002900&hterms=ECS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DECS','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20180002900&hterms=ECS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DECS"><span>Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity from Observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.</p> <p>2018-01-01</p> <p>An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2-radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.1595M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.1595M"><span>Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.</p> <p>2018-02-01</p> <p>An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC23D0663G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC23D0663G"><span>A Stochastic Climate Generator for Agriculture in Southeast Asian Domains</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Greene, A. M.; Allis, E. C.</p> <p>2014-12-01</p> <p>We extend a previously-described method for generating future climate scenarios, suitable for driving agricultural models, to selected domains in Lao PDR, Bangladesh and Indonesia. There are notable differences in climatology among the study regions, most importantly the inverse seasonal relationship of southeast Asian and Australian monsoons. These differences necessitate a partially-differentiated modeling approach, utilizing common features for better estimation while allowing independent modeling of divergent attributes. The method attempts to constrain uncertainty due to both anthropogenic and natural influences, providing a measure of how these effects may combine during specified future decades. Seasonal climate fields are downscaled to the daily time step by resampling the AgMERRA dataset, providing a full suite of agriculturally relevant variables and enabling the propagation of climate uncertainty to agricultural outputs. The role of this research in a broader project, conducted under the auspices of the International Fund for Agricultural Development (IFAD), is discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70196673','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70196673"><span>Climate model assessment of changes in winter-spring streamflow timing over North America</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Kam, Jonghun; Knutson, Thomas R.; Milly, Paul C. D.</p> <p>2018-01-01</p> <p>Over regions where snow-melt runoff substantially contributes to winter-spring streamflows, warming can accelerate snow melt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, a detection/attribution of changes in mid-latitude North American winter-spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. In this study, robustness across models, start/end dates for trends, and assumptions about internal variability is evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central U.S., where winter-spring streamflows have been coming earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western U.S./southwestern Canada and in extreme northeastern U.S./Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow-free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9607E..1KH','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9607E..1KH"><span>Collaboration pathway(s) using new tools for optimizing `operational' climate monitoring from space</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.</p> <p>2015-09-01</p> <p>Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a long term solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the collective needs of policy makers, scientific communities and global academic users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent rule-based expert system (RBES) optimization modeling of the intended NPOESS architecture becomes a surrogate for global operational climate monitoring architecture(s). These rulebased systems tools provide valuable insight for global climate architectures, by comparison/evaluation of alternatives and the sheer range of trade space explored. Optimization of climate monitoring architecture(s) for a partial list of ECV (essential climate variables) is explored and described in detail with dialogue on appropriate rule-based valuations. These optimization tool(s) suggest global collaboration advantages and elicit responses from the audience and climate science community. This paper will focus on recent research exploring joint requirement implications of the high profile NPOESS architecture and extends the research and tools to optimization for a climate centric case study. This reflects work from SPIE RS Conferences 2013 and 2014, abridged for simplification30, 32. First, the heavily securitized NPOESS architecture; inspired the recent research question - was Complexity (as a cost/risk factor) overlooked when considering the benefits of aggregating different missions into a single platform. Now years later a complete reversal; should agencies considering Disaggregation as the answer. We'll discuss what some academic research suggests. Second, using the GCOS requirements of earth climate observations via ECV (essential climate variables) many collected from space-based sensors; and accepting their definitions of global coverages intended to ensure the needs of major global and international organizations (UNFCCC and IPCC) are met as a core objective. Consider how new optimization tools like rule-based engines (RBES) offer alternative methods of evaluating collaborative architectures and constellations? What would the trade space of optimized operational climate monitoring architectures of ECV look like? Third, using the RBES tool kit (2014) demonstrate with application to a climate centric rule-based decision engine - optimizing architectural trades of earth observation satellite systems, allowing comparison(s) to existing architectures and gaining insights for global collaborative architectures. How difficult is it to pull together an optimized climate case study - utilizing for example 12 climate based instruments on multiple existing platforms and nominal handful of orbits; for best cost and performance benefits against the collection requirements of representative set of ECV. How much effort and resources would an organization expect to invest to realize these analysis and utility benefits?</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPA21D0357L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPA21D0357L"><span>Earth Observations in Support of Offshore Wind Energy Management in the Euro-Atlantic Region</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liberato, M. L. R.</p> <p>2017-12-01</p> <p>Climate change is one of the most important challenges in the 21st century and the energy sector is a major contributor to GHG emissions. Therefore greater attention has been given to the evaluation of offshore wind energy potentials along coastal areas, as it is expected offshore wind energy to be more efficient and cost-effective in the near future. Europe is developing offshore sites for over two decades and has been growing at gigawatt levels in annual capacity. Portugal is among these countries, with the development of a 25MW WindFloat Atlantic wind farm project. The international scientific community has developed robust ability on the research of the climate system components and their interactions. Climate scientists have gained expertise in the observation and analysis of the climate system as well as on the improvement of model and predictive capabilities. Developments on climate science allow advancing our understanding and prediction of the variability and change of Earth's climate on all space and time scales, while improving skilful climate assessments and tools for dealing with future challenges of a warming planet. However the availability of greater datasets amplifies the complexity on manipulation, representation and consequent analysis and interpretation of such datasets. Today the challenge is to translate scientific understanding of the climate system into climate information for society and decision makers. Here we discuss the development of an integration tool for multidisciplinary research, which allows access, management, tailored pre-processing and visualization of datasets, crucial to foster research as a service to society. One application is the assessment and monitoring of renewable energy variability, such as wind or solar energy, at several time and space scales. We demonstrate the ability of the e-science platform for planning, monitoring and management of renewable energy, particularly offshore wind energy in the Euro-Atlantic region. Further we explore the automatization of processes using different domains and datasets, which facilitate further research in evaluating and understanding renewable energy variability. AcknowledgementsThis work is supported by Foundation for Science and Technology (FCT), Portugal, project UID/GEO/50019/2013 - Instituto Dom Luiz.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23097130','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23097130"><span>The influence of global climate change on the scientific foundations and applications of Environmental Toxicology and Chemistry: introduction to a SETAC international workshop.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Stahl, Ralph G; Hooper, Michael J; Balbus, John M; Clements, William; Fritz, Alyce; Gouin, Todd; Helm, Roger; Hickey, Christopher; Landis, Wayne; Moe, S Jannicke</p> <p>2013-01-01</p> <p>This is the first of seven papers resulting from a Society of Environmental Toxicology and Chemistry (SETAC) international workshop titled "The Influence of Global Climate Change on the Scientific Foundations and Applications of Environmental Toxicology and Chemistry." The workshop involved 36 scientists from 11 countries and was designed to answer the following question: How will global climate change influence the environmental impacts of chemicals and other stressors and the way we assess and manage them in the environment? While more detail is found in the complete series of articles, some key consensus points are as follows: (1) human actions (including mitigation of and adaptation to impacts of global climate change [GCC]) may have as much influence on the fate and distribution of chemical contaminants as does GCC, and modeled predictions should be interpreted cautiously; (2) climate change can affect the toxicity of chemicals, but chemicals can also affect how organisms acclimate to climate change; (3) effects of GCC may be slow, variable, and difficult to detect, though some populations and communities of high vulnerability may exhibit responses sooner and more dramatically than others; (4) future approaches to human and ecological risk assessments will need to incorporate multiple stressors and cumulative risks considering the wide spectrum of potential impacts stemming from GCC; and (5) baseline/reference conditions for estimating resource injury and restoration/rehabilitation will continually shift due to GCC and represent significant challenges to practitioners. Copyright © 2013 SETAC.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70041965','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70041965"><span>The influence of global climate change on the scientific foundations and applications of Environmental Toxicology and Chemistry: Introduction to a SETAC international workshop</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Stahl, Ralph G.; Hooper, Michael J.; Balbus, John M.; Clements, William; Fritz, Alyce; Gouin, Todd; Helm, Roger; Hickey, Christopher; Landis, Wayne; Moe, S. Jannicke</p> <p>2013-01-01</p> <p>This is the first of seven papers resulting from a Society of Environmental Toxicology and Chemistry (SETAC) international workshop titled “The Influence of Global Climate Change on the Scientific Foundations and Applications of Environmental Toxicology and Chemistry.” The workshop involved 36 scientists from 11 countries and was designed to answer the following question: How will global climate change influence the environmental impacts of chemicals and other stressors and the way we assess and manage them in the environment? While more detail is found in the complete series of articles, some key consensus points are as follows: (1) human actions (including mitigation of and adaptation to impacts of global climate change [GCC]) may have as much influence on the fate and distribution of chemical contaminants as does GCC, and modeled predictions should be interpreted cautiously; (2) climate change can affect the toxicity of chemicals, but chemicals can also affect how organisms acclimate to climate change; (3) effects of GCC may be slow, variable, and difficult to detect, though some populations and communities of high vulnerability may exhibit responses sooner and more dramatically than others; (4) future approaches to human and ecological risk assessments will need to incorporate multiple stressors and cumulative risks considering the wide spectrum of potential impacts stemming from GCC; and (5) baseline/reference conditions for estimating resource injury and restoration/rehabilitation will continually shift due to GCC and represent significant challenges to practitioners.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29747612','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29747612"><span>Assessing safety climate in acute hospital settings: a systematic review of the adequacy of the psychometric properties of survey measurement tools.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Alsalem, Gheed; Bowie, Paul; Morrison, Jillian</p> <p>2018-05-10</p> <p>The perceived importance of safety culture in improving patient safety and its impact on patient outcomes has led to a growing interest in the assessment of safety climate in healthcare organizations; however, the rigour with which safety climate tools were developed and psychometrically tested was shown to be variable. This paper aims to identify and review questionnaire studies designed to measure safety climate in acute hospital settings, in order to assess the adequacy of reported psychometric properties of identified tools. A systematic review of published empirical literature was undertaken to examine sample characteristics and instrument details including safety climate dimensions, origin and theoretical basis, and extent of psychometric evaluation (content validity, criterion validity, construct validity and internal reliability). Five questionnaire tools, designed for general evaluation of safety climate in acute hospital settings, were included. Detailed inspection revealed ambiguity around concepts of safety culture and climate, safety climate dimensions and the methodological rigour associated with the design of these measures. Standard reporting of the psychometric properties of developed questionnaires was variable, although evidence of an improving trend in the quality of the reported psychometric properties of studies was noted. Evidence of the theoretical underpinnings of climate tools was limited, while a lack of clarity in the relationship between safety culture and patient outcome measures still exists. Evidence of the adequacy of the psychometric development of safety climate questionnaire tools is still limited. Research is necessary to resolve the controversies in the definitions and dimensions of safety culture and climate in healthcare and identify related inconsistencies. More importance should be given to the appropriate validation of safety climate questionnaires before extending their usage in healthcare contexts different from those in which they were originally developed. Mixed methods research to understand why psychometric assessment and measurement reporting practices can be inadequate and lacking in a theoretical basis is also necessary.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1379852-attribution-julyaugust-heat-event-central-eastern-china-anthropogenic-greenhouse-gas-emissions','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1379852-attribution-julyaugust-heat-event-central-eastern-china-anthropogenic-greenhouse-gas-emissions"><span>Attribution of the July–August 2013 heat event in Central and Eastern China to anthropogenic greenhouse gas emissions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Ma, Shuangmei; Zhou, Tianjun; Stone, Dáithí A.; ...</p> <p>2017-05-19</p> <p>In the midsummer of 2013, Central and Eastern China (CEC) was hit by an extraordinary heat event, with the region experiencing the warmest July-August on record. To explore how human-induced greenhouse gas emissions and natural internal variability contributed to this heat event, we compare observed July-August mean surface air temperature wit h that simulated by climate models. We find that both atmospheric natural variability and anthropogenic factors contributed to this heat event. This extreme warm midsummer was associated with a positive high-pressure anomaly that was closely related to the stochastic behavior of atmospheric circulation. Diagnosis of CMIP5 models and largemore » ensembles of two atmospheric models indicates that human influence has substantially increased the chance of warm mid-summers such as 2013 in CEC, although the exact estimated increase depends on the selection of climate models.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1379852','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1379852"><span>Attribution of the July–August 2013 heat event in Central and Eastern China to anthropogenic greenhouse gas emissions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Ma, Shuangmei; Zhou, Tianjun; Stone, Dáithí A.</p> <p></p> <p>In the midsummer of 2013, Central and Eastern China (CEC) was hit by an extraordinary heat event, with the region experiencing the warmest July-August on record. To explore how human-induced greenhouse gas emissions and natural internal variability contributed to this heat event, we compare observed July-August mean surface air temperature wit h that simulated by climate models. We find that both atmospheric natural variability and anthropogenic factors contributed to this heat event. This extreme warm midsummer was associated with a positive high-pressure anomaly that was closely related to the stochastic behavior of atmospheric circulation. Diagnosis of CMIP5 models and largemore » ensembles of two atmospheric models indicates that human influence has substantially increased the chance of warm mid-summers such as 2013 in CEC, although the exact estimated increase depends on the selection of climate models.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23722925','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23722925"><span>Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Modarres, Reza; Ouarda, Taha B M J; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre</p> <p>2014-07-01</p> <p>Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMAX-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56% of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014IJBm...58..921M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014IJBm...58..921M"><span>Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Modarres, Reza; Ouarda, Taha B. M. J.; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre</p> <p>2014-07-01</p> <p>Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMA X-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56 % of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.1085K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.1085K"><span>Pacific-Australia Climate Change Science and Adaptation Planning program: supporting climate science and enhancing climate services in Pacific Island Countries</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kuleshov, Yuriy; Jones, David; Hendon, Harry; Charles, Andrew; Shelton, Kay; de Wit, Roald; Cottrill, Andrew; Nakaegawa, Toshiyuki; Atalifo, Terry; Prakash, Bipendra; Seuseu, Sunny; Kaniaha, Salesa</p> <p>2013-04-01</p> <p>Over the past few years, significant progress in developing climate science for the Pacific has been achieved through a number of research projects undertaken under the Australian government International Climate Change Adaptation Initiative (ICCAI). Climate change has major impact on Pacific Island Countries and advancement in understanding past, present and futures climate in the region is vital for island nation to develop adaptation strategies to their rapidly changing environment. This new science is now supporting new services for a wide range of stakeholders in the Pacific through the National Meteorological Agencies of the region. Seasonal climate prediction is particularly important for planning in agriculture, tourism and other weather-sensitive industries, with operational services provided by all National Meteorological Services in the region. The interaction between climate variability and climate change, for example during droughts or very warm seasons, means that much of the early impacts of climate change are being felt through seasonal variability. A means to reduce these impacts is to improve forecasts to support decision making. Historically, seasonal climate prediction has been developed based on statistical past relationship. Statistical methods relate meteorological variables (e.g. temperature and rainfall) to indices which describe large-scale environment (e.g. ENSO indices) using historical data. However, with observed climate change, statistical approaches based on historical data are getting less accurate and less reliable. Recognising the value of seasonal forecasts, we have used outputs of a dynamical model POAMA (Predictive Ocean Atmosphere Model for Australia), to develop web-based information tools (http://poama.bom.gov.au/experimental/pasap/index.shtml) which are now used by climate services in 15 partner countries in the Pacific for preparing seasonal climate outlooks. Initial comparison conducted during 2012 has shown that the predictive skill of POAMA is consistently higher than skill of statistical-based method. Presently, under the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) program, we are developing dynamical model-based seasonal climate prediction for climate extremes. Of particular concern are tropical cyclones which are the most destructive weather systems that impact on coastal areas of Australia and Pacific Island Countries. To analyse historical cyclone data, we developed a consolidate archive for the Southern Hemisphere and North-Western Pacific (http://www.bom.gov.au/cyclone/history/tracks/). Using dynamical climate models (POAMA and Japan Meteorological Agency's model), we work on improving accuracy of seasonal forecasts of tropical cyclone activity for the regions of Western Pacific. Improved seasonal climate prediction based on dynamical models will further enhance climate services in Australia and Pacific Island Countries.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001JCli...14.3017L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001JCli...14.3017L"><span>Seasonal Predictability in a Model Atmosphere.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lin, Hai</p> <p>2001-07-01</p> <p>The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28924607','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28924607"><span>Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Foreman, Brady Z; Straub, Kyle M</p> <p>2017-09-01</p> <p>Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 10 4 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3621426','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3621426"><span>Surface changes in the North Atlantic meridional overturning circulation during the last millennium</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Wanamaker, Alan D.; Butler, Paul G.; Scourse, James D.; Heinemeier, Jan; Eiríksson, Jón; Knudsen, Karen Luise; Richardson, Christopher A.</p> <p>2012-01-01</p> <p>Despite numerous investigations, the dynamical origins of the Medieval Climate Anomaly and the Little Ice Age remain uncertain. A major unresolved issue relating to internal climate dynamics is the mode and tempo of Atlantic meridional overturning circulation variability, and the significance of decadal-to-centennial scale changes in Atlantic meridional overturning circulation strength in regulating the climate of the last millennium. Here we use the time-constrained high-resolution local radiocarbon reservoir age offset derived from an absolutely dated annually resolved shell chronology spanning the past 1,350 years, to reconstruct changes in surface ocean circulation and climate. The water mass tracer data presented here from the North Icelandic shelf, combined with previously published data from the Arctic and subtropical Atlantic, show that surface Atlantic meridional overturning circulation dynamics likely amplified the relatively warm conditions during the Medieval Climate Anomaly and the relatively cool conditions during the Little Ice Age within the North Atlantic sector. PMID:22692542</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22692542','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22692542"><span>Surface changes in the North Atlantic meridional overturning circulation during the last millennium.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wanamaker, Alan D; Butler, Paul G; Scourse, James D; Heinemeier, Jan; Eiríksson, Jón; Knudsen, Karen Luise; Richardson, Christopher A</p> <p>2012-06-12</p> <p>Despite numerous investigations, the dynamical origins of the Medieval Climate Anomaly and the Little Ice Age remain uncertain. A major unresolved issue relating to internal climate dynamics is the mode and tempo of Atlantic meridional overturning circulation variability, and the significance of decadal-to-centennial scale changes in Atlantic meridional overturning circulation strength in regulating the climate of the last millennium. Here we use the time-constrained high-resolution local radiocarbon reservoir age offset derived from an absolutely dated annually resolved shell chronology spanning the past 1,350 years, to reconstruct changes in surface ocean circulation and climate. The water mass tracer data presented here from the North Icelandic shelf, combined with previously published data from the Arctic and subtropical Atlantic, show that surface Atlantic meridional overturning circulation dynamics likely amplified the relatively warm conditions during the Medieval Climate Anomaly and the relatively cool conditions during the Little Ice Age within the North Atlantic sector.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5597307','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5597307"><span>Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Foreman, Brady Z.; Straub, Kyle M.</p> <p>2017-01-01</p> <p>Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 104 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation. PMID:28924607</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110013375','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110013375"><span>Influence of an Internally-Generated QBO on Modeled Stratospheric Dynamics and Ozone</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hurwitz, M. M.; Newman, P. A.; Song, I. S.</p> <p>2011-01-01</p> <p>A GEOS V2 CCM simulation with an internally generated quasi-biennial oscillation (QBO) signal is compared to an otherwise identical simulation without a QBO. In a present-day climate, inclusion of the modeled QBO makes a significant difference to stratospheric dynamics and ozone throughout the year. The QBO enhances variability in the tropics, as expected, but also in the polar stratosphere in some seasons. The modeled QBO also affects the mean stratospheric climate. Because tropical zonal winds in the baseline simulation are generally easterly, there is a relative increase in zonal wind magnitudes in tropical lower and middle stratosphere in the QBO simulation. Extra-tropical differences between the QBO and 'no QBO' simulations thus reflect a bias toward the westerly phase of the QBO: a relative strengthening and poleward shifting the polar stratospheric jets, and a reduction in Arctic lower stratospheric ozone.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.8691S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.8691S"><span>Using Spacecraft in Climate and Natural Disasters Registration</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sokol, Galyna; Kotlov, Vladyslav; Khorischenko, Oleksandr; Davydova, Angelica; Heti, Kristina</p> <p>2017-04-01</p> <p>Since the beginning of the space age it become possible the global monitoring of the planet Earth's state. Since the second half of the 20th century there are observations of the atmosphere's state and the Earth's climate have been held by a spacecraft. Also become possible large-scale monitoring of climate change. An attempt was made to define the role of infrasound in the interaction between a space weather, climate and biosphere of the Earth using spacecraft sensors recording. Many countries are involving in the detection of earthquakes, predicting volcanic eruptions and floods and also the monitoring of irregular solar activity. Understanding this leads to the conclusion that international cooperation for the protection of humanity is not only a political priority in the international arena, but also a question of the quality of living standards of any state. Commonly known following monitoring systems: Disaster Monitoring Constellation (DMC), FUEGO program (Spain), Sentinel-Asia program (Japan) and International aerospace system for monitoring of global phenomena (MAKCM, Russia). The Disaster Monitoring Constellation for International Imaging (DMCii) consists of a number of remote sensing satellites constructed by Surrey Satellite Technology Ltd (SSTL) and operated for the Algerian, Nigerian, Turkish, British and Chinese governments by DMC International Imaging. The DMC has monitored the effects and aftermath of the Indian Ocean Tsunami (December 2004), Hurricane Katrina (August 2005), and many other floods, fires and disasters. The individual DMC satellites are: 1. First generation satellites (AlSAT-1 - Algeria, BilSAT - Turkey, NigeriaSAT-1 - Nigeria, UK-DMC - United Kingdom); 2. Second generation satellites (Beijing - China, UK-DMC 2 - United Kingdom, Deimos-1 - Spanish commercial, NigeriaSAT-2 and NigeriaSAT-X). The sun-synchronous orbits of these satellites are coordinated so that the satellites follow each other around an orbital plane, ascending north over the Equator at 10:15 am local time (and 10:30 am local time for Beijing-1). Some of these satellites also include other imaging payloads and experimental payloads: onboard hardware-based image compression (on BilSAT), a GPS reflectometry experiment and onboard Internet router (on the UK-DMC satellite). The DMC satellites are notable for communicating with their ground stations using the Internet Protocol for payload data transfer and command and control, so extending the Internet into space, and allowing experiments with the Interplanetary Internet to be carried out. Many of the technologies used in the design of the DMC satellites, including Internet Protocol use, were tested in space beforehand on SSTL's earlier UoSAT-12 satellite. Currently, there is a great need to establish combining space and ground-based observation systems that will accurately capture key climate variables on a scale from regional to global and stable functioning for decades to determine climate variability and trends. With the help of modern computer systems were calculated moving of infrasonic waves in the atmosphere. This data can be used to predict the weather.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1764156','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1764156"><span>Assessment of Human Health Vulnerability to Climate Variability and Change in Cuba</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Bultó, Paulo Lázaro Ortíz; Rodríguez, Antonio Pérez; Valencia, Alina Rivero; Vega, Nicolás León; Gonzalez, Manuel Díaz; Carrera, Alina Pérez</p> <p>2006-01-01</p> <p>In this study we assessed the potential effects of climate variability and change on population health in Cuba. We describe the climate of Cuba as well as the patterns of climate-sensitive diseases of primary concern, particularly dengue fever. Analyses of the associations between climatic anomalies and disease patterns highlight current vulnerability to climate variability. We describe current adaptations, including the application of climate predictions to prevent disease outbreaks. Finally, we present the potential economic costs associated with future impacts due to climate change. The tools used in this study can be useful in the development of appropriate and effective adaptation options to address the increased climate variability associated with climate change. PMID:17185289</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/53945','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/53945"><span>Climate variability drives population cycling and synchrony</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Lars Y. Pomara; Benjamin Zuckerberg</p> <p>2017-01-01</p> <p>Aim There is mounting concern that climate change will lead to the collapse of cyclic population dynamics, yet the influence of climate variability on population cycling remains poorly understood. We hypothesized that variability in survival and fecundity, driven by climate variability at different points in the life cycle, scales up from...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.3653R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.3653R"><span>Impact of external forcing on simulated hydroclimate from interannual to multicentennial timescales</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roldán, Pedro; Fidel González-Rouco, Jesús; Melo-Aguilar, Camilo</p> <p>2017-04-01</p> <p>During the last millennium, external forcing experienced important changes in different timescales. It has been demostrated that these changes had an impact on climate. In particular, changes in solar activity, volcanic eruptions and emissions of greenhouse gases are related to short-term and long-term changes in global temperatures, with situations of higher total external forcing generally related with higher global and hemispherical temperatures, and conversely with situations of lower forcing. This connection is clearly observed in climate simulations from different models and in proxy-based reconstructions. The changes in external forcing can also explain certain changes in atmospheric dynamics and hydroclimate, although in this case it is in general more difficult to trace causality arguments. Analyses based on simulations from two different models (ECHO-G and CESM-LME) have been performed, to assess the impact of external forcing on climate in timescales ranging from interannual to multicentennial. Various climatic variables have been analysed, including temperature, sea level pressure, surface wind, precipitation and soil moisture. For interannual timescales, composites have been defined with the years before and after the main volcanic eruptions of the last millennium as well as the minima of solar activity during this period. For longer timescales, a Principal Component analysis has been performed, to try to separate the signal of external forcing from that of internal variability. This has been done for the whole millennium and for the pre-industrial period, to assess the difference between natural and anthropogenic forcing. For multicentennial timescales, composites for the Medieval Climate Anomaly (MCA; ca. 950-1250), the Little Ice Age (LIA; ca. 1450-1850) and the 20th Century have been compared. These three periods were respectively characterised by higher, lower and higher forcing. This allows to assess the contribution of external forcing to the evolution of climate over longer time intervals. These analyses have shown that external forcing is an important factor in the evolution of the simulated hydroclimate of the last millennium. In the short-term, it has been observed that volcanic eruptions and other situations of extreme forcing significantly alter the global precipitation in the subsequent years. In the long-term, variations of external forcing can be related to changes in atmospheric dynamics and in hydroclimate. However, this impact is not homogeneously distributed. There are areas where hydroclimate is mainly influenced by the external forcing and other areas more influenced by internal variability, with spatial decorrelation being higher in precipitation or drought related variables than in temperature. The regional sensitivity to external forcing of hydroclimate is model and, to a lesser degree, simulation dependent.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C44A..07D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C44A..07D"><span>Bayesian prediction of future ice sheet volume using local approximation Markov chain Monte Carlo methods</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Davis, A. D.; Heimbach, P.; Marzouk, Y.</p> <p>2017-12-01</p> <p>We develop a Bayesian inverse modeling framework for predicting future ice sheet volume with associated formal uncertainty estimates. Marine ice sheets are drained by fast-flowing ice streams, which we simulate using a flowline model. Flowline models depend on geometric parameters (e.g., basal topography), parameterized physical processes (e.g., calving laws and basal sliding), and climate parameters (e.g., surface mass balance), most of which are unknown or uncertain. Given observations of ice surface velocity and thickness, we define a Bayesian posterior distribution over static parameters, such as basal topography. We also define a parameterized distribution over variable parameters, such as future surface mass balance, which we assume are not informed by the data. Hyperparameters are used to represent climate change scenarios, and sampling their distributions mimics internal variation. For example, a warming climate corresponds to increasing mean surface mass balance but an individual sample may have periods of increasing or decreasing surface mass balance. We characterize the predictive distribution of ice volume by evaluating the flowline model given samples from the posterior distribution and the distribution over variable parameters. Finally, we determine the effect of climate change on future ice sheet volume by investigating how changing the hyperparameters affects the predictive distribution. We use state-of-the-art Bayesian computation to address computational feasibility. Characterizing the posterior distribution (using Markov chain Monte Carlo), sampling the full range of variable parameters and evaluating the predictive model is prohibitively expensive. Furthermore, the required resolution of the inferred basal topography may be very high, which is often challenging for sampling methods. Instead, we leverage regularity in the predictive distribution to build a computationally cheaper surrogate over the low dimensional quantity of interest (future ice sheet volume). Continual surrogate refinement guarantees asymptotic sampling from the predictive distribution. Directly characterizing the predictive distribution in this way allows us to assess the ice sheet's sensitivity to climate variability and change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.2845F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.2845F"><span>Modes of interannual variability in northern hemisphere winter atmospheric circulation in CMIP5 models: evaluation, projection and role of external forcing</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Frederiksen, Carsten S.; Ying, Kairan; Grainger, Simon; Zheng, Xiaogu</p> <p>2018-04-01</p> <p>Models from the coupled model intercomparison project phase 5 (CMIP5) dataset are evaluated for their ability to simulate the dominant slow modes of interannual variability in the Northern Hemisphere atmospheric circulation 500 hPa geopotential height in the twentieth century. A multi-model ensemble of the best 13 models has then been used to identify the leading modes of interannual variability in components related to (1) intraseasonal processes; (2) slowly-varying internal dynamics; and (3) the slowly-varying response to external changes in radiative forcing. Modes in the intraseasonal component are related to intraseasonal variability in the North Atlantic, North Pacific and North American, and Eurasian regions and are little affected by the larger radiative forcing of the Representative Concentration Pathways 8.5 (RCP8.5) scenario. The leading modes in the slow-internal component are related to the El Niño-Southern Oscillation, Pacific North American or Tropical Northern Hemisphere teleconnection, the North Atlantic Oscillation, and the Western Pacific teleconnection pattern. While the structure of these slow-internal modes is little affected by the larger radiative forcing of the RCP8.5 scenario, their explained variance increases in the warmer climate. The leading mode in the slow-external component has a significant trend and is shown to be related predominantly to the climate change trend in the well mixed greenhouse gas concentration during the historical period. This mode is associated with increasing height in the 500 hPa pressure level. A secondary influence on this mode is the radiative forcing due to stratospheric aerosols associated with volcanic eruptions. The second slow-external mode is shown to be also related to radiative forcing due to stratospheric aerosols. Under RCP8.5 there is only one slow-external mode related to greenhouse gas forcing with a trend over four times the historical trend.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NatSR...621251D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NatSR...621251D"><span>The Footprint of the Inter-decadal Pacific Oscillation in Indian Ocean Sea Surface Temperatures</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dong, Lu; Zhou, Tianjun; Dai, Aiguo; Song, Fengfei; Wu, Bo; Chen, Xiaolong</p> <p>2016-02-01</p> <p>Superimposed on a pronounced warming trend, the Indian Ocean (IO) sea surface temperatures (SSTs) also show considerable decadal variations that can cause regional climate oscillations around the IO. However, the mechanisms of the IO decadal variability remain unclear. Here we perform numerical experiments using a state-of-the-art, fully coupled climate model in which the external forcings with or without the observed SSTs in the tropical eastern Pacific Ocean (TEP) are applied for 1871-2012. Both the observed timing and magnitude of the IO decadal variations are well reproduced in those experiments with the TEP SSTs prescribed to observations. Although the external forcings account for most of the warming trend, the decadal variability in IO SSTs is dominated by internal variability that is induced by the TEP SSTs, especially the Inter-decadal Pacific Oscillation (IPO). The IPO weakens (enhances) the warming of the external forcings by about 50% over the IO during IPO’s cold (warm) phase, which contributes about 10% to the recent global warming hiatus since 1999. The decadal variability in IO SSTs is modulated by the IPO-induced atmospheric adjustment through changing surface heat fluxes, sea surface height and thermocline depth.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26884089','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26884089"><span>The Footprint of the Inter-decadal Pacific Oscillation in Indian Ocean Sea Surface Temperatures.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Dong, Lu; Zhou, Tianjun; Dai, Aiguo; Song, Fengfei; Wu, Bo; Chen, Xiaolong</p> <p>2016-02-17</p> <p>Superimposed on a pronounced warming trend, the Indian Ocean (IO) sea surface temperatures (SSTs) also show considerable decadal variations that can cause regional climate oscillations around the IO. However, the mechanisms of the IO decadal variability remain unclear. Here we perform numerical experiments using a state-of-the-art, fully coupled climate model in which the external forcings with or without the observed SSTs in the tropical eastern Pacific Ocean (TEP) are applied for 1871-2012. Both the observed timing and magnitude of the IO decadal variations are well reproduced in those experiments with the TEP SSTs prescribed to observations. Although the external forcings account for most of the warming trend, the decadal variability in IO SSTs is dominated by internal variability that is induced by the TEP SSTs, especially the Inter-decadal Pacific Oscillation (IPO). The IPO weakens (enhances) the warming of the external forcings by about 50% over the IO during IPO's cold (warm) phase, which contributes about 10% to the recent global warming hiatus since 1999. The decadal variability in IO SSTs is modulated by the IPO-induced atmospheric adjustment through changing surface heat fluxes, sea surface height and thermocline depth.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMEP53A0754C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMEP53A0754C"><span>Development and Implementation of Flood Risk Mapping, Water Bodies Monitoring and Climate Information for Human Health</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ceccato, P.; McDonald, K. C.; Jensen, K.; Podest, E.; De La Torre Juarez, M.</p> <p>2013-12-01</p> <p>Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI), City College of New York (CCNY) and NASA Jet Propulsion Laboratory (JPL) are developing new products to increase the public health community's capacity to understand, use, and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on vector-borne diseases such as malaria, leishmaniasis, rift valley fever. In this poster we present the new and improved products that have been developed for monitoring water bodies for monitoring and forecasting risks of vector-borne disease epidemics. The products include seasonal inundation patterns in the East African region based on the global mappings of inundated water fraction derived at the 25-km scale from both active and passive microwave instruments QuikSCAT, AMSR-E, SSM/I, ERS, ASCAT, and MODIS and LANDSAT data. We also present how the products are integrated into a knowledge system (IRI Data Library Map room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4685260','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4685260"><span>Sensitivity of proxies on non-linear interactions in the climate system</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Schultz, Johannes A.; Beck, Christoph; Menz, Gunter; Neuwirth, Burkhard; Ohlwein, Christian; Philipp, Andreas</p> <p>2015-01-01</p> <p>Recent climate change is affecting the earth system to an unprecedented extent and intensity and has the potential to cause severe ecological and socioeconomic consequences. To understand natural and anthropogenic induced processes, feedbacks, trends, and dynamics in the climate system, it is also essential to consider longer timescales. In this context, annually resolved tree-ring data are often used to reconstruct past temperature or precipitation variability as well as atmospheric or oceanic indices such as the North Atlantic Oscillation (NAO) or the Atlantic Multidecadal Oscillation (AMO). The aim of this study is to assess weather-type sensitivity across the Northern Atlantic region based on two tree-ring width networks. Our results indicate that nonstationarities in superordinate space and time scales of the climate system (here synoptic- to global scale, NAO, AMO) can affect the climate sensitivity of tree-rings in subordinate levels of the system (here meso- to synoptic scale, weather-types). This scale bias effect has the capability to impact even large multiproxy networks and the ability of these networks to provide information about past climate conditions. To avoid scale biases in climate reconstructions, interdependencies between the different scales in the climate system must be considered, especially internal ocean/atmosphere dynamics. PMID:26686001</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC33H..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC33H..01S"><span>PERSIANN-CDR Daily Precipitation Dataset for Hydrologic Applications and Climate Studies.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sorooshian, S.; Hsu, K. L.; Ashouri, H.; Braithwaite, D.; Nguyen, P.; Thorstensen, A. R.</p> <p>2015-12-01</p> <p>Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network - Climate Data Record (PERSIANN-CDR) is a newly developed and released dataset which covers more than 3 decades (01/01/1983 - 03/31/2015 to date) of daily precipitation estimations at 0.25° resolution for 60°S-60°N latitude band. PERSIANN-CDR is processed using the archive of the Gridded Satellite IRWIN CDR (GridSat-B1) from the International Satellite Cloud Climatology Project (ISCCP), and the Global Precipitation Climatology Project (GPCP) 2.5° monthly product for bias correction. The dataset has been released and made available for public access through NOAA's National Centers for Environmental Information (NCEI) (http://www1.ncdc.noaa.gov/pub/data/sds/cdr/CDRs/PERSIANN/Overview.pdf). PERSIANN-CDR has already shown its usefulness for a wide range of applications, including climate variability and change monitoring, hydrologic applications, and water resources system planning and management. This precipitation CDR data has also been used in studying the behavior of historical extreme precipitation events. Demonstration of PERSIANN-CDR data in detecting trends and variability of precipitation over the past 30 years, the potential usefulness of the dataset for evaluating climate model performance relevant to precipitation in retrospective mode, will be presented.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150021055','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150021055"><span>Interactions of Mean Climate Change and Climate Variability on Food Security Extremes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.</p> <p>2015-01-01</p> <p>Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030014739','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030014739"><span>Information Theoretic Approaches to Rapid Discovery of Relationships in Large Climate Data Sets</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Knuth, Kevin H.; Rossow, William B.; Clancy, Daniel (Technical Monitor)</p> <p>2002-01-01</p> <p>Mutual information as the asymptotic Bayesian measure of independence is an excellent starting point for investigating the existence of possible relationships among climate-relevant variables in large data sets, As mutual information is a nonlinear function of of its arguments, it is not beholden to the assumption of a linear relationship between the variables in question and can reveal features missed in linear correlation analyses. However, as mutual information is symmetric in its arguments, it only has the ability to reveal the probability that two variables are related. it provides no information as to how they are related; specifically, causal interactions or a relation based on a common cause cannot be detected. For this reason we also investigate the utility of a related quantity called the transfer entropy. The transfer entropy can be written as a difference between mutual informations and has the capability to reveal whether and how the variables are causally related. The application of these information theoretic measures is rested on some familiar examples using data from the International Satellite Cloud Climatology Project (ISCCP) to identify relation between global cloud cover and other variables, including equatorial pacific sea surface temperature (SST), over seasonal and El Nino Southern Oscillation (ENSO) cycles.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.3221P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.3221P"><span>Mechanisms Controlling Global Mean Sea Surface Temperature Determined From a State Estimate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ponte, R. M.; Piecuch, C. G.</p> <p>2018-04-01</p> <p>Global mean sea surface temperature (T¯) is a variable of primary interest in studies of climate variability and change. The temporal evolution of T¯ can be influenced by surface heat fluxes (F¯) and by diffusion (D¯) and advection (A¯) processes internal to the ocean, but quantifying the contribution of these different factors from data alone is prone to substantial uncertainties. Here we derive a closed T¯ budget for the period 1993-2015 based on a global ocean state estimate, which is an exact solution of a general circulation model constrained to most extant ocean observations through advanced optimization methods. The estimated average temperature of the top (10-m thick) level in the model, taken to represent T¯, shows relatively small variability at most time scales compared to F¯, D¯, or A¯, reflecting the tendency for largely balancing effects from all the latter terms. The seasonal cycle in T¯ is mostly determined by small imbalances between F¯ and D¯, with negligible contributions from A¯. While D¯ seems to simply damp F¯ at the annual period, a different dynamical role for D¯ at semiannual period is suggested by it being larger than F¯. At periods longer than annual, A¯ contributes importantly to T¯ variability, pointing to the direct influence of the variable ocean circulation on T¯ and mean surface climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.5625M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.5625M"><span>Statistical attribution of mid-term droughts in central Europe</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mikšovský, Jiří; Trnka, Miroslav; Brázdil, Rudolf</p> <p>2017-04-01</p> <p>Occurrence and intensity of meteorological droughts are determined by a number of factors, both anthropogenic and natural. Besides the trend-like components, often attributable to local or global man-induced changes to the climate system, manifestations of internal climate oscillatory modes are also of great importance in establishing the hydrological regime. In this presentation, we focus on identification and quantification of factors responsible for central European drought variability at seasonal time scales. Using multivariable regression analysis applied to predictands reflecting various definitions of meteorological droughts (based on Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index and Palmer's Z-index, over the 1883-2010 period), components attributable to external and internal climate-forming agents are extracted and evaluated with regard to their statistical significance. Our results confirm presence of strong links of central European droughts to the anthropogenic radiative forcing and to the phase of the North Atlantic Oscillation, but also existence of connections to the climate oscillations originating from the Pacific area. In this context, we demonstrate that prominence of components related to the phase of the Pacific Decadal Oscillation generally surpasses that of El Niño - Southern Oscillation, although the related transfer mechanisms still remain unclear. Finally, it is shown that noteworthy deviations from linearity exist in some of the drought responses, particularly for the effects of the North Atlantic Oscillation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018E%26ES..129a2038L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018E%26ES..129a2038L"><span>The precautionary principle in fisheries management under climate change: How the international legal framework formulate it?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Latifah, E.; Imanullah, M. N.</p> <p>2018-03-01</p> <p>One of the objectives of fisheries management is to reach long-term sustainable benefits of the fish stocks while reducing the risk of severe or irreversible damage to the marine ecosystem. Achieving this objective needs, the good scientific knowledge and understanding on fisheries management including scientific data and information on the fish stock, fishing catch, distribution, migration, the proportion of mature fish, the mortality rate, reproduction as well as the knowledge on the impact of fishing on dependent and associated species and other species belonging to the same ecosystem, and further the impact of climate change and climate variability on the fish stocks and marine ecosystem. Lack of this scientific knowledge may lead to high levels of uncertainty. The precautionary principle is one of the basic environmental principles needed in overcoming this problem. An essence of this principle is that, in facing the serious risk as a result of the limited scientific knowledge or the absence of complete evidence of harm, it should not prevent the precautionary measures in minimizing risks and protecting the fish stocks and ecosystem. This study aims to examine how the precautionary principle in fisheries management be formulated into the international legal framework, especially under the climate change framework.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUSMIN32A..02D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUSMIN32A..02D"><span>The Integrating Role of the LBA and the LPB Programs as an Example of Cyberinfrastructures in International Scientific Collaboration</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dias, P. L.</p> <p>2007-05-01</p> <p>International science collaboration is a key component of research programs such as the The Large Scale Biosphere Atmosphere Interaction Program (LBA) and the La Plata Basin Project (LPB). Both are programs with crosscutting science questions permeating different areas of knowledge related to the functioning of the natural and agricultural ecosystems in the Amazon system (LBA) and the change in the hydrological, agricultural and social systems of the Plata Basin (LPB) ecosystem under natural climatic variability and climate change. Both programs are strongly related to GEWEX, CLIVAR and IGBP and are based on extensive use of data information system (LBA/LPB/DIS) with mirror sites in the US, Europe and South America. These international programs have a significant impact in building up regional scientific capabilities at all levels of education and triggered the establishment of new research groups located in remote areas of South America. The cyberinfrastructure has been fundamental to promote the integration of the research groups, and a remarkable feedback with the operational forecasting systems has been detected. The LBA/LPB should be used as examples on how to promote international scientific and operational collaboration.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016QSRv..136..229X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016QSRv..136..229X"><span>The Medieval Climate Anomaly and Byzantium: A review of the evidence on climatic fluctuations, economic performance and societal change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xoplaki, Elena; Fleitmann, Dominik; Luterbacher, Juerg; Wagner, Sebastian; Haldon, John F.; Zorita, Eduardo; Telelis, Ioannis; Toreti, Andrea; Izdebski, Adam</p> <p>2016-03-01</p> <p>At the beginning of the Medieval Climate Anomaly, in the ninth and tenth century, the medieval eastern Roman empire, more usually known as Byzantium, was recovering from its early medieval crisis and experiencing favourable climatic conditions for the agricultural and demographic growth. Although in the Balkans and Anatolia such favourable climate conditions were prevalent during the eleventh century, parts of the imperial territories were facing significant challenges as a result of external political/military pressure. The apogee of medieval Byzantine socio-economic development, around AD 1150, coincides with a period of adverse climatic conditions for its economy, so it becomes obvious that the winter dryness and high climate variability at this time did not hinder Byzantine society and economy from achieving that level of expansion. Soon after this peak, towards the end of the twelfth century, the populations of the Byzantine world were experiencing unusual climatic conditions with marked dryness and cooler phases. The weakened Byzantine socio-political system must have contributed to the events leading to the fall of Constantinople in AD 1204 and the sack of the city. The final collapse of the Byzantine political control over western Anatolia took place half century later, thus contemporaneous with the strong cooling effect after a tropical volcanic eruption in AD 1257. We suggest that, regardless of a range of other influential factors, climate change was also an important contributing factor to the socio-economic changes that took place in Byzantium during the Medieval Climate Anomaly. Crucially, therefore, while the relatively sophisticated and complex Byzantine society was certainly influenced by climatic conditions, and while it nevertheless displayed a significant degree of resilience, external pressures as well as tensions within the Byzantine society more broadly contributed to an increasing vulnerability in respect of climate impacts. Our interdisciplinary analysis is based on all available sources of information on the climate and society of Byzantium, that is textual (documentary), archaeological, environmental, climate and climate model-based evidence about the nature and extent of climate variability in the eastern Mediterranean. The key challenge was, therefore, to assess the relative influence to be ascribed to climate variability and change on the one hand, and on the other to the anthropogenic factors in the evolution of Byzantine state and society (such as invasions, changes in international or regional market demand and patterns of production and consumption, etc.). The focus of this interdisciplinary study was to address the possible causal relationships between climatic and socio-economic change and to assess the resilience of the Byzantine socio-economic system in the context of climate change impacts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.4738X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.4738X"><span>The Medieval Climate Anomaly and Byzantium: A review of the evidence on climatic fluctuations, economic performance and societal change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xoplaki, Elena; Fleitmann, Dominik; Luterbacher, Juerg; Wagner, Sebastian; Haldon, John F.; Zorita, Eduardo; Telelis, Ioannis; Toreti, Andrea; Izdebski, Adam</p> <p>2016-04-01</p> <p>At the beginning of the Medieval Climate Anomaly, in the ninth and tenth century, the medieval eastern Roman empire, more usually known as Byzantium, was recovering from its early medieval crisis and experiencing favourable climatic conditions for the agricultural and demographic growth. Although in the Balkans and Anatolia such favourable climate conditions were prevalent during the eleventh century, parts of the imperial territories were facing significant challenges as a result of external political/military pressure. The apogee of medieval Byzantine socio-economic development, around AD 1150, coincides with a period of adverse climatic conditions for its economy, so it becomes obvious that the winter dryness and high climate variability at this time did not hinder Byzantine society and economy from achieving that level of expansion. Soon after this peak, towards the end of the twelfth century, the populations of the Byzantine world were experiencing unusual climatic conditions with marked dryness and cooler phases. The weakened Byzantine socio-political system must have contributed to the events leading to the fall of Constantinople in AD 1204 and the sack of the city. The final collapse of the Byzantine political control over western Anatolia took place half century later, thus contemporaneous with the strong cooling effect after a tropical volcanic eruption in AD 1257. We suggest that, regardless of a range of other influential factors, climate change was also an important contributing factor to the socio-economic changes that took place in Byzantium during the Medieval Climate Anomaly. Crucially, therefore, while the relatively sophisticated and complex Byzantine society was certainly influenced by climatic conditions, and while it nevertheless displayed a significant degree of resilience, external pressures as well as tensions within the Byzantine society more broadly contributed to an increasing vulnerability in respect of climate impacts. Our interdisciplinary analysis is based on all available sources of information on the climate and society of Byzantium, that is textual (documentary), archaeological, environmental, climate and climate model-based evidence about the nature and extent of climate variability in the eastern Mediterranean. The key challenge was, therefore, to assess the relative influence to be ascribed to climate variability and change on the one hand, and on the other to the anthropogenic factors in the evolution of Byzantine state and society (such as invasions, changes in international or regional market demand and patterns of production and consumption, etc.). The focus of this interdisciplinary study was to address the possible causal relationships between climatic and socio-economic change and to assess the resilience of the Byzantine socio-economic system in the context of climate change impacts.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy...49.3627W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy...49.3627W"><span>Variability of tropical cyclone rapid intensification in the North Atlantic and its relationship with climate variations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Chunzai; Wang, Xidong; Weisberg, Robert H.; Black, Michael L.</p> <p>2017-12-01</p> <p>The paper uses observational data from 1950 to 2014 to investigate rapid intensification (RI) variability of tropical cyclones (TCs) in the North Atlantic and its relationships with large-scale climate variations. RI is defined as a TC intensity increase of at least 15.4 m/s (30 knots) in 24 h. The seasonal RI distribution follows the seasonal TC distribution, with the highest number in September. Although an RI event can occur anywhere over the tropical North Atlantic (TNA), there are three regions of maximum RI occurrence: (1) the western TNA of 12°N-18°N and 60°W-45°W, (2) the Gulf of Mexico and the western Caribbean Sea, and (3) the open ocean southeast and east of Florida. RI events also show a minimum value in the eastern Caribbean Sea north of South America—a place called a hurricane graveyard due to atmospheric divergence and subsidence. On longer time scales, RI displays both interannual and multidecadal variability, but RI does not show a long-term trend due to global warming. The top three climate indices showing high correlations with RI are the June-November ENSO and Atlantic warm pool indices, and the January-March North Atlantic oscillation index. It is found that variabilities of vertical wind shear and TC heat potential are important for TC RI in the hurricane main development region, whereas relative humidity at 500 hPa is the main factor responsible for TC RI in the eastern TNA. However, the large-scale oceanic and atmospheric variables analyzed in this study do not show an important role in TC RI in the Gulf of Mexico and the open ocean southeast and east of Florida. This suggests that other factors such as small-scale changes of oceanic and atmospheric variables or TC internal processes may be responsible for TC RI in these two regions. Additionally, the analyses indicate that large-scale atmospheric and oceanic variables are not critical to TC genesis and formation; however, once a tropical depression forms, large-scale climate variations play a role in TC intensification.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.A21G0180N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.A21G0180N"><span>Analysis of the Effect of Interior Nudging on Temperature and Precipitation Distributions of Multi-year Regional Climate Simulations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nolte, C. G.; Otte, T. L.; Bowden, J. H.; Otte, M. J.</p> <p>2010-12-01</p> <p>There is disagreement in the regional climate modeling community as to the appropriateness of the use of internal nudging. Some investigators argue that the regional model should be minimally constrained and allowed to respond to regional-scale forcing, while others have noted that in the absence of interior nudging, significant large-scale discrepancies develop between the regional model solution and the driving coarse-scale fields. These discrepancies lead to reduced confidence in the ability of regional climate models to dynamically downscale global climate model simulations under climate change scenarios, and detract from the usability of the regional simulations for impact assessments. The advantages and limitations of interior nudging schemes for regional climate modeling are investigated in this study. Multi-year simulations using the WRF model driven by reanalysis data over the continental United States at 36km resolution are conducted using spectral nudging, grid point nudging, and for a base case without interior nudging. The means, distributions, and inter-annual variability of temperature and precipitation will be evaluated in comparison to regional analyses.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18060692','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18060692"><span>Safety climate practice in Korean manufacturing industry.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Baek, Jong-Bae; Bae, Sejong; Ham, Byung-Ho; Singh, Karan P</p> <p>2008-11-15</p> <p>Safety climate survey was sent to 642 plants in 2003 to explore safety climate practices in the Korean manufacturing plants, especially in hazardous chemical treating plants. Out of 642 plants contacted 195 (30.4%) participated in the surveys. Data were collected by e-mail using SQL-server and mail. The main objective of this study was to explore safety climate practices (level of safety climate and the underlying problems). In addition, the variables that may influence the level of safety climate among managers and workers were explored. The questionnaires developed by health and safety executive (HSE) in the UK were modified to incorporate differences in Korean culture. Eleven important factors were summarized. Internal reliability of these factors was validated. Number of employees in the company varied from less than 30 employees (9.2%) to over 1000 employees (37.4%). Both managers and workers showed generally high level of safety climate awareness. The major underlying problems identified were inadequate health and safety procedures/rules, pressure for production, and rule breaking. The length of employment was a significant contributing factor to the level of safety climate. In this study, participants showed generally high level of safety climate, and length of employment affected the differences in the level of safety climate. Managers' commitment to comply safety rules, procedures, and effective safety education and training are recommended.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20436336','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20436336"><span>Quality of internal communication in health care and the professional-patient relationship.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>March Cerdá, Joan Carles; Prieto Rodríguez, María Angeles; Pérez Corral, Olivia; Lorenzo, Sergio Minué; Danet, Alina</p> <p>2010-01-01</p> <p>A study was undertaken for the purpose of describing internal communication and the professional-patient relationship and to establish a descriptive model of the interaction between these 2 variables. A nationwide survey was carried out in primary care and specialist care centers in Spain. A simple random sampling method was used with 1183 health care professionals. The data collection instrument was a Likert questionnaire that recorded information on the perceived quality of internal communication (0-100 scale), professional-patient relationships (0-100 scale), and sociodemographic variables. The results were analyzed using SPSS 15.0, performing mean comparisons and a suitable linear regression model.The total average of the quality of internal communication was 53.79 points, and that of the professional-patient relationships was 74.17 points. Sex made no statistically significant difference. Age shows that the older the participant, the better his/her opinion of internal communication and professional-patient relationships. Nursing staff had the highest opinion of internal communication and professional-patient relationships. The association between internal communication and professional-patient relationship was positive (R = 0.45).It was concluded that continuous exchange of information among health care professionals, together with learning and shared decision making or a positive emotional climate, is an element that will consolidate good professional-patient relationships and ensure patient satisfaction.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19910003143','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19910003143"><span>Climate Impact of Solar Variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Schatten, Kenneth H. (Editor); Arking, Albert (Editor)</p> <p>1990-01-01</p> <p>The conference on The Climate Impact of Solar Variability, was held at Goddard Space Flight Center from April 24 to 27, 1990. In recent years they developed a renewed interest in the potential effects of increasing greenhouse gases on climate. Carbon dioxide, methane, nitrous oxide, and the chlorofluorocarbons have been increasing at rates that could significantly change climate. There is considerable uncertainty over the magnitude of this anthropogenic change. The climate system is very complex, with feedback processes that are not fully understood. Moreover, there are two sources of natural climate variability (volcanic aerosols and solar variability) added to the anthropogenic changes which may confuse our interpretation of the observed temperature record. Thus, if we could understand the climatic impact of the natural variability, it would aid our interpretation and understanding of man-made climate changes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4258067','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4258067"><span>Climate variability and vulnerability to climate change: a review</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Thornton, Philip K; Ericksen, Polly J; Herrero, Mario; Challinor, Andrew J</p> <p>2014-01-01</p> <p>The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here, we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades. PMID:24668802</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4362079','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4362079"><span>Climate services for society: origins, institutional arrangements, and design elements for an evaluation framework</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Vaughan, Catherine; Dessai, Suraje</p> <p>2014-01-01</p> <p>Climate services involve the generation, provision, and contextualization of information and knowledge derived from climate research for decision making at all levels of society. These services are mainly targeted at informing adaptation to climate variability and change, widely recognized as an important challenge for sustainable development. This paper reviews the development of climate services, beginning with a historical overview, a short summary of improvements in climate information, and a description of the recent surge of interest in climate service development including, for example, the Global Framework for Climate Services, implemented by the World Meteorological Organization in October 2012. It also reviews institutional arrangements of selected emerging climate services across local, national, regional, and international scales. By synthesizing existing literature, the paper proposes four design elements of a climate services evaluation framework. These design elements include: problem identification and the decision-making context; the characteristics, tailoring, and dissemination of the climate information; the governance and structure of the service, including the process by which it is developed; and the socioeconomic value of the service. The design elements are intended to serve as a guide to organize future work regarding the evaluation of when and whether climate services are more or less successful. The paper concludes by identifying future research questions regarding the institutional arrangements that support climate services and nascent efforts to evaluate them. PMID:25798197</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25798197','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25798197"><span>Climate services for society: origins, institutional arrangements, and design elements for an evaluation framework.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Vaughan, Catherine; Dessai, Suraje</p> <p>2014-09-01</p> <p>Climate services involve the generation, provision, and contextualization of information and knowledge derived from climate research for decision making at all levels of society. These services are mainly targeted at informing adaptation to climate variability and change, widely recognized as an important challenge for sustainable development. This paper reviews the development of climate services, beginning with a historical overview, a short summary of improvements in climate information, and a description of the recent surge of interest in climate service development including, for example, the Global Framework for Climate Services, implemented by the World Meteorological Organization in October 2012. It also reviews institutional arrangements of selected emerging climate services across local, national, regional, and international scales. By synthesizing existing literature, the paper proposes four design elements of a climate services evaluation framework. These design elements include: problem identification and the decision-making context; the characteristics, tailoring, and dissemination of the climate information; the governance and structure of the service, including the process by which it is developed; and the socioeconomic value of the service. The design elements are intended to serve as a guide to organize future work regarding the evaluation of when and whether climate services are more or less successful. The paper concludes by identifying future research questions regarding the institutional arrangements that support climate services and nascent efforts to evaluate them.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN11B0033T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN11B0033T"><span>Statistical Compression of Wind Speed Data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tagle, F.; Castruccio, S.; Crippa, P.; Genton, M.</p> <p>2017-12-01</p> <p>In this work we introduce a lossy compression approach that utilizes a stochastic wind generator based on a non-Gaussian distribution to reproduce the internal climate variability of daily wind speed as represented by the CESM Large Ensemble over Saudi Arabia. Stochastic wind generators, and stochastic weather generators more generally, are statistical models that aim to match certain statistical properties of the data on which they are trained. They have been used extensively in applications ranging from agricultural models to climate impact studies. In this novel context, the parameters of the fitted model can be interpreted as encoding the information contained in the original uncompressed data. The statistical model is fit to only 3 of the 30 ensemble members and it adequately captures the variability of the ensemble in terms of seasonal internannual variability of daily wind speed. To deal with such a large spatial domain, it is partitioned into 9 region, and the model is fit independently to each of these. We further discuss a recent refinement of the model, which relaxes this assumption of regional independence, by introducing a large-scale component that interacts with the fine-scale regional effects.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AdAtS..29..910H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AdAtS..29..910H"><span>Characteristics, processes, and causes of the spatio-temporal variabilities of the East Asian monsoon system</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Huang, Ronghui; Chen, Jilong; Wang, Lin; Lin, Zhongda</p> <p>2012-09-01</p> <p>Recent advances in the study of the characteristics, processes, and causes of spatio-temporal variabilities of the East Asian monsoon (EAM) system are reviewed in this paper. The understanding of the EAM system has improved in many aspects: the basic characteristics of horizontal and vertical structures, the annual cycle of the East Asian summer monsoon (EASM) system and the East Asian winter monsoon (EAWM) system, the characteristics of the spatio-temporal variabilities of the EASM system and the EAWM system, and especially the multiple modes of the EAM system and their spatio-temporal variabilities. Some new results have also been achieved in understanding the atmosphere-ocean interaction and atmosphere-land interaction processes that affect the variability of the EAM system. Based on recent studies, the EAM system can be seen as more than a circulation system, it can be viewed as an atmosphere-ocean-land coupled system, namely, the EAM climate system. In addition, further progress has been made in diagnosing the internal physical mechanisms of EAM climate system variability, especially regarding the characteristics and properties of the East Asia-Pacific (EAP) teleconnection over East Asia and the North Pacific, the "Silk Road" teleconnection along the westerly jet stream in the upper troposphere over the Asian continent, and the dynamical effects of quasi-stationary planetary wave activity on EAM system variability. At the end of the paper, some scientific problems regarding understanding the EAM system variability are proposed for further study.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27279167','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27279167"><span>Climate-driven vital rates do not always mean climate-driven population.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tavecchia, Giacomo; Tenan, Simone; Pradel, Roger; Igual, José-Manuel; Genovart, Meritxell; Oro, Daniel</p> <p>2016-12-01</p> <p>Current climatic changes have increased the need to forecast population responses to climate variability. A common approach to address this question is through models that project current population state using the functional relationship between demographic rates and climatic variables. We argue that this approach can lead to erroneous conclusions when interpopulation dispersal is not considered. We found that immigration can release the population from climate-driven trajectories even when local vital rates are climate dependent. We illustrated this using individual-based data on a trans-equatorial migratory seabird, the Scopoli's shearwater Calonectris diomedea, in which the variation of vital rates has been associated with large-scale climatic indices. We compared the population annual growth rate λ i , estimated using local climate-driven parameters with ρ i , a population growth rate directly estimated from individual information and that accounts for immigration. While λ i varied as a function of climatic variables, reflecting the climate-dependent parameters, ρ i did not, indicating that dispersal decouples the relationship between population growth and climate variables from that between climatic variables and vital rates. Our results suggest caution when assessing demographic effects of climatic variability especially in open populations for very mobile organisms such as fish, marine mammals, bats, or birds. When a population model cannot be validated or it is not detailed enough, ignoring immigration might lead to misleading climate-driven projections. © 2016 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.3703F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.3703F"><span>Assessing the vulnerability of economic sectors to climate variability to improve the usability of seasonal to decadal climate forecasts in Europe - a preliminary concept</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Funk, Daniel</p> <p>2015-04-01</p> <p>Climate variability poses major challenges for decision-makers in climate-sensitive sectors. Seasonal to decadal (S2D) forecasts provide potential value for management decisions especially in the context of climate change where information from present or past climatology loses significance. However, usable and decision-relevant tailored climate forecasts are still sparse for Europe and successful examples of application require elaborate and individual producer-user interaction. The assessment of sector-specific vulnerabilities to critical climate conditions at specific temporal scale will be a great step forward to increase the usability and efficiency of climate forecasts. A concept for a sector-specific vulnerability assessment (VA) to climate variability is presented. The focus of this VA is on the provision of usable vulnerability information which can be directly incorporated in decision-making processes. This is done by developing sector-specific climate-impact-decision-pathways and the identification of their specific time frames using data from both bottom-up and top-down approaches. The structure of common VA's for climate change related issues is adopted which envisages the determination of exposure, sensitivity and coping capacity. However, the application of the common vulnerability components within the context of climate service application poses some fundamental considerations: Exposure - the effect of climate events on the system of concern may be modified and delayed due to interconnected systems (e.g. catchment). The critical time-frame of a climate event or event sequence is dependent on system-internal thresholds and initial conditions. But also on decision-making processes which require specific lead times of climate information to initiate respective coping measures. Sensitivity - in organizational systems climate may pose only one of many factors relevant for decision making. The scope of "sensitivity" in this concept comprises both the potential physical response of the system of concern as well as the criticality of climate-related decision-making processes. Coping capacity - in an operational context coping capacity can only reduce vulnerability if it can be applied purposeful. With respect to climate vulnerabilities this refers to the availability of suitable, usable and skillful climate information. The focus for this concept is on existing S2D climate service products and their match with user needs. The outputs of the VA are climate-impact-decision-pathways which characterize critical climate conditions, estimate the role of climate in decision-making processes and evaluate the availability and potential usability of S2D climate forecast products. A classification scheme is developed for each component of the impact-pathway to assess its specific significance. The systemic character of these schemes enables a broad application of this VA across sectors where quantitative data is limited. This concept is developed and will be tested within the context of the EU-FP7 project "European Provision Of Regional Impacts Assessments on Seasonal and Decadal Timescales" EUPORIAS.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4804158','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4804158"><span>Survey of Expert Opinion on Intelligence: Causes of International Differences in Cognitive Ability Tests</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Rindermann, Heiner; Becker, David; Coyle, Thomas R.</p> <p>2016-01-01</p> <p>Following Snyderman and Rothman (1987, 1988), we surveyed expert opinions on the current state of intelligence research. This report examines expert opinions on causes of international differences in student assessment and psychometric IQ test results. Experts were surveyed about the importance of culture, genes, education (quantity and quality), wealth, health, geography, climate, politics, modernization, sampling error, test knowledge, discrimination, test bias, and migration. The importance of these factors was evaluated for diverse countries, regions, and groups including Finland, East Asia, sub-Saharan Africa, Southern Europe, the Arabian-Muslim world, Latin America, Israel, Jews in the West, Roma (gypsies), and Muslim immigrants. Education was rated by N = 71 experts as the most important cause of international ability differences. Genes were rated as the second most relevant factor but also had the highest variability in ratings. Culture, health, wealth, modernization, and politics were the next most important factors, whereas other factors such as geography, climate, test bias, and sampling error were less important. The paper concludes with a discussion of limitations of the survey (e.g., response rates and validity of expert opinions). PMID:27047425</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ems..confE.293B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ems..confE.293B"><span>European climate variability and human susceptibility over the past 2500 years</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Buentgen, U.</p> <p>2010-09-01</p> <p>Climate variations including droughts in the western US and African Sahel, landfalls of Atlantic hurricanes, and shifts in the Asian monsoon have affected human societies throughout history mainly by modulating water supply and agricultural productivity, health risk and civil conflict. Yet, discriminations of environmental impacts from political, economical and technological drivers of societal shifts are may be hampered by the indirect effects of climate on society, but certainly by the paucity of high-resolution palaeoclimatic evidence. Here we present a tree-ring network of 7284 precipitation sensitive oak series from lower elevations in France and Germany, and a compilation of 1546 temperature responsive conifers from higher elevations in the Austrian Alps, both covering the past 2500 years. Temporal distribution of historical felling dates of construction timber refers to changes in settlement activity that mirror different stages of economic wealth. Variations in Central European summer precipitation and temperature are contrasted with societal benchmarks. Prolonged periods of generally wet and warm summers, favourable for cultural prosperity, appeared during the Roman epoch between ~200 BC and 200 AD and from ~700-1000 AD, with the latter facilitating the rapid economic, cultural and political growth of medieval Europe. Unprecedented climate variability from ~200-500 AD coincides with the demise of the Western Roman Empire and the subsequent Barbarian Migrations. This period was characterized by continental-scale political turmoil, cultural stagnation and socio-economic instability including settlement abandonment, population migration, and societal collapse. Driest and coldest summers of the Late Holocene concurred in the 6th century, during which regional consolidation began. The recent political, cultural and fiscal reluctance to adapt to and mitigate projected climate change reflects the common belief of societal insusceptibility to environmental conditions. The complex climatic interference with agrarian civilizations, however, challenges the sustainability of this attitude. In addition to the long-term context it provides for instrumentally observed European climate variability, our study reveals critical targets for next-generation climate models to hindcast the temporal footprints and magnitudes of natural fluctuations over the Late Holocene in response to internal dynamics and external forcings.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMOS31C1734C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMOS31C1734C"><span>Predictability of Subsurface Temperature and the AMOC</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chang, Y.; Schubert, S. D.</p> <p>2013-12-01</p> <p>GEOS 5 coupled model is extensively used for experimental decadal climate prediction. Understanding the limits of decadal ocean predictability is critical for making progress in these efforts. Using this model, we study the subsurface temperature initial value predictability, the variability of the Atlantic meridional overturning circulation (AMOC) and its impacts on the global climate. Our approach is to utilize the idealized data assimilation technology developed at the GMAO. The technique 'replay' allows us to assess, for example, the impact of the surface wind stresses and/or precipitation on the ocean in a very well controlled environment. By running the coupled model in replay mode we can in fact constrain the model using any existing reanalysis data set. We replay the model constraining (nudging) it to the MERRA reanalysis in various fields from 1948-2012. The fields, u,v,T,q,ps, are adjusted towards the 6-hourly analyzed fields in atmosphere. The simulated AMOC variability is studied with a 400-year-long segment of replay integration. The 84 cases of 10-year hindcasts are initialized from 4 different replay cycles. Here, the variability and predictability are examined further by a measure to quantify how much the subsurface temperature and AMOC variability has been influenced by atmospheric forcing and by ocean internal variability. The simulated impact of the AMOC on the multi-decadal variability of the SST, sea surface height (SSH) and sea ice extent is also studied.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27835959','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27835959"><span>Current medical research funding and frameworks are insufficient to address the health risks of global environmental change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ebi, Kristie L; Semenza, Jan C; Rocklöv, Joacim</p> <p>2016-11-11</p> <p>Three major international agreements signed in 2015 are key milestones for transitioning to more sustainable and resilient societies: the UN 2030 Agenda for Sustainable Development; the Sendai Framework for Disaster Risk Reduction; and the Paris Agreement under the United Nations Framework Convention on Climate Change. Together, these agreements underscore the critical importance of understanding and managing the health risks of global changes, to ensure continued population health improvements in the face of significant social and environmental change over this century. BODY: Funding priorities of major health institutions and organizations in the U.S. and Europe do not match research investments with needs to inform implementation of these international agreements. In the U.S., the National Institutes of Health commit 0.025 % of their annual research budget to climate change and health. The European Union Seventh Framework Programme committed 0.08 % of the total budget to climate change and health; the amount committed under Horizon 2020 was 0.04 % of the budget. Two issues apparently contributing to this mismatch are viewing climate change primarily as an environmental problem, and therefore the responsibility of other research streams; and narrowly framing research into managing the health risks of climate variability and change from the perspective of medicine and traditional public health. This reductionist, top-down perspective focuses on proximate, individual level risk factors. While highly successful in reducing disease burdens, this framing is insufficient to protect health and well-being over a century that will be characterized by profound social and environmental changes. International commitments in 2015 underscored the significant challenges societies will face this century from climate change and other global changes. However, the low priority placed on understanding and managing the associated health risks by national and international research institutions and organizations leaves populations poorly prepared to cope with changing health burdens. Risk-centered, systems approaches can facilitate understanding of the complex interactions and dependencies across environmental, social, and human systems. This understanding is needed to formulate effective interventions targeting socio-environmental factors that are as important for determining health burdens as are individual risk factors.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9963S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9963S"><span>How resilient are ecosystems in adapting to climate variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Savenije, Hubert H. G.</p> <p>2015-04-01</p> <p>The conclusion often drawn in the media is that ecosystems may perish as a result of climate change. Although climatic trends may indeed lead to shifts in ecosystem composition, the challenge to adjust to climatic variability - even if there is no trend - is larger, particularly in semi-arid or topical climates where climatic variability is large compared to temperate climates. How do ecosystems buffer for climatic variability? The most powerful mechanism is to invest in root zone storage capacity, so as to guarantee access to water and nutrients during period of drought. This investment comes at a cost of having less energy available to invest in growth or formation of fruits. Ecosystems are expected to create sufficient buffer to overcome critical periods of drought, but not more than is necessary to survive or reproduce. Based on this concept, a methodology has been developed to estimate ecosystem root zone storage capacity at local, regional and global scale. These estimates correspond well with estimates made by combining soil and ecosystem information, but are more accurate and more detailed. The methodology shows that ecosystems have intrinsic capacity to adjust to climatic variability and hence have a high resilience to both climatic variability and climatic trends.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.8751B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.8751B"><span>Integrating Climate Information and Decision Processes for Regional Climate Resilience</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Buizer, James; Goddard, Lisa; Guido, Zackry</p> <p>2015-04-01</p> <p>An integrated multi-disciplinary team of researchers from the University of Arizona and the International Research Institute for Climate and Society at Columbia University have joined forces with communities and institutions in the Caribbean, South Asia and West Africa to develop relevant, usable climate information and connect it to real decisions and development challenges. The overall objective of the "Integrating Climate Information and Decision Processes for Regional Climate Resilience" program is to build community resilience to negative impacts of climate variability and change. We produce and provide science-based climate tools and information to vulnerable peoples and the public, private, and civil society organizations that serve them. We face significant institutional challenges because of the geographical and cultural distance between the locale of climate tool-makers and the locale of climate tool-users and because of the complicated, often-inefficient networks that link them. To use an accepted metaphor, there is great institutional difficulty in coordinating the supply of and the demand for useful climate products that can be put to the task of building local resilience and reducing climate vulnerability. Our program is designed to reduce the information constraint and to initiate a linkage that is more demand driven, and which provides a set of priorities for further climate tool generation. A demand-driven approach to the co-production of appropriate and relevant climate tools seeks to meet the direct needs of vulnerable peoples as these needs have been canvassed empirically and as the benefits of application have been adequately evaluated. We first investigate how climate variability and climate change affect the livelihoods of vulnerable peoples. In so doing we assess the complex institutional web within which these peoples live -- the public agencies that serve them, their forms of access to necessary information, the structural constraints under which they make their decisions, and the non-public institutions of support that are available to them. We then interpret this complex reality in terms of the demand for science-based climate products and analyze the channels through which such climate support must pass, thus linking demand assessment with the scientific capacity to create appropriate decision support tools. In summary, the approach we employ is: 1) Demand-driven, beginning with a knowledge of the impacts of climate variability and change upon targeted populations, 2) Focused on vulnerability and resilience, which requires an understanding of broader networks of institutional actors who contribute to the adaptive capacity of vulnerable peoples, 3) Needs-based in that the climate needs matrix set priorities for the assessment of relevant climate products, 4) Dynamic in that the producers of climate products are involved at the point of demand assessment and can respond directly to stated needs, 5) Reflective in that the impacts of climate product interventions are subject to monitoring and evaluation throughout the process. Methods, approaches and preliminary results of our work in the Caribbean will be presented.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4639351','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4639351"><span>THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan</p> <p>2015-01-01</p> <p>Background: The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran’s universities. Methods: This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran’s public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. Results: of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran’s libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Conclusions: Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries. PMID:26622203</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26622203','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26622203"><span>THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan</p> <p>2015-10-01</p> <p>The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran's universities. This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran's public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran's libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.7054K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.7054K"><span>On the role of "internal variability" on soil erosion assessment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kim, Jongho; Ivanov, Valeriy; Fatichi, Simone</p> <p>2017-04-01</p> <p>Empirical data demonstrate that soil loss is highly non-unique with respect to meteorological or even runoff forcing and its frequency distributions exhibit heavy tails. However, all current erosion assessments do not describe the large associated uncertainties of temporal erosion variability and make unjustified assumptions by relying on central tendencies. Thus, the predictive skill of prognostic models and reliability of national-scale assessments have been repeatedly questioned. In this study, we attempt to reveal that the high variability in soil losses can be attributed to two sources: (1) 'external variability' referring to the uncertainties originating at macro-scale, such as climate, topography, and land use, which has been extensively studied; (2) 'geomorphic internal variability' referring to the micro-scale variations of pedologic properties (e.g., surface erodibility in soils with multi-sized particles), hydrologic properties (e.g., soil structure and degree of saturation), and hydraulic properties (e.g., surface roughness and surface topography). Using data and a physical hydraulic, hydrologic, and erosion and sediment transport model, we show that the geomorphic internal variability summarized by spatio-temporal variability in surface erodibility properties is a considerable source of uncertainty in erosion estimates and represents an overlooked but vital element of geomorphic response. The conclusion is that predictive frameworks of soil erosion should embed stochastic components together with deterministic assessments, if they do not want to largely underestimate uncertainty. Acknowledgement: This study was supported by the Basic Science Research Program of the National Research Foundation of Korea funded by the Ministry of Education (2016R1D1A1B03931886).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27907262','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27907262"><span>Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bateman, Brooke L; Pidgeon, Anna M; Radeloff, Volker C; Flather, Curtis H; VanDerWal, Jeremy; Akçakaya, H Resit; Thogmartin, Wayne E; Albright, Thomas P; Vavrus, Stephen J; Heglund, Patricia J</p> <p>2016-12-01</p> <p>Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate variability is low, and assess how species' potential distributions may have already shifted due recent climate change. However, long-term climate averages require less data and processing time and may be more readily available for some areas of interest. Where data on short-term climate variability are not available, long-term climate information is a sufficient predictor of species distributions in many cases. However, short-term climate variability data may provide information not captured with long-term climate data for use in SDMs. © 2016 by the Ecological Society of America.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33A1178B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33A1178B"><span>Dynamical adjustment of Scandinavian glacier mass-balance time series</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bonan, D.; Christian, J. E.; Christianson, K. A.</p> <p>2017-12-01</p> <p>Glacier mass wastage is often cited as one of the most visible manifestations of anthropogenic climate change. Annual glacier mass-balance is related to local climate and atmospheric circulation, as it is defined as the yearly sum of accumulation and ablation—processes that are strongly influenced by year-to-year fluctuations in precipitation and temperature. Glacier response to a climatic trend can, however, be masked by internal variability in atmospheric circulation, and by non-climatic factors (such as topographic control, wind deposition, and incident solar radiation). Thus, unambiguous attribution of a negative glacier mass-balance trend to anthropogenic forcing remains challenging. Maritime glacier mass-balance records may be especially difficult to interpret due to the high winter balances from decadal-scale climate oscillations and the relatively short time series. Here we examine the influence of climate and atmospheric circulation variability on 14 Norwegian glaciers that span 20° of latitude, from southern Norway to Svalbard. We use dynamical adjustment—a statistical method based on partial least squares regression—to identify the components of variability within the mass-balance records that are associated with the time-varying sea level pressure (SLP) and sea surface temperature (SST) fields. We find that 30-50% of the variance in the winter mass-balance records of the glaciers in southern Norway is explained by using sea level pressure as a predictor. The leading SLP predictor pattern mimics the spatial signature of the North Atlantic Oscillation (NAO), indicating that winter balance is strongly influenced by the NAO. Moreover, the adjusted mass-balance records indicate a geographic trend: the southern Norwegian glaciers have significant negative trends in the summer balance that remain negative after adjustment, while the more northern glaciers have negative winter balance trends that only become significant after adjustment. We look into anthropogenic warming to explain the trends after dynamical adjustment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H23O..06S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H23O..06S"><span>The integrated effects of future climate and hydrologic uncertainty on sustainable flood risk management</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Steinschneider, S.; Wi, S.; Brown, C. M.</p> <p>2013-12-01</p> <p>Flood risk management performance is investigated within the context of integrated climate and hydrologic modeling uncertainty to explore system robustness. The research question investigated is whether structural and hydrologic parameterization uncertainties are significant relative to other uncertainties such as climate change when considering water resources system performance. Two hydrologic models are considered, a conceptual, lumped parameter model that preserves the water balance and a physically-based model that preserves both water and energy balances. In the conceptual model, parameter and structural uncertainties are quantified and propagated through the analysis using a Bayesian modeling framework with an innovative error model. Mean climate changes and internal climate variability are explored using an ensemble of simulations from a stochastic weather generator. The approach presented can be used to quantify the sensitivity of flood protection adequacy to different sources of uncertainty in the climate and hydrologic system, enabling the identification of robust projects that maintain adequate performance despite the uncertainties. The method is demonstrated in a case study for the Coralville Reservoir on the Iowa River, where increased flooding over the past several decades has raised questions about potential impacts of climate change on flood protection adequacy.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy...49.1181V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy...49.1181V"><span>Comparison of full field and anomaly initialisation for decadal climate prediction: towards an optimal consistency between the ocean and sea-ice anomaly initialisation state</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco J.</p> <p>2017-08-01</p> <p>Decadal prediction exploits sources of predictability from both the internal variability through the initialisation of the climate model from observational estimates, and the external radiative forcings. When a model is initialised with the observed state at the initial time step (Full Field Initialisation—FFI), the forecast run drifts towards the biased model climate. Distinguishing between the climate signal to be predicted and the model drift is a challenging task, because the application of a-posteriori bias correction has the risk of removing part of the variability signal. The anomaly initialisation (AI) technique aims at addressing the drift issue by answering the following question: if the model is allowed to start close to its own attractor (i.e. its biased world), but the phase of the simulated variability is constrained toward the contemporaneous observed one at the initialisation time, does the prediction skill improve? The relative merits of the FFI and AI techniques applied respectively to the ocean component and the ocean and sea ice components simultaneously in the EC-Earth global coupled model are assessed. For both strategies the initialised hindcasts show better skill than historical simulations for the ocean heat content and AMOC along the first two forecast years, for sea ice and PDO along the first forecast year, while for AMO the improvements are statistically significant for the first two forecast years. The AI in the ocean and sea ice components significantly improves the skill of the Arctic sea surface temperature over the FFI.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29472598','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29472598"><span>Climate-Driven Crop Yield and Yield Variability and Climate Change Impacts on the U.S. Great Plains Agricultural Production.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Kukal, Meetpal S; Irmak, Suat</p> <p>2018-02-22</p> <p>Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968-2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28589633','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28589633"><span>Does climate variability influence the demography of wild primates? Evidence from long-term life-history data in seven species.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Campos, Fernando A; Morris, William F; Alberts, Susan C; Altmann, Jeanne; Brockman, Diane K; Cords, Marina; Pusey, Anne; Stoinski, Tara S; Strier, Karen B; Fedigan, Linda M</p> <p>2017-11-01</p> <p>Earth's rapidly changing climate creates a growing need to understand how demographic processes in natural populations are affected by climate variability, particularly among organisms threatened by extinction. Long-term, large-scale, and cross-taxon studies of vital rate variation in relation to climate variability can be particularly valuable because they can reveal environmental drivers that affect multiple species over extensive regions. Few such data exist for animals with slow life histories, particularly in the tropics, where climate variation over large-scale space is asynchronous. As our closest relatives, nonhuman primates are especially valuable as a resource to understand the roles of climate variability and climate change in human evolutionary history. Here, we provide the first comprehensive investigation of vital rate variation in relation to climate variability among wild primates. We ask whether primates are sensitive to global changes that are universal (e.g., higher temperature, large-scale climate oscillations) or whether they are more sensitive to global change effects that are local (e.g., more rain in some places), which would complicate predictions of how primates in general will respond to climate change. To address these questions, we use a database of long-term life-history data for natural populations of seven primate species that have been studied for 29-52 years to investigate associations between vital rate variation, local climate variability, and global climate oscillations. Associations between vital rates and climate variability varied among species and depended on the time windows considered, highlighting the importance of temporal scale in detection of such effects. We found strong climate signals in the fertility rates of three species. However, survival, which has a greater impact on population growth, was little affected by climate variability. Thus, we found evidence for demographic buffering of life histories, but also evidence of mechanisms by which climate change could affect the fates of wild primates. © 2017 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EnMan..60..422D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EnMan..60..422D"><span>Climatic-Induced Shifts in the Distribution of Teak ( Tectona grandis) in Tropical Asia: Implications for Forest Management and Planning</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Deb, Jiban Chandra; Phinn, Stuart; Butt, Nathalie; McAlpine, Clive A.</p> <p>2017-09-01</p> <p>Modelling the future suitable climate space for tree species has become a widely used tool for forest management planning under global climate change. Teak ( Tectona grandis) is one of the most valuable tropical hardwood species in the international timber market, and natural teak forests are distributed from India through Myanmar, Laos and Thailand. The extents of teak forests are shrinking due to deforestation and the local impacts of global climate change. However, the direct impacts of climate changes on the continental-scale distributions of native and non-native teak have not been examined. In this study, we developed a species distribution model for teak across its entire native distribution in tropical Asia, and its non-native distribution in Bangladesh. We used presence-only records of trees and twelve environmental variables that were most representative for current teak distributions in South and Southeast Asia. MaxEnt (maximum entropy) models were used to model the distributions of teak under current and future climate scenarios. We found that land use/land cover change and elevation were the two most important variables explaining the current and future distributions of native and non-native teak in tropical Asia. Changes in annual precipitation, precipitation seasonality and annual mean actual evapotranspiration may result in shifts in the distributions of teak across tropical Asia. We discuss the implications for the conservation of critical teak habitats, forest management planning, and risks of biological invasion that may occur due to its cultivation in non-native ranges.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1816035V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1816035V"><span>The Upstream and Downstream impact of Milankovitch cycles in continental nonmarine sedimentary records</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Valero, Luis; Garcés, Miguel; Huerta, Pedro; Cabrera, Lluís</p> <p>2016-04-01</p> <p>Discerning the effects of climate in the stratigraphic record is crucial for the comprehension of past climate changes. The signature of climate in sedimentary sequences is often assessed by the identification of Milankovitch cycles, as they can be recognized due to their (quasi) periodic behaviour. The integration of diverse stratigraphic disciplines is required in order to understand the different processes involved in the expression of the orbital cycles in the sedimentary records. New advances in Stratigraphy disclose the different variables that affect the sedimentation along the sediment routing systems. These variables can be summarized as the relationship between accommodation and sediment supply (AS/SS), because they account for the shifts of the total mass balance of a basin. Based in these indicators we propose a synthetic model for the understanding of the expression of climate in continental basins. Sedimentation in internally drained lake basins is particularly sensitive to net precipitation/evaporation variations. Rapid base level oscillations modify the AS/SS ratio sufficiently as to mask possible sediment flux variations associated to the changing discharge. On the other hand, basins lacking a central lacustrine system do not experience climatically-driven accommodation changes, and thus are more sensitive to archive sediment pulses. Small basins lacking carbonate facies are the ideal candidates to archive the impact of orbital forcing in the landscapes, as their small-scale sediment transfer systems are unable to buffer the upstream signal. Sedimentation models that include the relationship between accommodation and sediment supply, the effects of density and type of vegetation, and its coupled response with climate are needed to enhance their reliability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A13E0313S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A13E0313S"><span>Low-frequency climate anomalies, changes in synoptic scale circulation patterns and statistics of extreme events over south-east Poland during the Last Millennium</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Slawinska, J. M.; Bartoszek, K.; Gabriel, C. J.</p> <p>2016-12-01</p> <p>Long-term predictions of changes in extreme event frequency are of utmost importance due to their high societal and economic impact. Yet, current projections are of limited skills as they rely on satellite records that are relatively short compared to the timescale of interest, and also due to the presence of a significant anthropogenic trend superimposed onto other low-frequency variabilities. Novel simulations of past climates provide unique opportunity to separate external perturbations from internal climate anomalies and to attribute the latter to systematic changes in different types of synoptic scale circulation and distributions of high-frequency events. Here we study such changes by employing the Last Millennium Ensemble of climate simulations carried out with the Community Earth System Model (CESM) at the U.S. National Center for Atmospheric Research, focusing in particular on decadal changes in frequency of extreme precipitation events over south-east Poland. We analyze low-frequency modulations of dominant patterns of synoptic scale circulations over Europe and their dependence on the Atlantic Meridional Overturning Circulation, along with their coupling with the North Atlantic Oscillation. Moreover, we examine whether some decades of persistently anomalous statistics of extreme events can be attributed to externally forced (e.g., via volcanic eruptions) perturbations of the North Atlantic climate. In the end, we discuss the possible linkages and physical mechanisms connecting volcanic eruptions, low-frequency variabilities of North Atlantic climate and changes in statistics of high impact weather, and compare briefly our results with some historical and paleontological records.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21G1182M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21G1182M"><span>Assessing concentration uncertainty estimates from passive microwave sea ice products</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meier, W.; Brucker, L.; Miller, J. A.</p> <p>2017-12-01</p> <p>Sea ice concentration is an essential climate variable and passive microwave derived estimates of concentration are one of the longest satellite-derived climate records. However, until recently uncertainty estimates were not provided. Numerous validation studies provided insight into general error characteristics, but the studies have found that concentration error varied greatly depending on sea ice conditions. Thus, an uncertainty estimate from each observation is desired, particularly for initialization, assimilation, and validation of models. Here we investigate three sea ice products that include an uncertainty for each concentration estimate: the NASA Team 2 algorithm product, the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF) product, and the NOAA/NSIDC Climate Data Record (CDR) product. Each product estimates uncertainty with a completely different approach. The NASA Team 2 product derives uncertainty internally from the algorithm method itself. The OSI-SAF uses atmospheric reanalysis fields and a radiative transfer model. The CDR uses spatial variability from two algorithms. Each approach has merits and limitations. Here we evaluate the uncertainty estimates by comparing the passive microwave concentration products with fields derived from the NOAA VIIRS sensor. The results show that the relationship between the product uncertainty estimates and the concentration error (relative to VIIRS) is complex. This may be due to the sea ice conditions, the uncertainty methods, as well as the spatial and temporal variability of the passive microwave and VIIRS products.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMSH42A..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMSH42A..01S"><span>Solar Influences on El Nino/Southern Oscillation Dynamics Over the Last Millennium</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stevenson, S.; Capotondi, A.; Fasullo, J.; Otto-Bliesner, B. L.</p> <p>2017-12-01</p> <p>The El Niño/Southern Oscillation (ENSO) exhibits considerable differences between the evolution of individual El Nino and La Nina events (`ENSO diversity'), with significant implications for impacts studies. However, the degree to which external forcing may affect ENSO diversity is not well understood, due to both internal variability and potentially compensatory contributions from multiple forcings. The Community Earth System Model Last Millennium Ensemble (CESM LME) provides an ideal testbed for studying the sensitivity of twentieth century ENSO to forced climate changes, as it contains many realizations of the 850-2005 period with differing combinations of forcings. Metrics of ENSO amplitude and diversity are compared across LME simulations, and although forced changes to ENSO amplitude are generally small, forced changes to diversity are often detectable. Anthropogenic changes to greenhouse gas and ozone/aerosol emissions modify the persistence of Eastern and Central Pacific El Nino events, through shifts in the upwelling and zonal advective feedbacks; these influences generally cancel one another over the twentieth century. Natural forcings are generally small over the 20th century, but when epochs of high/low solar irradiance are compared, distinct shifts in the development and termination of El Nino events can be observed. This indicates that solar variability can indeed have a significant role to play in setting the characteristics of tropical Pacific climate variability. Implications for configuring and evaluating projections of future climate change will be discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.4296M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.4296M"><span>Simulating Heinrich events in a coupled atmosphere-ocean-ice sheet model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mikolajewicz, Uwe; Ziemen, Florian</p> <p>2016-04-01</p> <p>Heinrich events are among the most prominent events of long-term climate variability recorded in proxies across the northern hemisphere. They are the archetype of ice sheet - climate interactions on millennial time scales. Nevertheless, the exact mechanisms that cause Heinrich events are still under discussion, and their climatic consequences are far from being fully understood. We contribute to answering the open questions by studying Heinrich events in a coupled ice sheet model (ISM) atmosphere-ocean-vegetation general circulation model (AOVGCM) framework, where this variability occurs as part of the model generated internal variability without the need to prescribe external perturbations, as was the standard approach in almost all model studies so far. The setup consists of a northern hemisphere setup of the modified Parallel Ice Sheet Model (mPISM) coupled to the global coarse resolution AOVGCM ECHAM5/MPIOM/LPJ. The simulations used for this analysis were an ensemble covering substantial parts of the late Glacial forced with transient insolation and prescribed atmospheric greenhouse gas concentrations. The modeled Heinrich events show a marked influence of the ice discharge on the Atlantic circulation and heat transport, but none of the Heinrich events during the Glacial did show a complete collapse of the North Atlantic meridional overturning circulation. The simulated main consequences of the Heinrich events are a freshening and cooling over the North Atlantic and a drying over northern Europe.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A31K..03O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A31K..03O"><span>Climate Projections from the NARCliM Project: Bayesian Model Averaging of Maximum Temperature Projections</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Olson, R.; Evans, J. P.; Fan, Y.</p> <p>2015-12-01</p> <p>NARCliM (NSW/ACT Regional Climate Modelling Project) is a regional climate project for Australia and the surrounding region. It dynamically downscales 4 General Circulation Models (GCMs) using three Regional Climate Models (RCMs) to provide climate projections for the CORDEX-AustralAsia region at 50 km resolution, and for south-east Australia at 10 km resolution. The project differs from previous work in the level of sophistication of model selection. Specifically, the selection process for GCMs included (i) conducting literature review to evaluate model performance, (ii) analysing model independence, and (iii) selecting models that span future temperature and precipitation change space. RCMs for downscaling the GCMs were chosen based on their performance for several precipitation events over South-East Australia, and on model independence.Bayesian Model Averaging (BMA) provides a statistically consistent framework for weighing the models based on their likelihood given the available observations. These weights are used to provide probability distribution functions (pdfs) for model projections. We develop a BMA framework for constructing probabilistic climate projections for spatially-averaged variables from the NARCliM project. The first step in the procedure is smoothing model output in order to exclude the influence of internal climate variability. Our statistical model for model-observations residuals is a homoskedastic iid process. Comparing RCMs with Australian Water Availability Project (AWAP) observations is used to determine model weights through Monte Carlo integration. Posterior pdfs of statistical parameters of model-data residuals are obtained using Markov Chain Monte Carlo. The uncertainty in the properties of the model-data residuals is fully accounted for when constructing the projections. We present the preliminary results of the BMA analysis for yearly maximum temperature for New South Wales state planning regions for the period 2060-2079.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=34049','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=34049"><span>Assessing climate impacts</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Wohl, Ellen E.; Pulwarty, Roger S.; Zhang, Jian Yun</p> <p>2000-01-01</p> <p>Assessing climate impacts involves identifying sources and characteristics of climate variability, and mitigating potential negative impacts of that variability. Associated research focuses on climate driving mechanisms, biosphere–hydrosphere responses and mediation, and human responses. Examples of climate impacts come from 1998 flooding in the Yangtze River Basin and hurricanes in the Caribbean and Central America. Although we have limited understanding of the fundamental driving-response interactions associated with climate variability, increasingly powerful measurement and modeling techniques make assessing climate impacts a rapidly developing frontier of science. PMID:11027321</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3601432','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3601432"><span>THE INFLUENCE OF GLOBAL CLIMATE CHANGE ON THE SCIENTIFIC FOUNDATIONS AND APPLICATIONS OF ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY: INTRODUCTION TO A SETAC INTERNATIONAL WORKSHOP</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Stahl, Ralph G; Hooper, Michael J; Balbus, John M; Clements, William; Fritz, Alyce; Gouin, Todd; Helm, Roger; Hickey, Christopher; Landis, Wayne; Moe, S Jannicke</p> <p>2013-01-01</p> <p>This is the first of seven papers resulting from a Society of Environmental Toxicology and Chemistry (SETAC) international workshop titled “The Influence of Global Climate Change on the Scientific Foundations and Applications of Environmental Toxicology and Chemistry.” The workshop involved 36 scientists from 11 countries and was designed to answer the following question: How will global climate change influence the environmental impacts of chemicals and other stressors and the way we assess and manage them in the environment? While more detail is found in the complete series of articles, some key consensus points are as follows: (1) human actions (including mitigation of and adaptation to impacts of global climate change [GCC]) may have as much influence on the fate and distribution of chemical contaminants as does GCC, and modeled predictions should be interpreted cautiously; (2) climate change can affect the toxicity of chemicals, but chemicals can also affect how organisms acclimate to climate change; (3) effects of GCC may be slow, variable, and difficult to detect, though some populations and communities of high vulnerability may exhibit responses sooner and more dramatically than others; (4) future approaches to human and ecological risk assessments will need to incorporate multiple stressors and cumulative risks considering the wide spectrum of potential impacts stemming from GCC; and (5) baseline/reference conditions for estimating resource injury and restoration/rehabilitation will continually shift due to GCC and represent significant challenges to practitioners. Environ. Toxicol. Chem. 2013;32:13–19. © 2012 SETAC PMID:23097130</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMGC12A..03H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMGC12A..03H"><span>Biophysical and Economic Uncertainty in the Analysis of Poverty Impacts of Climate Change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hertel, T. W.; Lobell, D. B.; Verma, M.</p> <p>2011-12-01</p> <p>This paper seeks to understand the main sources of uncertainty in assessing the impacts of climate change on agricultural output, international trade, and poverty. We incorporate biophysical uncertainty by sampling from a distribution of global climate model predictions for temperature and precipitation for 2050. The implications of these realizations for crop yields around the globe are estimated using the recently published statistical crop yield functions provided by Lobell, Schlenker and Costa-Roberts (2011). By comparing these yields to those predicted under current climate, we obtain the likely change in crop yields owing to climate change. The economic uncertainty in our analysis relates to the response of the global economic system to these biophysical shocks. We use a modified version of the GTAP model to elicit the impact of the biophysical shocks on global patterns of production, consumption, trade and poverty. Uncertainty in these responses is reflected in the econometrically estimated parameters governing the responsiveness of international trade, consumption, production (and hence the intensive margin of supply response), and factor supplies (which govern the extensive margin of supply response). We sample from the distributions of these parameters as specified by Hertel et al. (2007) and Keeney and Hertel (2009). We find that, even though it is difficult to predict where in the world agricultural crops will be favorably affected by climate change, the responses of economic variables, including output and exports can be far more robust (Table 1). This is due to the fact that supply and demand decisions depend on relative prices, and relative prices depend on productivity changes relative to other crops in a given region, or relative to similar crops in other parts of the world. We also find that uncertainty in poverty impacts of climate change appears to be almost entirely driven by biophysical uncertainty.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPP33C1344L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPP33C1344L"><span>A new reference frame for astronomically-tuned Plio-Pleistocene climate variability derived from a benthic oxygen isotope splice of the Mediterranean</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lourens, L. J.; Ziegler, M.; Konijnendijk, T. Y. M.; Hilgen, F. J.; Bos, R.; Beekvelt, B.; van Loevezijn, A.; Collin, S.</p> <p>2017-12-01</p> <p>The astronomical theory of climate has revolutionized our understanding of past climate change and the development of highly accurate geologic time scales for the entire Cenozoic. Most of this understanding has come from the construction of astronomically tuned global ocean benthic foraminiferal oxygen isotope (δ18O) stacked record, derived by the international drilling operations of DSDP, ODP and IODP. The tuning includes fixed phase relationships between the obliquity and precession cycles and the inferred high-latitude climate, i.e. glacial-interglacial, response, which hark back to SPECMAP, using simple ice sheet models and a limited number of radiometric dates. This approach was largely implemented in the widely applied LR04 stack, though LR04 assumed shorter response times for the smaller ice caps during the Pliocene. In the past decades, an astronomically calibrated time scale for the Pliocene and Pleistocene of the Mediterranean has been developed, which has become the reference for the standard Geologic Time Scale. Typical of the Mediterranean marine sediments are the cyclic lithological alternations, reflecting the interference between obliquity and precession-paced low latitude climate variability, such as the African monsoon. Here we present the first benthic foraminiferal based oxygen isotope record of the Mediterranean reference scale, which strikingly mirrors the LR04. We will use this record to discuss the assumed open ocean glacial-interglacial related phase relations over the past 5.3 million years.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4495927','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4495927"><span>Quantifying the Intra-Regional Precipitation Variability in Northwestern China over the Past 1,400 Years</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Lee, Harry F.; Pei, Qing; Zhang, David D.; Choi, Kan P. K.</p> <p>2015-01-01</p> <p>There has been a surge of paleo-climatic/environmental studies of Northwestern China (NW China), a region characterized by a diverse assortment of hydro-climatic systems. Their common approach, however, focuses on “deducing regional resemblance” rather than “exploring regional variance.” To date, efforts to produce a quantitative assessment of long-term intra-regional precipitation variability (IRPV) in NW China has been inadequate. In the present study, we base on historical flood/drought records to compile a decadal IRPV index for NW China spanned AD580–1979 and to find its major determinants via wavelet analysis. Results show that our IRPV index captures the footprints of internal hydro-climatic disparity in NW China. In addition, we find distinct ~120–200 year periodicities in the IRPV index over the Little Ice Age, which are attributable to the change of hydro-climatic influence of ocean-atmospheric modes during the period. Also, we offer statistical evidence of El Niño Southern Oscillation (Indo-Pacific warm pool sea surface temperature and China-wide land surface temperature) as the prominent multi-decadal to centennial (centennial to multi-centennial) determinant of the IRPV in NW China. The present study contributes to the quantitative validation of the long-term IRPV in NW China and its driving forces, covering the periods with and without instrumental records. It may help to comprehend the complex hydro-climatic regimes in the region. PMID:26154711</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFMGC21A0712B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFMGC21A0712B"><span>Evaluation of surface water budget and assessment the global water cycle for the IPCC AR4 A1B scenario simulations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Baek, H.; Park, E.; Kwon, W.</p> <p>2009-12-01</p> <p>Water balance calculations are becoming increasingly important for earth-system studies, because humans require water for their survival. Especially, the relationship between climate change and freshwater resources is of primary concern to human society and also has implications for all living species. The goal of this study is to assess the closure and annual variations of the water cycles based on the multi-model ensemble approach. In this study, the projection results of the previous works focusing on global and six sub-regions are updated using sixteen atmosphere-ocean general circulation model (AOGCM) simulations based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario. Before projecting future climate, model performances are evaluated on the simulation of the present-day climate. From the result, we construct and use mainly multi-model ensembles (MMEs), which is referred to as MME9, defined from nine selected AOGCMs of higher performance. Analyzed variables include annual and seasonal precipitation, evaporation, and runoff. The overall projection results from MME9 show that most regions will experience warmer and wetter climate at the end of 21st century. The evaporation shows a very similar trend to precipitation, but not in the runoff projection. The internal and inter-model variabilities are larger in the runoff than both precipitation and evaporation. Moreover, the runoff is notably reduced in Europe at the end of 21st century.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008JGRD..11310105L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008JGRD..11310105L"><span>Assessment of surface air temperature over the Arctic Ocean in reanalysis and IPCC AR4 model simulations with IABP/POLES observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Jiping; Zhang, Zhanhai; Hu, Yongyun; Chen, Liqi; Dai, Yongjiu; Ren, Xiaobo</p> <p>2008-05-01</p> <p>The surface air temperature (SAT) over the Arctic Ocean in reanalyses and global climate model simulations was assessed using the International Arctic Buoy Programme/Polar Exchange at the Sea Surface (IABP/POLES) observations for the period 1979-1999. The reanalyses, including the National Centers for Environmental Prediction Reanalysis II (NCEP2) and European Centre for Medium-Range Weather Forecast 40-year Reanalysis (ERA40), show encouraging agreement with the IABP/POLES observations, although some spatiotemporal discrepancies are noteworthy. The reanalyses have warm annual mean biases and underestimate the observed interannual SAT variability in summer. Additionally, NCEP2 shows an excessive warming trend. Most model simulations (coordinated by the International Panel on Climate Change for its Fourth Assessment Report) reproduce the annual mean, seasonal cycle, and trend of the observed SAT reasonably well, particularly the multi-model ensemble mean. However, large discrepancies are found. Some models have the annual mean SAT biases far exceeding the standard deviation of the observed interannul SAT variability and the across-model standard deviation. Spatially, the largest inter-model variance of the annual mean SAT is found over the North Pole, Greenland Sea, Barents Sea and Baffin Bay. Seasonally, a large spread of the simulated SAT among the models is found in winter. The models show interannual variability and decadal trend of various amplitudes, and can not capture the observed dominant SAT mode variability and cooling trend in winter. Further discussions of the possible attributions to the identified SAT errors for some models suggest that the model's performance in the sea ice simulation is an important factor.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1919195V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1919195V"><span>A global database with parallel measurements to study non-climatic changes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Venema, Victor; Auchman, Renate; Aguilar, Enric</p> <p>2017-04-01</p> <p>In this work we introduce the rationale behind the ongoing compilation of a parallel measurements database, in the framework of the International Surface Temperatures Initiative (ISTI) and with the support of the World Meteorological Organization. We intend this database to become instrumental for a better understanding of inhomogeneities affecting the evaluation of long-term changes in daily climate data. Long instrumental climate records are usually affected by non-climatic changes, due to, e.g., (i) station re- locations, (ii) instrument height changes, (iii) instrumentation changes, (iv) observing environment changes, (v) different sampling intervals or data collection procedures, among others. These so-called inhomogeneities distort the climate signal and can hamper the assessment of long-term trends and variability of climate. Thus to study climatic changes we need to accurately distinguish non-climatic and climatic signals. The most direct way to study the influence of non-climatic changes on the distribution and to understand the reasons for these biases is the analysis of parallel measurements representing the old and new situation (in terms of e.g. instruments, location, different radiation shields, etc.). According to the limited number of available studies and our understanding of the causes of inhomogeneity, we expect that they will have a strong impact on the tails of the distribution of air temperatures and most likely of other climate elements. Our abilities to statistically homogenize daily data will be increased by systematically studying different causes of inhomogeneity replicated through parallel measurements. Current studies of non-climatic changes using parallel data are limited to local and regional case studies. However, the effect of specific transitions depends on the local climate and the most interesting climatic questions are about the systematic large-scale biases produced by transitions that occurred in many regions. Important potentially biasing transitions are the adoption of Stevenson screens, relocations (to airports) efforts to reduce undercatchment of precipitation or the move to automatic weather stations. Thus a large global parallel dataset is highly desirable as it allows for the study of systematic biases in the global record. We are interested in data from all climate variables at all time scales; from annual to sub-daily. High-resolution data is important for understanding the physical causes for the differences between the parallel measurements. For the same reason, we are also interested in other climate variables measured at the same station. For example, in case of parallel air temperature measurements, the influencing factors are expected to be global radiation, wind, humidity and cloud cover; in case of parallel precipitation measurements, wind and wet-bulb temperature are potentially important.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990094166&hterms=climate+change+evidence&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dclimate%2Bchange%2Bevidence','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990094166&hterms=climate+change+evidence&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dclimate%2Bchange%2Bevidence"><span>Solar Variability in the Context of Other Climate Forcing Mechanisms</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hansen, James E.</p> <p>1999-01-01</p> <p>I compare and contrast climate forcings due to solar variability with climate forcings due to other mechanisms of climate change, interpretation of the role of the sun in climate change depends upon climate sensitivity and upon the net forcing by other climate change mechanisms. Among the potential indirect climate forcings due to solar variability, only that due to solar cycle induced ozone changes has been well quantified. There is evidence that the sun has been a significant player in past climate change on decadal to century time scales, and that it has the potential to contribute to climate change in the 21st century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5786539','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5786539"><span>Development of a Work Climate Scale in Emergency Health Services</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Sanduvete-Chaves, Susana; Lozano-Lozano, José A.; Chacón-Moscoso, Salvador; Holgado-Tello, Francisco P.</p> <p>2018-01-01</p> <p>An adequate work climate fosters productivity in organizations and increases employee satisfaction. Workers in emergency health services (EHS) have an extremely high degree of responsibility and consequent stress. Therefore, it is essential to foster a good work climate in this context. Despite this, scales with a full study of their psychometric properties (i.e., validity evidence based on test content, internal structure and relations to other variables, and reliability) are not available to measure work climate in EHS specifically. For this reason, our objective was to develop a scale to measure the quality of work climates in EHS. We carried out three studies. In Study 1, we used a mixed-method approach to identify the latent conceptual structure of the construct work climate. Thus, we integrated the results found in (a) a previous study, where a content analysis of seven in-depth interviews obtained from EHS professionals in two hospitals in Gibraltar Countryside County was carried out; and (b) the factor analysis of the responses given by 113 EHS professionals from these same centers to 18 items that measured the work climate in health organizations. As a result, we obtained 56 items grouped into four factors (work satisfaction, productivity/achievement of aims, interpersonal relationships, and performance at work). In Study 2, we presented validity evidence based on test content through experts' judgment. Fourteen experts from the methodology and health fields evaluated the representativeness, utility, and feasibility of each of the 56 items with respect to their factor (theoretical dimension). Forty items met the inclusion criterion, which was to obtain an Osterlind index value greater than or equal to 0.5 in the three aspects assessed. In Study 3, 201 EHS professionals from the same centers completed the resulting 40-item scale. This new instrument produced validity evidence based on the internal structure in a second-order factor model with four components (RMSEA = 0.079, GFI = 0.97, AGFI = 0.97, CFI = 0.97; NFI = 0.95, and NNFI = 0.97); absence of Differential Item Functioning (DIF) in 80% of the items; reliability (α = 0.96); and validity evidence based on relations to other variables, specifically the test-criterion relationship (ρ = 0.680). Finally, we discuss further developments of the instrument and its possible implications for EHS workers. PMID:29403417</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29403417','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29403417"><span>Development of a Work Climate Scale in Emergency Health Services.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sanduvete-Chaves, Susana; Lozano-Lozano, José A; Chacón-Moscoso, Salvador; Holgado-Tello, Francisco P</p> <p>2018-01-01</p> <p>An adequate work climate fosters productivity in organizations and increases employee satisfaction. Workers in emergency health services (EHS) have an extremely high degree of responsibility and consequent stress. Therefore, it is essential to foster a good work climate in this context. Despite this, scales with a full study of their psychometric properties (i.e., validity evidence based on test content, internal structure and relations to other variables, and reliability) are not available to measure work climate in EHS specifically. For this reason, our objective was to develop a scale to measure the quality of work climates in EHS. We carried out three studies. In Study 1, we used a mixed-method approach to identify the latent conceptual structure of the construct work climate . Thus, we integrated the results found in (a) a previous study, where a content analysis of seven in-depth interviews obtained from EHS professionals in two hospitals in Gibraltar Countryside County was carried out; and (b) the factor analysis of the responses given by 113 EHS professionals from these same centers to 18 items that measured the work climate in health organizations. As a result, we obtained 56 items grouped into four factors (work satisfaction, productivity/achievement of aims, interpersonal relationships, and performance at work). In Study 2, we presented validity evidence based on test content through experts' judgment. Fourteen experts from the methodology and health fields evaluated the representativeness, utility, and feasibility of each of the 56 items with respect to their factor (theoretical dimension). Forty items met the inclusion criterion, which was to obtain an Osterlind index value greater than or equal to 0.5 in the three aspects assessed. In Study 3, 201 EHS professionals from the same centers completed the resulting 40-item scale. This new instrument produced validity evidence based on the internal structure in a second-order factor model with four components ( RMSEA = 0.079, GFI = 0.97, AGFI = 0.97, CFI = 0.97; NFI = 0.95, and NNFI = 0.97); absence of Differential Item Functioning (DIF) in 80% of the items; reliability (α = 0.96); and validity evidence based on relations to other variables, specifically the test-criterion relationship (ρ = 0.680). Finally, we discuss further developments of the instrument and its possible implications for EHS workers.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26234736','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26234736"><span>Global inequities between polluters and the polluted: climate change impacts on coral reefs.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wolff, Nicholas H; Donner, Simon D; Cao, Long; Iglesias-Prieto, Roberto; Sale, Peter F; Mumby, Peter J</p> <p>2015-11-01</p> <p>For many ecosystem services, it remains uncertain whether the impacts of climate change will be mostly negative or positive and how these changes will be geographically distributed. These unknowns hamper the identification of regional winners and losers, which can influence debate over climate policy. Here, we use coral reefs to explore the spatial variability of climate stress by modelling the ecological impacts of rising sea temperatures and ocean acidification, two important coral stressors associated with increasing greenhouse gas (GHG) emissions. We then combine these results with national per capita emissions to quantify inequities arising from the distribution of cause (CO2 emissions) and effect (stress upon reefs) among coral reef countries. We find pollution and coral stress are spatially decoupled, creating substantial inequity of impacts as a function of emissions. We then consider the implications of such inequity for international climate policy. Targets for GHG reductions are likely to be tied to a country's emissions. Yet within a given level of GHG emissions, our analysis reveals that some countries experience relatively high levels of impact and will likely experience greater financial cost in terms of lost ecosystem productivity and more extensive adaptation measures. We suggest countries so disadvantaged be given access to international adaptation funds proportionate with impacts to their ecosystem. We raise the idea that funds could be more equitably allocated by formally including a metric of equity within a vulnerability framework. © 2015 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=338471','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=338471"><span>Flexible stocking as a strategy for enhancing ranch profitability in the face of a changing and variable climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Predicted climate change impacts include increased weather variability and increased occurrences of extreme events such as drought. Such climate changes potentially affect cattle performance as well as pasture and range productivity. These climate induced risks are often coupled with variable market...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMPP44A..03Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMPP44A..03Z"><span>Heinrich events simulated across the glacial</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ziemen, F. A.; Mikolajewicz, U.</p> <p>2015-12-01</p> <p>Heinrich events are among the most prominent climate change events recorded in proxies across the northern hemisphere. They are the archetype of ice sheet — climate interactions on millennial time scales. Nevertheless, the exact mechanisms that cause Heinrich events are still under discussion, and their climatic consequences are far from being fully understood. We contribute to answering the open questions by studying Heinrich events in a coupled ice sheet model (ISM) atmosphere-ocean-vegetation general circulation model (AOVGCM) framework, where this variability occurs as part of the model generated internal variability. The setup consists of a northern hemisphere setup of the modified Parallel Ice Sheet Model (mPISM) coupled to the global AOVGCM ECHAM5/MPIOM/LPJ. The simulations were performed fully coupled and with transient orbital and greenhouse gas forcing. They span from several millennia before the last glacial maximum into the deglaciation. We analyze simulations where the ISM is coupled asynchronously to the AOVGCM and simulations where the ISM and the ocean model are coupled synchronously and the atmosphere model is coupled asynchronously to them. The modeled Heinrich events show a marked influence of the ice discharge on the Atlantic circulation and heat transport.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20404180','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20404180"><span>Linking global climate and temperature variability to widespread amphibian declines putatively caused by disease.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Rohr, Jason R; Raffel, Thomas R</p> <p>2010-05-04</p> <p>The role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial, and the effect of climatic variability, in particular, has largely been ignored. For instance, it was recently revealed that the proposed link between climate change and widespread amphibian declines, putatively caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), was tenuous because it was based on a temporally confounded correlation. Here we provide temporally unconfounded evidence that global El Niño climatic events drive widespread amphibian losses in genus Atelopus via increased regional temperature variability, which can reduce amphibian defenses against pathogens. Of 26 climate variables tested, only factors associated with temperature variability could account for the spatiotemporal patterns of declines thought to be associated with Bd. Climatic predictors of declines became significant only after controlling for a pattern consistent with epidemic spread (by temporally detrending the data). This presumed spread accounted for 59% of the temporal variation in amphibian losses, whereas El Niño accounted for 59% of the remaining variation. Hence, we could account for 83% of the variation in declines with these two variables alone. Given that global climate change seems to increase temperature variability, extreme climatic events, and the strength of Central Pacific El Niño episodes, climate change might exacerbate worldwide enigmatic declines of amphibians, presumably by increasing susceptibility to disease. These results suggest that changes to temperature variability associated with climate change might be as significant to biodiversity losses and disease emergence as changes to mean temperature.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12..741B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12..741B"><span>Effects of short-term variability of meteorological variables on soil temperature in permafrost regions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias</p> <p>2018-03-01</p> <p>Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14..194L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14..194L"><span>Climate change and viticulture in Mediterranean climates: the complex response of socio-ecosystems. A comparative case study from France and Australia (1955-2040)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lereboullet, A.-L.; Beltrando, G.; Bardsley, D. K.</p> <p>2012-04-01</p> <p>The wine industry is very sensitive to extreme weather events, especially to temperatures above 35°C and drought. In a context of global climate change, Mediterranean climate regions are predicted to experience higher variability in rainfall and temperatures and an increased occurrence of extreme weather events. Some viticultural systems could be particularly at risk in those regions, considering their marginal position in the growth climatic range of Vitis vinifera, the long commercial lifespan of a vineyard, the high added-value of wine and the volatile nature of global markets. The wine industry, like other agricultural systems, is inserted in complex networks of climatic and non-climatic (other physical, economical, social and legislative) components, with constant feedbacks. We use a socio-ecosystem approach to analyse the adaptation of two Mediterranean viticultural systems to recent and future increase of extreme weather events. The present analysis focuses on two wine regions with a hot-summer Mediterranean climate (CSb type in the Köppen classification): Côtes-du-Roussillon in southern France and McLaren Vale in southern Australia. Using climate data from two synoptic weather stations, Perpignan (France) and Adelaide (Australia), with time series running from 1955 to 2010, we highlight changes in rainfall patterns and an increase in the number of days with Tx >35°c since the last three decades in both regions. Climate models (DRIAS project data for France and CSIRO Mk3.5 for Australia) project similar trends in the future. To date, very few projects have focused on an international comparison of the adaptive capacity of viticultural systems to climate change with a holistic approach. Here, the analysis of climate data was complemented by twenty in-depth semi-structured interviews with key actors of the two regional wine industries, in order to analyse adaptation strategies put in place regarding recent climate evolution. This mixed-methods approach allows for a comprehensive assessment of adaptation capacity of the two viticultural systems to future climate change. The strategies of grape growers and wine producers focus on maintaining optimal yields and a constant wine style adapted to markets in a variable and uncertain climate. Their implementation and efficiency depend strongly on non-climatic factors. Thus, adaptation capacity to recent and future climate change depends strongly on adaptation to other non-climatic changes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3295284','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3295284"><span>Timing of climate variability and grassland productivity</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Craine, Joseph M.; Nippert, Jesse B.; Elmore, Andrew J.; Skibbe, Adam M.; Hutchinson, Stacy L.; Brunsell, Nathaniel A.</p> <p>2012-01-01</p> <p>Future climates are forecast to include greater precipitation variability and more frequent heat waves, but the degree to which the timing of climate variability impacts ecosystems is uncertain. In a temperate, humid grassland, we examined the seasonal impacts of climate variability on 27 y of grass productivity. Drought and high-intensity precipitation reduced grass productivity only during a 110-d period, whereas high temperatures reduced productivity only during 25 d in July. The effects of drought and heat waves declined over the season and had no detectable impact on grass productivity in August. If these patterns are general across ecosystems, predictions of ecosystem response to climate change will have to account not only for the magnitude of climate variability but also for its timing. PMID:22331914</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22889171','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22889171"><span>Selection of climate change scenario data for impact modelling.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sloth Madsen, M; Maule, C Fox; MacKellar, N; Olesen, J E; Christensen, J Hesselbjerg</p> <p>2012-01-01</p> <p>Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ERL....13f4026S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ERL....13f4026S"><span>Internal variability in European summer temperatures at 1.5 °C and 2 °C of global warming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Suarez-Gutierrez, Laura; Li, Chao; Müller, Wolfgang A.; Marotzke, Jochem</p> <p>2018-06-01</p> <p>We use the 100-member Grand Ensemble with the climate model MPI-ESM to evaluate the controllability of mean and extreme European summer temperatures with the global mean temperature targets in the Paris Agreement. We find that European summer temperatures at 2 °C of global warming are on average 1 °C higher than at 1.5 °C of global warming with respect to pre-industrial levels. In a 2 °C warmer world, one out of every two European summer months would be warmer than ever observed in our current climate. Daily maximum temperature anomalies for extreme events with return periods of up to 500 years reach return levels of 7 °C at 2 °C of global warming and 5.5 °C at 1.5 °C of global warming. The largest differences in return levels for shorter return periods of 20 years are over southern Europe, where we find the highest mean temperature increase. In contrast, for events with return periods of over 100 years these differences are largest over central Europe, where we find the largest changes in temperature variability. However, due to the large effect of internal variability, only four out of every ten summer months in a 2 °C warmer world present mean temperatures that could be distinguishable from those in a 1.5 °C world. The distinguishability between the two climates is largest over southern Europe, while decreasing to around 10% distinguishable months over eastern Europe. Furthermore, we find that 10% of the most extreme and severe summer maximum temperatures in a 2 °C world could be avoided by limiting global warming to 1.5 °C.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23438320','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23438320"><span>Means and extremes: building variability into community-level climate change experiments.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Thompson, Ross M; Beardall, John; Beringer, Jason; Grace, Mike; Sardina, Paula</p> <p>2013-06-01</p> <p>Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of 'generations' based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new 'generation' of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. © 2013 John Wiley & Sons Ltd/CNRS.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.5886P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.5886P"><span>Assessment of the uncertainty in future projection for summer climate extremes over the East Asia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Park, Changyong; Min, Seung-Ki; Cha, Dong-Hyun</p> <p>2017-04-01</p> <p>Future projections of climate extremes in regional and local scales are essential information needed for better adapting to climate changes. However, future projections hold larger uncertainty factors arising from internal and external processes which reduce the projection confidence. Using CMIP5 (Coupled Model Intercomparison Project Phase 5) multi-model simulations, we assess uncertainties in future projections of the East Asian temperature and precipitation extremes focusing on summer. In examining future projection, summer mean and extreme projections of the East Asian temperature and precipitation would be larger as time. Moreover, uncertainty cascades represent wider scenario difference and inter-model ranges with increasing time. A positive mean-extreme relation is found in projections for both temperature and precipitation. For the assessment of uncertainty factors for these projections, dominant uncertainty factors from temperature and precipitation change as time. For uncertainty of mean and extreme temperature, contributions of internal variability and model uncertainty declines after mid-21st century while role of scenario uncertainty grows rapidly. For uncertainty of mean precipitation projections, internal variability is more important than the scenario uncertainty. Unlike mean precipitation, extreme precipitation shows that the scenario uncertainty is expected to be a dominant factor in 2090s. The model uncertainty holds as an important factor for both mean and extreme precipitation until late 21st century. The spatial changes for the uncertainty factors of mean and extreme projections generally are expressed according to temporal changes of the fraction of total variance from uncertainty factors in many grids of the East Asia. ACKNOWLEDGEMENTS The research was supported by the Korea Meteorological Administration Research and Development program under grant KMIPA 2015-2083 and the National Research Foundation of Korea Grant funded by the Ministry of Science, ICT and Future Planning of Korea (NRF-2016M3C4A7952637) for its support and assistant in completion of the study.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMPA43A2177P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMPA43A2177P"><span>Integrated analysis considered mitigation cost, damage cost and adaptation cost in Northeast Asia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Park, J. H.; Lee, D. K.; Kim, H. G.; Sung, S.; Jung, T. Y.</p> <p>2015-12-01</p> <p>Various studies show that raising the temperature as well as storms, cold snap, raining and drought caused by climate change. And variety disasters have had a damage to mankind. The world risk report(2012, The Nature Conservancy) and UNU-EHS (the United Nations University Institute for Environment and Human Security) reported that more and more people are exposed to abnormal weather such as floods, drought, earthquakes, typhoons and hurricanes over the world. In particular, the case of Korea, we influenced by various pollutants which are occurred in Northeast Asian countries, China and Japan, due to geographical meteorological characteristics. These contaminants have had a significant impact on air quality with the pollutants generated in Korea. Recently, around the world continued their effort to reduce greenhouse gas and to improve air quality in conjunction with the national or regional development goals priority. China is also working on various efforts in accordance with the international flows to cope with climate change and air pollution. In the future, effect of climate change and air quality in Korea and Northeast Asia will be change greatly according to China's growth and mitigation policies. The purpose of this study is to minimize the damage caused by climate change on the Korean peninsula through an integrated approach taking into account the mitigation and adaptation plan. This study will suggest a climate change strategy at the national level by means of a comprehensive economic analysis of the impacts and mitigation of climate change. In order to quantify the impact and damage cost caused by climate change scenarios in a regional scale, it should be priority variables selected in accordance with impact assessment of climate change. The sectoral impact assessment was carried out on the basis of selected variables and through this, to derive the methodology how to estimate damage cost and adaptation cost. And then, the methodology was applied in Korea. Finally, we build an integrated analysis considered mitigation cost, damage cost, and adaptation cost by climate change</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ESD.....6..311F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ESD.....6..311F"><span>Exploring objective climate classification for the Himalayan arc and adjacent regions using gridded data sources</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Forsythe, N.; Blenkinsop, S.; Fowler, H. J.</p> <p>2015-05-01</p> <p>A three-step climate classification was applied to a spatial domain covering the Himalayan arc and adjacent plains regions using input data from four global meteorological reanalyses. Input variables were selected based on an understanding of the climatic drivers of regional water resource variability and crop yields. Principal component analysis (PCA) of those variables and k-means clustering on the PCA outputs revealed a reanalysis ensemble consensus for eight macro-climate zones. Spatial statistics of input variables for each zone revealed consistent, distinct climatologies. This climate classification approach has potential for enhancing assessment of climatic influences on water resources and food security as well as for characterising the skill and bias of gridded data sets, both meteorological reanalyses and climate models, for reproducing subregional climatologies. Through their spatial descriptors (area, geographic centroid, elevation mean range), climate classifications also provide metrics, beyond simple changes in individual variables, with which to assess the magnitude of projected climate change. Such sophisticated metrics are of particular interest for regions, including mountainous areas, where natural and anthropogenic systems are expected to be sensitive to incremental climate shifts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19625300','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19625300"><span>Integrating bioclimate with population models to improve forecasts of species extinctions under climate change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Brook, Barry W; Akçakaya, H Resit; Keith, David A; Mace, Georgina M; Pearson, Richard G; Araújo, Miguel B</p> <p>2009-12-23</p> <p>Climate change is already affecting species worldwide, yet existing methods of risk assessment have not considered interactions between demography and climate and their simultaneous effect on habitat distribution and population viability. To address this issue, an international workshop was held at the University of Adelaide in Australia, 25-29 May 2009, bringing leading species distribution and population modellers together with plant ecologists. Building on two previous workshops in the UK and Spain, the participants aimed to develop methodological standards and case studies for integrating bioclimatic and metapopulation models, to provide more realistic forecasts of population change, habitat fragmentation and extinction risk under climate change. The discussions and case studies focused on several challenges, including spatial and temporal scale contingencies, choice of predictive climate, land use, soil type and topographic variables, procedures for ensemble forecasting of both global climate and bioclimate models and developing demographic structures that are realistic and species-specific and yet allow generalizations of traits that make species vulnerable to climate change. The goal is to provide general guidelines for assessing the Red-List status of large numbers of species potentially at risk, owing to the interactions of climate change with other threats such as habitat destruction, overexploitation and invasive species.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23066755','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23066755"><span>Climate forecasts in disaster management: Red Cross flood operations in West Africa, 2008.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Braman, Lisette Martine; van Aalst, Maarten Krispijn; Mason, Simon J; Suarez, Pablo; Ait-Chellouche, Youcef; Tall, Arame</p> <p>2013-01-01</p> <p>In 2008, the International Federation of Red Cross and Red Crescent Societies (IFRC) used a seasonal forecast for West Africa for the first time to implement an Early Warning, Early Action strategy for enhanced flood preparedness and response. Interviews with disaster managers suggest that this approach improved their capacity and response. Relief supplies reached flood victims within days, as opposed to weeks in previous years, thereby preventing further loss of life, illness, and setbacks to livelihoods, as well as augmenting the efficiency of resource use. This case demonstrates the potential benefits to be realised from the use of medium-to-long-range forecasts in disaster management, especially in the context of potential increases in extreme weather and climate-related events due to climate variability and change. However, harnessing the full potential of these forecasts will require continued effort and collaboration among disaster managers, climate service providers, and major humanitarian donors. © 2013 The Author(s). Journal compilation © Overseas Development Institute, 2013.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC33C1079S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC33C1079S"><span>Atmospheric Teleconnection and Climate Variability: Affecting Rice Productivity of Bihar, India</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Saini, A.</p> <p>2017-12-01</p> <p>Climate variability brought various negative results to the environment around us and area under rice crop in Bihar has also faced a lot of negative impacts due to variability in temperature and rainfall. Location of Bihar in Northern Plain of India automatically makes it prime location for agriculture and therefore variability in climatic variables brings highly sensitive results to the agricultural production (especially rice). In this study, rainfall and temperature variables are taken into consideration to investigate the impact on rice cultivated area. Change in climate variable with the passage of time is prevailing since the start of geological time scale, how the variability in climate variables has affected the major crops. Climate index of Pacific Ocean and Indian Ocean influences the seasonal weather in Bihar and therefore role of ENSO and IOD is an interesting point of inquiry. Does there exists direct relation between climate variability and area under agricultural crops? How many important variables directly signals towards the change in area under agriculture production? These entire questions are answered with respect to change in area under rice cultivation of Bihar State of India. Temperature, rainfall and ENSO are a good indicator with respect to rice cultivation in Indian subcontinent. Impact on the area under rice has been signaled through ONI, Niño3 and DMI. Increasing range of temperature in the rice productivity declining years is observed since 1990.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29024396','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29024396"><span>Health Impact of Climate Change in Older People: An Integrative Review and Implications for Nursing.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Leyva, Erwin William A; Beaman, Adam; Davidson, Patricia M</p> <p>2017-11-01</p> <p>Older people account for the highest proportion of mortality from extreme weather events associated with climate change. This article aims to describe the health impacts of climate change on older people. An integrative review was conducted with 30 studies retrieved from PubMed, EBSCO, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) on climate stressors, determinants of resilient capacity, risk factors, and health outcomes. Heat, temperature variability, and air pollution increase mortality risk in older people, especially from cardiovascular and respiratory diseases. Floods are linked with increasing incidence of post-traumatic stress disorder, depression, and anxiety. Facing these adversities, older people exhibit both vulnerability and resilience. Research gaps exist in understanding the full spectrum of the resilience experience of older people, and appreciating areas wherein nursing can play a pivotal role. Recognizing the vulnerabilities of older people in the context of climate change is important. Identifying opportunities to promote resilience is an important focus for nurses to develop tailored and targeted nursing interventions. © 2017 Sigma Theta Tau International.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/of/2009/1115/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/of/2009/1115/"><span>Framework for a U.S. Geological Survey Hydrologic Climate-Response Program in Maine</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Hodgkins, Glenn A.; Lent, Robert M.; Dudley, Robert W.; Schalk, Charles W.</p> <p>2009-01-01</p> <p>This report presents a framework for a U.S. Geological Survey (USGS) hydrologic climate-response program designed to provide early warning of changes in the seasonal water cycle of Maine. Climate-related hydrologic changes on Maine's rivers and lakes in the winter and spring during the last century are well documented, and several river and lake variables have been shown to be sensitive to air-temperature changes. Monitoring of relevant hydrologic data would provide important baseline information against which future climate change can be measured. The framework of the hydrologic climate-response program presented here consists of four major parts: (1) identifying homogeneous climate-response regions; (2) identifying hydrologic components and key variables of those components that would be included in a hydrologic climate-response data network - as an example, streamflow has been identified as a primary component, with a key variable of streamflow being winter-spring streamflow timing; the data network would be created by maintaining existing USGS data-collection stations and establishing new ones to fill data gaps; (3) regularly updating historical trends of hydrologic data network variables; and (4) establishing basins for process-based studies. Components proposed for inclusion in the hydrologic climate-response data network have at least one key variable for which substantial historical data are available. The proposed components are streamflow, lake ice, river ice, snowpack, and groundwater. The proposed key variables of each component have extensive historical data at multiple sites and are expected to be responsive to climate change in the next few decades. These variables are also important for human water use and (or) ecosystem function. Maine would be divided into seven climate-response regions that follow major river-basin boundaries (basins subdivided to hydrologic units with 8-digit codes or larger) and have relatively homogeneous climates. Key hydrologic variables within each climate-response region would be analyzed regularly to maintain up-to-date analyses of year-to-year variability, decadal variability, and longer term trends. Finally, one basin in each climate-response region would be identified for process-based hydrologic and ecological studies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.4890O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.4890O"><span>Sensitivity of the East African rift lakes to climate variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Olaka, L.; Trauth, M. H.</p> <p>2009-04-01</p> <p>Lakes in the East African Rift have provided excellent proxies to reconstruct past climate changes in the low latitudes. The lakes occupy volcano-tectonic depressions with highly variable climate and hydrological setting, that present a good opportunity to study the climatic and hydrogeological influences on the lake water budget. Previous studies have used lake floor sediments to establish the sensitivity of the East African rift lakes. This study focuses on geomorphology and climate to offer additional or alternative record of lake history that are key to quantifying sensitivity of these lakes as archives to external and internal climatic forcings. By using the published Holocene lake areas and levels, we analyze twelve lakes on the eastern arm of the East African rift; Ziway, Awassa, Turkana, Suguta, Baringo, Nakuru, Elmenteita, Naivasha, Natron, Manyara and compare with Lake Victoria, that occupies the plateau between the east and the western arms of the rift. Using the SRTM data, Hypsometric (area-altitude) analysis has been used to compare the lake basins between latitude 80 North and 30 South. The mean elevation for the lakes, is between 524 and 2262 meters above sea level, the lakes' hypsometric integrals (HI), a measure of landmass volume above the reference plane, vary from 0.31 to 0.76. The aridity index (Ai), defined as Precipitation/ Evapotranspiration, quantifies the water available to a lake, it encompasses land cover and climatic effects. It is lowest (arid) in the basin between the Ethiopian rift and the Kenyan rift and at the southern termination of the Kenyan Rift in the catchments of lake Turkana, Suguta, Baringo and Manyara with values of 0.55, 0.43, 0.43 and 0.5 respectively. And it is highest (wet) in the catchments of, Ziway, Awassa, Nakuru and Naivasha as 1.33,1.03 and 1.2 respectively, which occupy the highest points of the rift. Lake Victoria has an index of 1.42 the highest of these lakes and receives a high precipitation. We use a simple model written on a Matlab code to illustrate the lake volume and area response to climate of surficialy closed, graben shaped and panshaped lake basins. From preliminary results, lake basins that are sensitive to climate variability have a high HI and high aridity index, which will be presented in this conference</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.3276T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.3276T"><span>Urban Biometeorology: analysis of the air pollution and climate change on cognition and physical abilities of geriatric population of São Paulo City</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Teixeira Gonçalves, Fabio Luiz; Jacob, Wilson; Alucci, Marcia; Busse, Alexandre; Duarte, Denise; Monteiro, Leonardo; Trezza, Beatriz; Tribess, Arlindo; Batista, Rafael; Ambrizzi, Tercip</p> <p>2013-04-01</p> <p>This is a multidisciplinary Project, which emphasizes geriatric population impacts, i. e., over 65 years old, of meteorological variables and air pollutants (such as particulate matter) associated to human health, and concerning to the real climatology and climate change in the Metropolitan Region of São Paulo. This is a biometeorological study, human subdivision, based on ISB (International Society of Biometeorology). According to the society, the environmental effects are considered meteorotropics where one or more environmental variables (meteorological or climatic even air pollution) affect one or more individuals of a population. Atmospheric pollution will be analyzed using a personal particulate matter multi-collector, concerning the impact of unfavorable meteorological conditions where the impacts will be evaluated comparing the test results during dry season (high air pollutant concentrations) and wet season (low pollutant concentrations). Therefore, the aim of this study will be to evaluate the cognitive and physical performance of a geriatric population in a pre-selected group of aged people which are considered as capable (healthy). This performance is affected by environmental conditions which thermal comfort (where meteorological variables act together) and air pollution are the meteorotropic ones. Consequently, one of the aims of the study is to establish a human thermal comfort index for geriatric populations. Architectural premises (thermal performance and ergonomics) will be also developed. An acclimatized chamber will be used to simulate the extremes of São Paulo climate and to propose a thermal comfort index. Indoors (chamber) and outdoors will be used in order to compare the impact on the selected aged people. Finally, the climate change will be based on GCM's global models which show the meteorological variations in order to calculate their impact on a comfort index. The physical and cognitive performances and architectural premises (thermal performance and ergonomics) will be analyzed inside of the climatic chamber. The preliminary results for future (climate change for 2070-2100) comfort indexes present a reasonable impact for heat discomfort during the summer and less cold discomfort during wintertime.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.9489S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.9489S"><span>From South to North: flowering phenological responses at different geographical latitudes in 12 European countries</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Szabó, Barbara; Lehoczky, Annamária; Filzmoser, Peter; Templ, Matthias; Szentkirályi, Ferenc; Pongrácz, Rita; Ortner, Thomas; Mert, Can; Czúcz, Bálint</p> <p>2014-05-01</p> <p>Phenological sensitivity of plants strongly depends on regional climate variability, moreover it is also influenced by large-scale atmospheric circulation patterns. Plants in different environmental conditions (determined by geographical latitude and longitude, altitude, continentality) may show diverse responses to climate change. The first results of an international cooperation aiming at the analysis of plant phenological data along a latitudinal gradient over 12 European countries (Macedonia, Bosnia and Herzegovina, Montenegro, Slovenia, Croatia, Hungary, Slovakia, Poland, Lithuania, Latvia, Estonia and Finland) are presented. The spatio-temporal changes in the flowering onset dates of common lilac (Syringa vulgaris L.) during the period of 1970-2000 were analysed. To characterise the environmental conditions driving the phenological responses, climatic variables (atmospheric pressure, air temperature, precipitation) obtained from a gridded observational dataset (E-OBS 9.0) and time series of the North Atlantic Oscillation (NAO) index were used. Preliminary results for this particular species found a gradual advance of mean flowering onsets along latitudes from 40° N to 65° N, at the rate of -0.12 to -0.32 day/year. Significant zonal differences were found in these rates, which can be explained by the sensitivity of flowering to climatic conditions while moving from Mediterranen to boreal regions of Europe. Thus our results were coherent with most observations in the literature, that higher latitudes can exhibit more pronounced responses, particularly in case of spring phenological events.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMPP31B1484Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMPP31B1484Y"><span>Fluctuations in Tree Ring Cellulose d18O during the Little Ice Age Correlate with Solar Activity</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yamaguchi, Y. T.; Yokoyama, Y.; Miyahara, H.; Nakatsuka, T.</p> <p>2008-12-01</p> <p>The Maunder Minimum (AD1645-1715), when sunspots became exceedingly rare, is known to coincide with the coldest period during the Little Ice Age. This is a useful period to investigate possible linkage between solar activity and climate because variation in solar activity was different from that of today. The solar cycle length was longer (14 and 28 years) than that of today (11 and 22 years) hence any climate archives that have similar periodic changes could be separated from other internal climate forcing. We have reported that Greenland temperature variations coincided with decadal-scale variability in solar activity during the Maunder Minimum (Miyahara et al. 2008). Here we report interannual and intra-annual relative humidity (RH) variations in central Japan during that period, using tree ring cellulose d18O in a 382-year-old Japanese cedar tree (Cryptomeria japonica). The isotopic composition of tree rings can be a powerful tool to study the relationship between solar activity and climate, because we can directly compare solar activity (D14C) and climate (d18O) with little dating error. The climate proxy obtained using tree ring cellulose d18O is correlated both negatively and positively with RH and d18O in precipitation, respectively. Since d18O in precipitation is negatively correlated with the amount of precipitation in the monsoon area, tree ring cellulose d18O can be a reliable proxy for past RH and/or amount of precipitation in the area of the interest. Tree ring cellulose d18O of the cedar tree during AD1938-1998 in fact correlates significantly with the mean RH in June in central Japan. Tree ring d18O inferred RH variability during the Maunder Minimum shows distinct high RH spikes with an approximate 14-year quasiperiodicity. All nine solar minima during AD1640-1756 deduced from tree ring D14C coincided with high RH spikes, and seven of which coincided within 1-year. Interannual RH variations also coincided with Greenland temperature during this period. These results suggest that weakening of solar activity at solar minima caused distinct hemispheric scale climate change during the Maunder Minimum. We discuss the mechanism in which the solar activity variation caused the climate change, based on intra-annual RH variability and further data analysis of interannual RH variability. H. Miyahara et al., Earth Planet. Sci. Lett. 272, 1-2, 290-295 (2008).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1253370','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1253370"><span>The footprint of the inter-decadal Pacific oscillation in Indian Ocean sea surface temperatures</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Dong, Lu; Zhou, Tianjun; Dai, Aiguo</p> <p></p> <p>Superimposed on a pronounced warming trend, the Indian Ocean (IO) sea surface temperatures (SSTs) also show considerable decadal variations that can cause regional climate oscillations around the IO. However, the mechanisms of the IO decadal variability remain unclear. Here we perform numerical experiments using a state-of-the-art, fully coupled climate model in which the external forcings with or without the observed SSTs in the tropical eastern Pacific Ocean (TEP) are applied for 1871–2012. Both the observed timing and magnitude of the IO decadal variations are well reproduced in those experiments with the TEP SSTs prescribed to observations. Although the external forcingsmore » account for most of the warming trend, the decadal variability in IO SSTs is dominated by internal variability that is induced by the TEP SSTs, especially the Inter-decadal Pacific Oscillation (IPO). The IPO weakens (enhances) the warming of the external forcings by about 50% over the IO during IPO’s cold (warm) phase, which contributes about 10% to the recent global warming hiatus since 1999. As a result, the decadal variability in IO SSTs is modulated by the IPO-induced atmospheric adjustment through changing surface heat fluxes, sea surface height and thermocline depth.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1253370-footprint-inter-decadal-pacific-oscillation-indian-ocean-sea-surface-temperatures','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1253370-footprint-inter-decadal-pacific-oscillation-indian-ocean-sea-surface-temperatures"><span>The footprint of the inter-decadal Pacific oscillation in Indian Ocean sea surface temperatures</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Dong, Lu; Zhou, Tianjun; Dai, Aiguo; ...</p> <p>2016-02-17</p> <p>Superimposed on a pronounced warming trend, the Indian Ocean (IO) sea surface temperatures (SSTs) also show considerable decadal variations that can cause regional climate oscillations around the IO. However, the mechanisms of the IO decadal variability remain unclear. Here we perform numerical experiments using a state-of-the-art, fully coupled climate model in which the external forcings with or without the observed SSTs in the tropical eastern Pacific Ocean (TEP) are applied for 1871–2012. Both the observed timing and magnitude of the IO decadal variations are well reproduced in those experiments with the TEP SSTs prescribed to observations. Although the external forcingsmore » account for most of the warming trend, the decadal variability in IO SSTs is dominated by internal variability that is induced by the TEP SSTs, especially the Inter-decadal Pacific Oscillation (IPO). The IPO weakens (enhances) the warming of the external forcings by about 50% over the IO during IPO’s cold (warm) phase, which contributes about 10% to the recent global warming hiatus since 1999. As a result, the decadal variability in IO SSTs is modulated by the IPO-induced atmospheric adjustment through changing surface heat fluxes, sea surface height and thermocline depth.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009271','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009271"><span>Analysis of the Relationship Between Climate and NDVI Variability at Global Scales</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zeng, Fan-Wei; Collatz, G. James; Pinzon, Jorge; Ivanoff, Alvaro</p> <p>2011-01-01</p> <p>interannual variability in modeled (CASA) C flux is in part caused by interannual variability in Normalized Difference Vegetation Index (NDVI) Fraction of Photosynthetically Active Radiation (FPAR). This study confirms a mechanism producing variability in modeled NPP: -- NDVI (FPAR) interannual variability is strongly driven by climate; -- The climate driven variability in NDVI (FPAR) can lead to much larger fluctuation in NPP vs. the NPP computed from FPAR climatology</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.7678M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.7678M"><span>Antarctic warming driven by internal Southern Ocean deep convection oscillations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Martin, Torge; Pedro, Joel B.; Steig, Eric J.; Jochum, Markus; Park, Wonsun; Rasmussen, Sune O.</p> <p>2016-04-01</p> <p>Simulations with the free-running, complex coupled Kiel Climate Model (KCM) show that heat release associated with recurring Southern Ocean deep convection can drive centennial-scale Antarctic temperature variations of 0.5-2.0 °C. We propose a mechanism connecting the intrinsic ocean variability with Antarctic warming that involves the following three steps: Preconditioning: heat supplied by the lower branch of the Atlantic Meridional Overturning Circulation (AMOC) accumulates at depth in the Southern Ocean, trapped by the Weddell Gyre circulation; Convection onset: wind and/or sea-ice changes tip the preconditioned, thermally unstable system into the convective state; Antarctic warming: fast sea-ice-albedo feedbacks (on annual to decadal timescales) and slower Southern Ocean frontal and sea-surface temperature adjustments to the convective heat release (on multi-decadal to centennial timescales), drive an increase in atmospheric heat and moisture transport towards Antarctica resulting in warming over the continent. Further, we discuss the potential role of this mechanism to explain climate variability observed in Antarctic ice-core records.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1610754V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1610754V"><span>A variant of the anomaly initialisation approach for global climate forecast models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco; Hawkins, Ed; Nichols, Nancy; Carrassi, Alberto</p> <p>2014-05-01</p> <p>This work presents a refined method of anomaly initialisation (AI) applied to the ocean and sea ice components of the global climate forecast model EC-Earth, with the following particularities: - the use of a weight to the anomalies, in order to avoid the risk of introducing too big anomalies recorded in the observed state, whose amplitude does not fit the range of the internal variability generated by the model. - the AI of the temperature and density ocean state variables instead of the temperature and salinity. Results show that the use of such refinements improve the skill over the Arctic region, part of the North and South Atlantic, part of the North and South Pacific and the Mediterranean Sea. In the Tropical Pacific the full field initialised experiment performs better. This is probably due to a displacement of the observed anomalies caused by the use of the AI technique. Furthermore, preliminary results of an anomaly nudging experiment are discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28635270','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28635270"><span>Understanding the Effects of Genotype, Growing Year, and Breeding on Tunisian Durum Wheat Allergenicity. 2. The Celiac Disease Case.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Boukid, Fatma; Prandi, Barbara; Sforza, Stefano; Sayar, Rhouma; Seo, Yong Weon; Mejri, Mondher; Yacoubi, Ines</p> <p>2017-07-19</p> <p>The aim of this study was to compare immunogenic and toxic gluten peptides related to celiac disease (CD). 100 accessions of genotypes selected during the 20th century in Tunisia were in vitro digested and then analyzed by UPLC/ESI-MS technique using an isotopically labeled internal standard. The first MANOVA confirmed a high variability in the content of immunogenic and toxic peptides reflecting high genetic diversity in the germplasm released during the past century in Tunisia, consistently with PCA and clustering analysis results. Our finding showed also important variability in CD epitopes due to growing season's climate scenarios. Moreover, the second MANOVA revealed significant differences between abandoned and modern cultivars' CD-related peptide amounts. Although we could not conclude that there was an augment of allergens in newly selected durum wheat lines compared to abandoned ones, we demonstrated that modern genotype peptides were less sensitive to climate variation, which is a useful indicator for wheat breeders.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.9940D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.9940D"><span>The Stochastic predictability limits of GCM internal variability and the Stochastic Seasonal to Interannual Prediction System (StocSIPS)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Del Rio Amador, Lenin; Lovejoy, Shaun</p> <p>2017-04-01</p> <p>Over the past ten years, a key advance in our understanding of atmospheric variability is the discovery that between the weather and climate regime lies an intermediate "macroweather" regime, spanning the range of scales from ≈10 days to ≈30 years. Macroweather statistics are characterized by two fundamental symmetries: scaling and the factorization of the joint space-time statistics. In the time domain, the scaling has low intermittency with the additional property that successive fluctuations tend to cancel. In space, on the contrary the scaling has high (multifractal) intermittency corresponding to the existence of different climate zones. These properties have fundamental implications for macroweather forecasting: a) the temporal scaling implies that the system has a long range memory that can be exploited for forecasting; b) the low temporal intermittency implies that mathematically well-established (Gaussian) forecasting techniques can be used; and c), the statistical factorization property implies that although spatial correlations (including teleconnections) may be large, if long enough time series are available, they are not necessarily useful in improving forecasts. Theoretically, these conditions imply the existence of stochastic predictability limits in our talk, we show that these limits apply to GCM's. Based on these statistical implications, we developed the Stochastic Seasonal and Interannual Prediction System (StocSIPS) for the prediction of temperature from regional to global scales and from one month to many years horizons. One of the main components of StocSIPS is the separation and prediction of both the internal and externally forced variabilities. In order to test the theoretical assumptions and consequences for predictability and predictions, we use 41 different CMIP5 model outputs from preindustrial control runs that have fixed external forcings: whose variability is purely internally generated. We first show that these statistical assumptions hold with relatively good accuracy and then we performed hindcasts at global and regional scales from monthly to annual time resolutions using StocSIPS. We obtained excellent agreement between the hindcast Mean Square Skill Score (MSSS) and the theoretical stochastic limits. We also show the application of StocSIPS to the prediction of average global temperature and compare our results with those obtained using multi-model ensemble approaches. StocSIPS has numerous advantages including a) higher MSSS for large time horizons, b) the from convergence to the real - not model - climate, c) much higher computational speed, d) no need for data assimilation, e) no ad hoc post processing and f) no need for downscaling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015DSRII.113....1H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015DSRII.113....1H"><span>Impacts of climate change on marine top predators: Advances and future challenges</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hobday, Alistair J.; Arrizabalaga, Haritz; Evans, Karen; Nicol, Simon; Young, Jock W.; Weng, Kevin C.</p> <p>2015-03-01</p> <p>Oceanic top predators are the subject of studies by researchers under the international Climate Impacts on Oceanic Top Predators (CLIOTOP) program. A wide range of data sets have shown that environmental conditions, such as temperature and marine productivity, affect the distribution and biological processes of these species, and thus the activities of the humans that depend on them. In this special issue, 25 papers arising from the 2nd CLIOTOP symposium, held in Noumea, New Caledonia in February 2013 report the importance of realistic physical descriptions of oceanic processes for climate change projections, demonstrate a wide range of predator responses to historical climate variability, describe new analytical approaches for understanding the physiology, behaviour and trophodynamics, and project future distributions for a range of species. Several contributions discuss the implications for conservation and fisheries and show that resolving ecosystem management challenges and conflicts in the face of climate change is possible, but will require attention by decision-makers to issues that are broader than their traditional mandate. In the coming years, an increased focus on the development of management options to reduce the impacts of climate change on top predators and their dependent industries is needed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940011445','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940011445"><span>Global Energy and Water Cycle Experiment (GEWEX) and the Continental-scale International Project (GCIP)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Vane, Deborah</p> <p>1993-01-01</p> <p>A discussion of the objectives of the Global Energy and Water Cycle Experiment (GEWEX) and the Continental-scale International Project (GCIP) is presented in vugraph form. The objectives of GEWEX are as follows: determine the hydrological cycle by global measurements; model the global hydrological cycle; improve observations and data assimilation; and predict response to environmental change. The objectives of GCIP are as follows: determine the time/space variability of the hydrological cycle over a continental-scale region; develop macro-scale hydrologic models that are coupled to atmospheric models; develop information retrieval schemes; and support regional climate change impact assessment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24652258','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24652258"><span>[Modelling the effect of local climatic variability on dengue transmission in Medellin (Colombia) by means of time series analysis].</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Rúa-Uribe, Guillermo L; Suárez-Acosta, Carolina; Chauca, José; Ventosilla, Palmira; Almanza, Rita</p> <p>2013-09-01</p> <p>Dengue fever is a major impact on public health vector-borne disease, and its transmission is influenced by entomological, sociocultural and economic factors. Additionally, climate variability plays an important role in the transmission dynamics. A large scientific consensus has indicated that the strong association between climatic variables and disease could be used to develop models to explain the incidence of the disease. To develop a model that provides a better understanding of dengue transmission dynamics in Medellin and predicts increases in the incidence of the disease. The incidence of dengue fever was used as dependent variable, and weekly climatic factors (maximum, mean and minimum temperature, relative humidity and precipitation) as independent variables. Expert Modeler was used to develop a model to better explain the behavior of the disease. Climatic variables with significant association to the dependent variable were selected through ARIMA models. The model explains 34% of observed variability. Precipitation was the climatic variable showing statistically significant association with the incidence of dengue fever, but with a 20 weeks delay. In Medellin, the transmission of dengue fever was influenced by climate variability, especially precipitation. The strong association dengue fever/precipitation allowed the construction of a model to help understand dengue transmission dynamics. This information will be useful to develop appropriate and timely strategies for dengue control.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003AGUFM.C41C0987R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003AGUFM.C41C0987R"><span>The International Arctic Buoy Programme (IABP)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rigor, I. G.; Ortmeyer, M.</p> <p>2003-12-01</p> <p>The Arctic has undergone dramatic changes in weather, climate and environment. It should be noted that many of these changes were first observed and studied using data from the International Arctic Buoy Programme (IABP). For example, IABP data were fundamental to Walsh et al. (1996) showing that atmospheric pressure has decreased, Rigor et al. (2000) showing that air temperatures have increased, and to Proshutinsky and Johnson (1997); Steele and Boyd, (1998); Kwok, (2000); and Rigor et al. (2002) showing that the clockwise circulation of sea ice and the ocean has weakened. All these results relied heavily on data from the IABP. In addition to supporting these studies of climate change, the IABP observations are also used to forecast weather and ice conditions, validate satellite retrievals of environmental variables, to force, validate and initialize numerical models. Over 350 papers have been written using data from the IABP. The observations and datasets of the IABP data are one of the cornerstones for environmental forecasting and research in the Arctic.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/10154049','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/10154049"><span>International conference on the role of the polar regions in global change: Proceedings. Volume 2</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Weller, G.; Wilson, C.L.; Severin, B.A.B.</p> <p>1991-12-01</p> <p>The International Conference on the Role of the Polar Regions in Global Change took place on the campus of the University of Alaska Fairbanks on June 11--15, 1990. The goal of the conference was to define and summarize the state of knowledge on the role of the polar regions in global change, and to identify gaps in knowledge. To this purpose experts in a wide variety of relevant disciplines were invited to present papers and hold panel discussions. While there are numerous conferences on global change, this conference dealt specifically with the polar regions which occupy key positions in themore » global system. These two volumes of conference proceedings include papers on (1) detection and monitoring of change; (2) climate variability and climate forcing; (3) ocean, sea ice, and atmosphere interactions and processes; and (4) effects on biota and biological feedbacks; (5) ice sheet, glacier and permafrost responses and feedbacks, (6) paleoenvironmental studies; and, (7) aerosol and trace gases.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA.....1505D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA.....1505D"><span>300 Years of East African Climate Variability from Oxygen Isotopes in a Kenya Coral</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dunbar, R.</p> <p>2003-04-01</p> <p>Instrumental records of climate variability from the western Indian Ocean are relatively scarce and short. Here I present a monthly resolution stable isotopic record acquired from a large living coral head (Porites) from the Malindi Marine Reserve, Kenya (3^oS, 40^oE). The annual chronology is precise and is based on exceptionally clear high and low density growth band couplets. The record extends from 1696 to 1996 A.D., making it the longest coral climate record from the Indian Ocean and one of the longest available worldwide. We have analyzed the uppermost portion of the coral colony in triplicate, using 3 separate cores. This upper section, used for calibration purposes, also provides estimates of signal fidelity and noise in the climate recording system internal to the colony. Coral δ18O at this site primarily records SST; linear regression of monthly coral δ18O vs. SST yields a slope of -0.26 ppm δ18O per ^oC, and δ18O explains ˜57% of the SST variance. Additional isotopic variability may result from changes in seawater δ18O due to local runoff or regional evaporation/precipitation balance, but these changes are likely to be small because local rainfall δ18O is not strongly depleted relative to seawater and salinity gradients are small. The coral record indicates a clear warming trend of about 1.5^oC that accelerates in the latest 20th century, superimposed on strong decadal variability that persists throughout the record. In fact, δ18O values in the 1990's exceed the 300 year envelope (they are lower) and correspond with apparently unprecedented coral bleaching in coastal East Africa. The decadal component of the Malindi coral record reflects a regional climate signal spanning much of the western equatorial Indian Ocean. In general, East African SST and rainfall are better correlated with Pacific ENSO indicators than with the Indian Monsoon at all periods (inter-annual through multi-decadal) but the correlation weakens after 1975. One dramatic new result we report here is a strong indication of a major cool and dry period from 1750--1820 A.D. This is the single largest multi-decadal anomaly of the past 300 years and correlates perfectly in time with the historically and anecdotally defined Lapanarat Drought. Our results indicate a strong link between multi-decadal tropical cold SST anomalies And far-reaching continental droughts in East Africa. Causes and links to other climate recording systems will be explored. Interannual-decadal SST variations are strongly coherent with ENSO indices and other ENSO-sensitive coral records on decadal and interannual time scales. The decadal component of the Malindi coral record reflects a regional climate signal spanning much of the western equatorial Indian Ocean. Previous work has argued that this component likely reflects a monsoonal influence. However, decadal variance in both Malindi and Seychelles (Charles et al. 1997) coral records is more strongly coherent with ENSO indices than with the India or East Africa rain indices. The coherency of both coral records with Pacific indicators suggests instead that Indian Ocean variability reflects decadal ENSO-like variability originating in the Pacific. These records don't correlate significantly with the Pacific Decadal Oscillation implying a dominant role for the tropical Pacific (as opposed to extra-tropical regions) as a source of regional decadal variability in the western Indian Ocean. This work confirms that the tropical Pacific can act as an agent of decadal climate variability over a very large spatial scale.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007EOSTr..88..111G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007EOSTr..88..111G"><span>Reconstruction of Past Mediterranean Climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>García-Herrera, Ricardo; Luterbacher, Jürg; Lionello, Piero; Gonzáles-Rouco, Fidel; Ribera, Pedro; Rodó, Xavier; Kull, Christoph; Zerefos, Christos</p> <p>2007-02-01</p> <p>First MEDCLIVAR Workshop on Reconstruction of Past Mediterranean Climate; Pablo de Olavide University, Carmona, Spain, 8-11 November 2006; Mediterranean Climate Variability and Predictability (MEDCLIVAR; http://www.medclivar.eu) is a program that coordinates and promotes research on different aspects of Mediterranean climate. The main MEDCLIVAR goals include the reconstruction of past climate, describing patterns and mechanisms characterizing climate space-time variability, extremes at different time and space scales, coupled climate model/empirical reconstruction comparisons, seasonal forecasting, and the identification of the forcings responsible for the observed changes. The program has been endorsed by CLIVAR (Climate Variability and Predictability project) and is funded by the European Science Foundation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H32G..03H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H32G..03H"><span>Climate variability and demand growth as drivers of water scarcity in the Turkwel river basin: a bottom-up risk assessment of a data-sparse basin in Kenya</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hirpa, F. A.; Dyer, E.; Hope, R.; Dadson, S. J.</p> <p>2017-12-01</p> <p>Sustainable water management and allocation are essential for maintaining human well-being, sustaining healthy ecosystems, and supporting steady economic growth. The Turkwel river basin, located in north-western Kenya, experiences a high level of water scarcity due to its arid climate, high rainfall variability, and rapidly growing water demand. However, due to sparse hydro-climatic data and limited literature, the water resources system of the basin has been poorly understood. Here we apply a bottom-up climate risk assessment method to estimate the resilience of the basin's water resources system to growing demand and climate stressors. First, using a water resource system model and historical climate data, we construct a climate risk map that depicts the way in which the system responds to climate change and variability. Then we develop a set of water demand scenarios to identify the conditions that potentially lead to the risk of unmet water demand and groundwater depletion. Finally, we investigate the impact of climate change and variability by stress testing these development scenarios against historically strong El Niño/Southern Oscillation (ENSO) years and future climate projections from multiple Global Circulation Models (GCMs). The results reveal that climate variability and increased water demand are the main drivers of water scarcity in the basin. Our findings show that increases in water demand due to expanded irrigation and population growth exert the strongest influence on the ability of the system to meet water resource supply requirements, and in all cases considered increase the impacts of droughts caused by future climate variability. Our analysis illustrates the importance of combining analysis of future climate risks with other development decisions that affect water resources planning. Policy and investment decisions which maximise water use efficiency in the present day are likely to impart resilience to climate change and variability under a wide range of future scenarios and therefore constitute low regret measures for climate adaptation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA.....5938M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA.....5938M"><span>Indian-Southern Ocean Latitudinal Transect (ISOLAT): A proposal for the recovery of high-resolution sedimentary records in the western Indian Ocean sector of the Southern Ocean</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mackensen, A.; Zahn, R.; Hall, I.; Kuhn, G.; Koc, N.; Francois, R.; Hemming, S.; Goldstein, S.; Rogers, J.; Ehrmann, W.</p> <p>2003-04-01</p> <p>Quantifying oceanic variability at timescales of oceanic, atmospheric, and cryospheric processes are the fundamental objectives of the international IMAGES program. In this context the Southern Ocean plays a leading role in that it is involved, through its influence on global ocean circulation and carbon budget, with the development and maintenance of the Earth's climate system. The seas surrounding Antarctica contain the world's only zonal circum-global current system that entrains water masses from the three main ocean basins, and maintains the thermal isolation of Antarctica from warmer surface waters to the north. Furthermore, the Southern Ocean is a major site of bottom and intermediate water formation and thus actively impacts the global thermohaline circulation (THC). This proposal is an outcome of the IMAGES Southern Ocean Working Group and constitutes one component of a suite of new IMAGES/IODP initiatives that aim at resolving past variability of the Antarctic Circumpolar Current (ACC) on orbital and sub-orbital timescales and its involvement with rapid global ocean variability and climate instability. The primary aim of this proposal is to determine millennial- to sub-centennial scale variability of the ACC and the ensuing Atlantic-Indian water transports, including surface transports and deep-water flow. We will focus on periods of rapid ocean and climate change and assess the role of the Southern Ocean in these changes, both in terms of its thermohaline circulation and biogeochemical inventories. We propose a suite of 11 sites that form a latitudinal transect across the ACC in the westernmost Indian Ocean sector of the Southern Ocean. The transect is designed to allow the reconstruction of ACC variability across a range of latitudes in conjunction with meridional shifts of the surface ocean fronts. The northernmost reaches of the transect extend into the Agulhas Current and its retroflection system which is a key component of the THC warm water return flow to the Atlantic. The principal topics are: (i) the response of the ACC to climate variability; (ii) the history of the Southern Ocean surface ocean fronts during periods of rapid climate change; (iii) the history of North Atlantic Deep Water (NADW) export to the deep South Indian Ocean; (iv) the variability of Southern Ocean biogeochemical fluxes and their influence on Circumpolar Deep Water (CDW) carbon inventories and atmospheric chemistry; and (v) the variability of surface ocean fronts and the Indian-Atlantic surface ocean density flux. To achieve these objectives we will generate fine-scale records of palaeoceanographic proxies that are linked to a variety of climatically relevant ocean parameters. Temporal resolution of the records, depending on sedimentation rates, will range from millennial to sub-centennial time scales. Highest sedimentation rates are expected at coring sites located on current-controlled sediment drifts, whereas dense sampling of cores with moderate sedimentation rates will enable at least millennial-scale events to be resolved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.A41E0074B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.A41E0074B"><span>Understanding observed and simulated historical temperature trends in California</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bonfils, C. J.; Duffy, P. B.; Santer, B. D.; Lobell, D. B.; Wigley, T. M.</p> <p>2006-12-01</p> <p>In our study, we attempt 1) to improve our understanding of observed historical temperature trends and their underlying causes in the context of regional detection of climate change and 2) to identify possible neglected forcings and errors in the model response to imposed forcings at the origin of inconsistencies between models and observations. From eight different observational datasets, we estimate California-average temperature trends over 1950- 1999 and compare them to trends from a suite of IPCC control simulations of natural internal climate variability. We find that the substantial night-time warming occurring from January to September is inconsistent with model-based estimates of natural internal climate variability, and thus requires one or more external forcing agents to be explained. In contrast, we find that a significant day-time warming occurs only from January to March. Our confidence in these findings is increased because there is no evidence that the models systematically underestimate noise on interannual and decadal timescales. However, we also find that IPCC simulations of the 20th century that include combined anthropogenic and natural forcings are not able to reproduce such a pronounced seasonality of the trends. Our first hypothesis is that the warming of Californian winters over the second half of the twentieth century is associated with changes in large-scale atmospheric circulation that are likely to be human-induced. This circulation change is underestimated in the historical simulations, which may explain why the simulated warming of Californian winters is too weak. We also hypothesize that the lack of a detectable observed increase in summertime maximum temperature arises from a cooling associated with large-scale irrigation. This cooling may have, until now, counteracted the warming induced by increasing greenhouse gases and urbanization effects. Omitting to include this forcing in the simulations can result in overestimating the summertime maximum temperature trends. We conduct an empirical study based on observed climate and irrigation changes to evaluate this assumption.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPP13C1086T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPP13C1086T"><span>Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Trachsel, M.; Rehfeld, K.; Telford, R.; Laepple, T.</p> <p>2017-12-01</p> <p>Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2935129','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2935129"><span>Food security and marine capture fisheries: characteristics, trends, drivers and future perspectives</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Garcia, Serge M.; Rosenberg, Andrew A.</p> <p>2010-01-01</p> <p>World population is expected to grow from the present 6.8 billion people to about 9 billion by 2050. The growing need for nutritious and healthy food will increase the demand for fisheries products from marine sources, whose productivity is already highly stressed by excessive fishing pressure, growing organic pollution, toxic contamination, coastal degradation and climate change. Looking towards 2050, the question is how fisheries governance, and the national and international policy and legal frameworks within which it is nested, will ensure a sustainable harvest, maintain biodiversity and ecosystem functions, and adapt to climate change. This paper looks at global fisheries production, the state of resources, contribution to food security and governance. It describes the main changes affecting the sector, including geographical expansion, fishing capacity-building, natural variability, environmental degradation and climate change. It identifies drivers and future challenges, while suggesting how new science, policies and interventions could best address those challenges. PMID:20713390</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMPP43B1818N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMPP43B1818N"><span>Coral Records of 20th Century Central Tropical Pacific SST and Salinity: Signatures of Natural and Anthropogenic Climate Change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nurhati, I. S.; Cobb, K.; Di Lorenzo, E.</p> <p>2011-12-01</p> <p>Accurate forecasts of regional climate changes in many regions of the world largely depend on quantifying anthropogenic trends in tropical Pacific climate against its rich background of interannual to decadal-scale climate variability. However, the strong natural climate variability combined with limited instrumental climate datasets have obscured potential anthropogenic climate signals in the region. Here, we present coral-based sea-surface temperature (SST) and salinity proxy records over the 20th century (1898-1998) from the central tropical Pacific - a region sensitive to El Niño-Southern Oscillation (ENSO) whose variability strongly impacts the global climate. The SST and salinity proxy records are reconstructed via coral Sr/Ca and the oxygen isotopic composition of seawater (δ18Osw), respectively. On interannual (2-7yr) timescales, the SST proxy record tracks both eastern- and central-Pacific flavors of ENSO variability (R=0.65 and R=0.67, respectively). Interannual-scale salinity variability in our coral record highlights profound differences in precipitation and ocean advections during the two flavors of ENSO. On decadal (8yr-lowpassed) timescales, the central tropical Pacific SST and salinity proxy records are controlled by different sets of dynamics linked to the leading climate modes of North Pacific climate variability. Decadal-scale central tropical Pacific SST is highly correlated to the recently discovered North Pacific Gyre Oscillation (NPGO; R=-0.85), reflecting strong dynamical links between the central Pacific warming mode and extratropical decadal climate variability. Whereas decadal-scale salinity variations in the central tropical Pacific are significantly correlated with the Pacific Decadal Oscillation (PDO; R=0.54), providing a better understanding on low-frequency salinity variability in the region. Having characterized natural climate variability in this region, the coral record shows a +0.5°C warming trend throughout the last century. However, the most prominent feature of the new coral records is an unprecedented freshening trend since the mid-20th century, in line with global climate models (GCMs) projections of enhanced hydrological patterns (wet areas are getting wetter and vice versa) under greenhouse forcing. Taken together, the coral records provide key constraints on tropical Pacific climate trends that may improve regional climate projections in areas affected by tropical Pacific climate variability.<br />Central Tropical Pacific SST and Salinity Proxy Records<img class="jpg" border=0 width=600px src="/meetings/fm11/program/tables/PP43B-1818_T1.jpg"></p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B11D0502H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B11D0502H"><span>Analyzing the responses of species assemblages to climate change across the Great Basin, USA.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Henareh Khalyani, A.; Falkowski, M. J.; Crookston, N.; Yousef, F.</p> <p>2016-12-01</p> <p>The potential impacts of climate change on the future distribution of tree species in not well understood. Climate driven changes in tree species distribution could cause significant changes in realized species niches, potentially resulting in the loss of ecotonal species as well as the formation on novel assemblages of overlapping tree species. In an effort to gain a better understating of how the geographic distribution of tree species may respond to climate change, we model the potential future distribution of 50 different tree species across 70 million ha in the Great Basin, USA. This is achieved by leveraging a species realized niche model based on non-parametric analysis of species occurrences across climatic, topographic, and edaphic variables. Spatially explicit, high spatial resolution (30 m) climate variables (e.g., precipitation, and minimum, maximum, and mean temperature) and associated climate indices were generated on an annual basis between 1981-2010 by integrating climate station data with digital elevation data (Shuttle Radar Topographic Mission (SRTM) data) in a thin plate spline interpolation algorithm (ANUSPLIN). Bioclimate models of species niches in in the cotemporary period and three following 30 year periods were then generated by integrating the climate variables, soil data, and CMIP 5 general circulation model projections. Our results suggest that local scale contemporary variations in species realized niches across space are influenced by edaphic and topographic variables as well as climatic variables. The local variability in soil properties and topographic variability across space also affect the species responses to climate change through time and potential formation of species assemblages in future. The results presented here in will aid in the development of adaptive forest management techniques aimed at mitigating negative impacts of climate change on forest composition, structure, and function.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP23A2314L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP23A2314L"><span>Leaf wax biomarker reconstruction of Early Pleistocene hydrological variation during hominin evolution in West Turkana, Kenya</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lupien, R.; Russell, J. M.; Cohen, A. S.; Feibel, C. S.; Beck, C.; Castañeda, I. S.</p> <p>2016-12-01</p> <p>Climate change is thought to play a critical role in human evolution; however, this hypothesis is difficult to test due to a lack of long, high-quality paleoclimate records from key hominin fossil locales. To address this issue, we examine Plio-Pleistocene lake sediment drill cores from East Africa that were recovered by the Hominin Sites and Paleolakes Drilling Project, an international effort to study the environment in which our hominin ancestors evolved and dispersed. With new data we test various evolutionary hypotheses, such as the "variability selection" hypothesis, which posits that high-frequency environmental variations selected for generalist traits that allowed hominins to expand into variable environments. We analyzed organic geochemical signals of climate in lake cores from West Turkana, Kenya, which span 1.87-1.38 Ma and contain the first fossils from Homo erectus. In particular, we present a compound-specific hydrogen isotopic analysis of terrestrial plant waxes (δDwax) that records regional hydrology. The amount effect dominates water isotope fractionation in the tropics; therefore, these data are interpreted to reflect mean annual rainfall, which affects vegetation structure and thus, hominin habitats. The canonical view of East Africa is that climate became drier and increasingly felt high-latitude glacial-interglacial cycles during the Plio-Pleistocene. However, the drying trend seen in some records is not evident in Turkana δDwax, signifying instead a climate with a steady mean state. Spectral and moving variance analyses indicate paleohydrological variations related to both high-latitude glaciation (41 ky cycle) and local insolation-forced monsoons (21 ky cycle). An interval of particularly high-amplitude rainfall variation occurs at 1.7 Ma, which coincides with the intensification of the Walker Circulation. These results identify high- and low-latitude controls on East African paleohydrology during Homo erectus evolution. In particular, the interval of high-amplitude variability coincides with hominin evolution changes and lends support for the "variability selection" hypothesis. Similar analyses of a drill core from Northern Awash, Ethiopia ( 3.3-2.9 Ma) will be presented to compare Pliocene and Pleistocene climate variations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012CliPa...8.1997Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012CliPa...8.1997Z"><span>An ocean-ice coupled response during the last glacial: a view from a marine isotopic stage 3 record south of the Faeroe Shetland Gateway</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zumaque, J.; Eynaud, F.; Zaragosi, S.; Marret, F.; Matsuzaki, K. M.; Kissel, C.; Roche, D. M.; Malaizé, B.; Michel, E.; Billy, I.; Richter, T.; Palis, E.</p> <p>2012-12-01</p> <p>The rapid climatic variability characterising the Marine Isotopic Stage (MIS) 3 (~60-30 cal ka BP) provides key issues to understand the atmosphere-ocean-cryosphere dynamics. Here we investigate the response of sea-surface paleoenvironments to the MIS3 climatic variability through the study of a high resolution oceanic sedimentological archive (core MD99-2281, 60°21' N; 09°27' W; 1197 m water depth), retrieved during the MD114-IMAGES (International Marine Global Change Study) cruise from the southern part of the Faeroe Bank. This sector was under the proximal influence of European ice sheets (Fennoscandian Ice Sheet to the East, British Irish Ice Sheet to the South) during the last glacial and thus probably responded to the MIS3 pulsed climatic changes. We conducted a multi-proxy analysis of core MD99-2281, including magnetic properties, x-ray fluorescence measurements, characterisation of the coarse (>150 μm) lithic fraction (grain concentration) and the analysis of selected biogenic proxies (assemblages and stable isotope ratio of calcareous planktonic foraminifera, dinoflagellate cyst - e.g. dinocyst - assemblages). Results presented here are focussed on the dinocyst response, this proxy providing the reconstruction of past sea-surface hydrological conditions, qualitatively as well as quantitatively (e.g. transfer function sensu lato). Our study documents a very coherent and sensitive oceanic response to the MIS3 rapid climatic variability: strong fluctuations, matching those of stadial/interstadial climatic oscillations as depicted by Greenland ice cores, are recorded in the MD99-2281 archive. Proxies of terrigeneous and detritical material suggest increases in continental advection during Greenland Stadials (including Heinrich events), the latter corresponding also to southward migrations of polar waters. At the opposite, milder sea-surface conditions seem to develop during Greenland Interstadials. After 30 ka, reconstructed paleohydrological conditions evidence strong shifts in SST: this increasing variability seems consistent with the hypothesised coalescence of the British and Fennoscandian ice sheets at that time, which could have directly influenced sea-surface environments in the vicinity of core MD99-2281.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012CliPD...8.3043Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012CliPD...8.3043Z"><span>An Ocean - ice coupled response during the last glacial: zooming on the marine isotopic stage 3 south of the Faeroe Shetland Gateway</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zumaque, J.; Eynaud, F.; Zaragosi, S.; Marret, F.; Matsuzaki, K. M.; Kissel, C.; Roche, D. M.; Malaizé, B.; Michel, E.; Billy, I.; Richter, T.; Palis, E.</p> <p>2012-08-01</p> <p>The rapid climatic variability characterising the Marine Isotopic Stage (MIS) 3 (~ 60-30 CAL-ka BP) provides key issues to understand the atmosphere-ocean-cryosphere dynamics. Here we investigate the response of sea-surface paleoenvironments to the MIS3 climatic variability through the study of a high resolution oceanic sedimentological archive (core MD99-2281, 60°21' N; 09°27' W; 1197 m water depth), retrieved during the MD114-IMAGES (International Marine Global Change Study) cruise from the Southern part of the Faeroe Bank. This sector was under the proximal influence of European Ice Sheets (Fennoscandian Ice Sheet to the East, British Irish Ice Sheet to the South) and thus probably recorded their response to the MIS3 pulsed climatic changes. We conducted a multi-proxy analysis on core MD99-2281, including magnetic properties, X-Ray Fluorescence measurements, characterisation of the coarse (> 150 μm) lithic fraction (grain concentration) and the analysis of selected biogenic proxies (assemblages and stable isotope ratio of calcareous planktonic foraminifera, dinoflagellate cyst - e.g. dinocyst - assemblages). Results presented here are focussed on the dinocyst response, this proxy providing the reconstruction of past sea-surface hydrological conditions, qualitatively as well as quantitatively (e.g. transfer function sensu lato). Our study documents a very coherent and sensitive oceanic response to the MIS3 rapid climatic variability: strong fluctuations, matching those of stadial/interstadial climatic oscillations as depicted by Greenland Ice Cores, are recorded in the MD99-2281 archive. Proxies of terrigeneous and detritical material typify increases in continental advection during Greenland Stadials (including Heinrich events), the latter corresponding also to southward migrations of polar waters. At the opposite, milder sea-surface conditions seem to develop during Greenland Interstadials. After 30 ka, reconstructed paleohydrological conditions evidence strong shifts in SST: this increasing variability seems consistent with the hypothesised coalescence of the British and Fennoscandian ice sheets at that time, which could have directly influenced sea-surface environments in the vicinity of core MD99-2281.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1550767','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1550767"><span>Climate variability has a stabilizing effect on the coexistence of prairie grasses</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Adler, Peter B.; HilleRisLambers, Janneke; Kyriakidis, Phaedon C.; Guan, Qingfeng; Levine, Jonathan M.</p> <p>2006-01-01</p> <p>How expected increases in climate variability will affect species diversity depends on the role of such variability in regulating the coexistence of competing species. Despite theory linking temporal environmental fluctuations with the maintenance of diversity, the importance of climate variability for stabilizing coexistence remains unknown because of a lack of appropriate long-term observations. Here, we analyze three decades of demographic data from a Kansas prairie to demonstrate that interannual climate variability promotes the coexistence of three common grass species. Specifically, we show that (i) the dynamics of the three species satisfy all requirements of “storage effect” theory based on recruitment variability with overlapping generations, (ii) climate variables are correlated with interannual variation in species performance, and (iii) temporal variability increases low-density growth rates, buffering these species against competitive exclusion. Given that environmental fluctuations are ubiquitous in natural systems, our results suggest that coexistence based on the storage effect may be underappreciated and could provide an important alternative to recent neutral theories of diversity. Field evidence for positive effects of variability on coexistence also emphasizes the need to consider changes in both climate means and variances when forecasting the effects of global change on species diversity. PMID:16908862</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1911236M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1911236M"><span>Drought Persistence in Models and Observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moon, Heewon; Gudmundsson, Lukas; Seneviratne, Sonia</p> <p>2017-04-01</p> <p>Many regions of the world have experienced drought events that persisted several years and caused substantial economic and ecological impacts in the 20th century. However, it remains unclear whether there are significant trends in the frequency or severity of these prolonged drought events. In particular, an important issue is linked to systematic biases in the representation of persistent drought events in climate models, which impedes analysis related to the detection and attribution of drought trends. This study assesses drought persistence errors in global climate model (GCM) simulations from the 5th phase of Coupled Model Intercomparison Project (CMIP5), in the period of 1901-2010. The model simulations are compared with five gridded observational data products. The analysis focuses on two aspects: the identification of systematic biases in the models and the partitioning of the spread of drought-persistence-error into four possible sources of uncertainty: model uncertainty, observation uncertainty, internal climate variability and the estimation error of drought persistence. We use monthly and yearly dry-to-dry transition probabilities as estimates for drought persistence with drought conditions defined as negative precipitation anomalies. For both time scales we find that most model simulations consistently underestimated drought persistence except in a few regions such as India and Eastern South America. Partitioning the spread of the drought-persistence-error shows that at the monthly time scale model uncertainty and observation uncertainty are dominant, while the contribution from internal variability does play a minor role in most cases. At the yearly scale, the spread of the drought-persistence-error is dominated by the estimation error, indicating that the partitioning is not statistically significant, due to a limited number of considered time steps. These findings reveal systematic errors in the representation of drought persistence in current climate models and highlight the main contributors of uncertainty of drought-persistence-error. Future analyses will focus on investigating the temporal propagation of drought persistence to better understand the causes for the identified errors in the representation of drought persistence in state-of-the-art climate models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5608457','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5608457"><span>International Climate Migration: Evidence for the Climate Inhibitor Mechanism and the Agricultural Pathway</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Nawrotzki, Raphael J.; Bakhtsiyarava, Maryia</p> <p>2016-01-01</p> <p>Research often assumes that, in rural areas of developing countries, adverse climatic conditions increase (climate driver mechanism) rather than reduce (climate inhibitor mechanism) migration, and that the impact of climate on migration is moderated by changes in agricultural productivity (agricultural pathway). Using representative census data in combination with high-resolution climate data derived from the novel Terra Populus system, we explore the climate-migration relationship in rural Burkina Faso and Senegal. We construct four threshold-based climate measures to investigate the effect of heat waves, cold snaps, droughts and excessive precipitation on the likelihood of household-level international outmigration. Results from multi-level logit models show that excessive precipitation increases international migration from Senegal while heat waves decrease international mobility in Burkina Faso, providing evidence for the climate inhibitor mechanism. Consistent with the agricultural pathway, interaction models and results from a geographically weighted regression (GWR) reveal a conditional effect of droughts on international outmigration from Senegal, which becomes stronger in areas with high levels of groundnut production. Moreover, climate change effects show a clear seasonal pattern, with the strongest effects appearing when heat waves overlap with the growing season and when excessive precipitation occurs prior to the growing season. PMID:28943813</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28943813','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28943813"><span>International Climate Migration: Evidence for the Climate Inhibitor Mechanism and the Agricultural Pathway.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Nawrotzki, Raphael J; Bakhtsiyarava, Maryia</p> <p>2017-05-01</p> <p>Research often assumes that, in rural areas of developing countries, adverse climatic conditions increase (climate driver mechanism) rather than reduce (climate inhibitor mechanism) migration, and that the impact of climate on migration is moderated by changes in agricultural productivity (agricultural pathway). Using representative census data in combination with high-resolution climate data derived from the novel Terra Populus system, we explore the climate-migration relationship in rural Burkina Faso and Senegal. We construct four threshold-based climate measures to investigate the effect of heat waves, cold snaps, droughts and excessive precipitation on the likelihood of household-level international outmigration. Results from multi-level logit models show that excessive precipitation increases international migration from Senegal while heat waves decrease international mobility in Burkina Faso, providing evidence for the climate inhibitor mechanism. Consistent with the agricultural pathway, interaction models and results from a geographically weighted regression (GWR) reveal a conditional effect of droughts on international outmigration from Senegal, which becomes stronger in areas with high levels of groundnut production. Moreover, climate change effects show a clear seasonal pattern, with the strongest effects appearing when heat waves overlap with the growing season and when excessive precipitation occurs prior to the growing season.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1918026M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1918026M"><span>Hydrological response of karst systems to large-scale climate variability for different catchments of the French karst observatory network INSU/CNRS SNO KARST</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Massei, Nicolas; Labat, David; Jourde, Hervé; Lecoq, Nicolas; Mazzilli, Naomi</p> <p>2017-04-01</p> <p>The french karst observatory network SNO KARST is a national initiative from the National Institute for Earth Sciences and Astronomy (INSU) of the National Center for Scientific Research (CNRS). It is also part of the new french research infrastructure for the observation of the critical zone OZCAR. SNO KARST is composed by several karst sites distributed over conterminous France which are located in different physiographic and climatic contexts (Mediterranean, Pyrenean, Jura mountain, western and northwestern shore near the Atlantic or the English Channel). This allows the scientific community to develop advanced research and experiments dedicated to improve understanding of the hydrological functioning of karst catchments. Here we used several sites of SNO KARST in order to assess the hydrological response of karst catchments to long-term variation of large-scale atmospheric circulation. Using NCEP reanalysis products and karst discharge, we analyzed the links between large-scale circulation and karst water resources variability. As karst hydrosystems are highly heterogeneous media, they behave differently across different time-scales : we explore the large-scale/local-scale relationships according to time-scales using a wavelet multiresolution approach of both karst hydrological variables and large-scale climate fields such as sea level pressure (SLP). The different wavelet components of karst discharge in response to the corresponding wavelet component of climate fields are either 1) compared to physico-chemical/geochemical responses at karst springs, or 2) interpreted in terms of hydrological functioning by comparing discharge wavelet components to internal components obtained from precipitation/discharge models using the KARSTMOD conceptual modeling platform of SNO KARST.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170002480','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170002480"><span>Global Meteorological Drought: A Synthesis of Current Understanding with a Focus on SST Drivers of Precipitation Deficits</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Schubert, S.; Stewart, R.; Wang, H.; Barlow, M.; Berbery, H.; Cai, W.; Hoerling, M.; Kanikicharla, K.; Koster, R.; Lyon, B.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170002480'); toggleEditAbsImage('author_20170002480_show'); toggleEditAbsImage('author_20170002480_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170002480_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170002480_hide"></p> <p>2016-01-01</p> <p>Drought affects virtually every region of the world, and potential shifts in its character in a changing climate are a major concern. This article presents a synthesis of current understanding of meteorological drought, with a focus on the large-scale controls on precipitation afforded by sea surface temperature (SST anomalies), land surface feedbacks, and radiative forcings. The synthesis is primarily based on regionally-focused articles submitted to the Global Drought Information System (GDIS) collection together with new results from a suite of atmospheric general circulation model experiments intended to integrate those studies into a coherent view of drought worldwide. On interannual time scales, the preeminence of ENSO as a driver of meteorological drought throughout much of the Americas, eastern Asia, Australia, and the Maritime Continent is now well established, whereas in other regions (e.g., Europe, Africa, and India), the response to ENSO is more ephemeral or nonexistent. Northern Eurasia, central Europe, as well as central and eastern Canada stand out as regions with little SST-forced impacts on precipitation interannual time scales. Decadal changes in SST appear to be a major factor in the occurrence of long-term drought, as highlighted by apparent impacts on precipitation of the late 1990s 'climate shifts' in the Pacific and Atlantic SST. Key remaining research challenges include (i) better quantification of unforced and forced atmospheric variability as well as land/atmosphere feedbacks, (ii) better understanding of the physical basis for the leading modes of climate variability and their predictability, and (iii) quantification of the relative contributions of internal decadal SST variability and forced climate change to long-term drought.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990041333','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990041333"><span>Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.</p> <p>1997-01-01</p> <p>The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1379728','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1379728"><span>Half a degree additional warming, prognosis and projected impacts (HAPPI): background and experimental design</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Mitchell, Daniel; AchutaRao, Krishna; Allen, Myles</p> <p></p> <p>The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and on related global greenhouse-gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the half a degree additional warming, projections, prognosis and impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the presentmore » day in worlds that are 1.5 and 2.0 °C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of impact models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments under low-emission scenarios.Large ensembles of simulations (> 50 members) of atmosphere-only models for three time slices are proposed, each a decade in length: the first being the most recent observed 10-year period (2006–2015), the second two being estimates of a similar decade but under 1.5 and 2 °C conditions a century in the future. We use the representative concentration pathway 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5 °C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2 °C scenario.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1379728-half-degree-additional-warming-prognosis-projected-impacts-happi-background-experimental-design','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1379728-half-degree-additional-warming-prognosis-projected-impacts-happi-background-experimental-design"><span>Half a degree additional warming, prognosis and projected impacts (HAPPI): background and experimental design</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Mitchell, Daniel; AchutaRao, Krishna; Allen, Myles; ...</p> <p>2017-02-08</p> <p>The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and on related global greenhouse-gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the half a degree additional warming, projections, prognosis and impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the presentmore » day in worlds that are 1.5 and 2.0 °C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of impact models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments under low-emission scenarios.Large ensembles of simulations (> 50 members) of atmosphere-only models for three time slices are proposed, each a decade in length: the first being the most recent observed 10-year period (2006–2015), the second two being estimates of a similar decade but under 1.5 and 2 °C conditions a century in the future. We use the representative concentration pathway 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5 °C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2 °C scenario.« less</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_22 --> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/24572','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/24572"><span>Spatial variability in forest growth—climate relationships in the Olympic Mountains, Washington.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Jill M. Nakawatase; David L. Peterson</p> <p>2006-01-01</p> <p>For many Pacific Northwest forests, little is known about the spatial and temporal variability in tree growth - climate relationships, yet it is this information that is needed to predict how forests will respond to future climatic change. We studied the effects of climatic variability on forest growth at 74 plots in the western and northeastern Olympic Mountains....</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1275738-frontiers-decadal-climate-variability-proceedings-workshop','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1275738-frontiers-decadal-climate-variability-proceedings-workshop"><span>Frontiers in Decadal Climate Variability: Proceedings of a Workshop</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Purcell, Amanda</p> <p></p> <p>A number of studies indicate an apparent slowdown in the overall rise in global average surface temperature between roughly 1998 and 2014. Most models did not predict such a slowdown--a fact that stimulated a lot of new research on variability of Earth's climate system. At a September 2015 workshop, leading scientists gathered to discuss current understanding of climate variability on decadal timescales (10 to 30 years) and whether and how prediction of it might be improved. Many researchers have focused their attention on the climate system itself, which is known to vary across seasons, decades, and other timescales. Several naturalmore » variables produce "ups and downs" in the climate system, which are superimposed on the long-term warming trend due to human influence. Understanding decadal climate variability is important not only for assessing global climate change but also for improving decision making related to infrastructure, water resources, agriculture, energy, and other realms. Like the well-studied El Nino and La Nina interannual variations, decadal climate variability is associated with specific regional patterns of temperature and precipitation, such as heat waves, cold spells, and droughts. Several participants shared research that assesses decadal predictive capability of current models.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28319296','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28319296"><span>Joint effects of climate variability and socioecological factors on dengue transmission: epidemiological evidence.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Akter, Rokeya; Hu, Wenbiao; Naish, Suchithra; Banu, Shahera; Tong, Shilu</p> <p>2017-06-01</p> <p>To assess the epidemiological evidence on the joint effects of climate variability and socioecological factors on dengue transmission. Following PRISMA guidelines, a detailed literature search was conducted in PubMed, Web of Science and Scopus. Peer-reviewed, freely available and full-text articles, considering both climate and socioecological factors in relation to dengue, published in English from January 1993 to October 2015 were included in this review. Twenty studies have met the inclusion criteria and assessed the impact of both climatic and socioecological factors on dengue dynamics. Among those, four studies have further investigated the relative importance of climate variability and socioecological factors on dengue transmission. A few studies also developed predictive models including both climatic and socioecological factors. Due to insufficient data, methodological issues and contextual variability of the studies, it is hard to draw conclusion on the joint effects of climate variability and socioecological factors on dengue transmission. Future research should take into account socioecological factors in combination with climate variables for a better understanding of the complex nature of dengue transmission as well as for improving the predictive capability of dengue forecasting models, to develop effective and reliable early warning systems. © 2017 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC41F..02C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC41F..02C"><span>Continuing the Total and Spectral Solar Irradiance Climate Data Record</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Coddington, O.; Pilewskie, P.; Kopp, G.; Richard, E. C.; Sparn, T.; Woods, T. N.</p> <p>2017-12-01</p> <p>Radiative energy from the Sun establishes the basic climate of the Earth's surface and atmosphere and defines the terrestrial environment that supports all life on the planet. External solar variability on a wide range of scales ubiquitously affects the Earth system, and combines with internal forcings, including anthropogenic changes in greenhouse gases and aerosols, and natural modes such as ENSO, and volcanic forcing, to define past, present, and future climates. Understanding these effects requires continuous measurements of total and spectrally resolved solar irradiance that meet the stringent requirements of climate-quality accuracy and stability over time. The current uninterrupted 39-year total solar irradiance (TSI) climate data record is the result of several overlapping instruments flown on different missions. Measurement continuity, required to link successive instruments to the existing data record to discern long-term trends makes this important climate data record susceptible to loss in the event of a gap in measurements. While improvements in future instrument accuracy will reduce the risk of a gap, the 2017 launch of TSIS-1 ensures continuity of the solar irradiance record into the next decade. There are scientific and programmatic motivations for addressing the challenges of maintaining the solar irradiance data record beyond TSIS-1. The science rests on well-founded requirements of establishing a trusted climate observing network that can monitor trends in fundamental climate variables. Programmatically, the long-term monitoring of solar irradiance must be balanced within the broader goals of NASA Earth Science. New concepts for a low-risk, cost efficient observing strategy is a priority. New highly capable small spacecraft, low-cost launch vehicles and a multi-decadal plan to provide overlapping TSI and SSI data records are components of a low risk/high reliability plan with lower annual cost than past implementations. This paper provides the justification for prioritizing solar irradiance observations and plans for extending the record into the next two decades that adheres to the rigors of quantifiable methods for meeting objectives.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002SPIE.4678..685K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002SPIE.4678..685K"><span>Modern nature and climate changes in Siberia: new methods and results of analysis of instrumented observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kabanov, Mikhail V.</p> <p>2002-02-01</p> <p>Peculiarity of nature and climate changes in middle latitudes of the Northern Hemisphere and in Siberia is that the temporal variability of meteorological quantities here has a wide range and their spatial variability has a complicated zone structure. Therefore, regional monitoring of modern nature and climate changes in Siberia is of scientific interest from the viewpoint of the global changes observed. Another Siberian peculiarity is associated with the fact that there are many unique objects that have global importance both as natural complexes (boreal forests, water- bog systems, Baikal lake, etc.) And as technogenic objects (oil and gas production, coal mining, metallurgy, transport, etc.). Therefore monitoring and modeling of regional nature and climate changes in Siberia have great practical importance, which is underestimated now, for industrial development of Siberia. Taking into account the above peculiarities and tendencies on investigation of global and regional environmental and climate changes, the multidisciplinary project on Climate and Ecological Monitoring of Siberia (CEMS) was accepted to the research and development program Sibir' since 1993. To realize this project, the Climate and Ecological Observatory was established in Tomsk at the Institute for Optical Monitoring (IOM) SB RAS. At the present time the stations (the basic and background ones) of this observatory are in a progress and theory and instruments for monitoring are being developed as well. In this paper we discuss some results obtained in the framework of CEMS project that were partially published in the monographs, in scientific journals, and will be published in the Proceedings of the 8th Joint International Symposium on Atmospheric and Ocean Optics and Atmosphere Physics. This review has a purpose not only to discuss the obtained regularities but also to formulate scientific and technical tasks for further investigations into the regional changes of technogenic, natural, and climate systems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.H13G1391S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.H13G1391S"><span>Impacts of Considering Climate Variability on Investment Decisions in Ethiopia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Strzepek, K.; Block, P.; Rosegrant, M.; Diao, X.</p> <p>2005-12-01</p> <p>In Ethiopia, climate extremes, inducing droughts or floods, are not unusual. Monitoring the effects of these extremes, and climate variability in general, is critical for economic prediction and assessment of the country's future welfare. The focus of this study involves adding climate variability to a deterministic, mean climate-driven agro-economic model, in an attempt to understand its effects and degree of influence on general economic prediction indicators for Ethiopia. Four simulations are examined, including a baseline simulation and three investment strategies: simulations of irrigation investment, roads investment, and a combination investment of both irrigation and roads. The deterministic model is transformed into a stochastic model by dynamically adding year-to-year climate variability through climate-yield factors. Nine sets of actual, historic, variable climate data are individually assembled and implemented into the 12-year stochastic model simulation, producing an ensemble of economic prediction indicators. This ensemble allows for a probabilistic approach to planning and policy making, allowing decision makers to consider risk. The economic indicators from the deterministic and stochastic approaches, including rates of return to investments, are significantly different. The predictions of the deterministic model appreciably overestimate the future welfare of Ethiopia; the predictions of the stochastic model, utilizing actual climate data, tend to give a better semblance of what may be expected. Inclusion of climate variability is vital for proper analysis of the predictor values from this agro-economic model.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.H13B1398S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.H13B1398S"><span>Post-Fire Recovery of Eco-Hydrologic Behavior Given Historic and Projected Climate Variability in California Mediterranean Type Environments</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Seaby, L. P.; Tague, C. L.; Hope, A. S.</p> <p>2006-12-01</p> <p>The Mediterranean type environments (MTEs) of California are characterized by a distinct wet and dry season and high variability in inter-annual climate. Water limitation in MTEs makes eco-hydrological processes highly sensitive to both climate variability and frequent fire disturbance. This research modeled post-fire eco- hydrologic behavior under historical and moderate and extreme scenarios of future climate in a semi-arid chaparral dominated southern California MTE. We used a physically-based, spatially-distributed, eco- hydrological model (RHESSys - Regional Hydro-Ecologic Simulation System), to capture linkages between water and vegetation response to the combined effects of fire and historic and future climate variability. We found post-fire eco-hydrologic behavior to be strongly influenced by the episodic nature of MTE climate, which intensifies under projected climate change. Higher rates of post-fire net primary productivity were found under moderate climate change, while more extreme climate change produced water stressed conditions which were less favorable for vegetation productivity. Precipitation variability in the historic record follows the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), and these inter-annual climate characteristics intensify under climate change. Inter-annual variation in streamflow follows these precipitation patterns. Post-fire streamflow and carbon cycling trajectories are strongly dependent on climate characteristics during the first 5 years following fire, and historic intra-climate variability during this period tends to overwhelm longer term trends and variation that might be attributable to climate change. Results have implications for water resource availability, vegetation type conversion from shrubs to grassland, and changes in ecosystem structure and function.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016QuRes..86....1W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016QuRes..86....1W"><span>Direct versus indirect climate controls on Holocene diatom assemblages in a sub-tropical deep, alpine lake (Lugu Hu, Yunnan, SW China)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Qian; Yang, Xiangdong; Anderson, Nicholas John; Dong, Xuhui</p> <p>2016-07-01</p> <p>The reconstruction of Holocene environmental changes in lakes on the plateau region of southwest China provides an understanding of how these ecosystems may respond to climate change. Fossil diatom assemblages were investigated from an 11,000-year lake sediment core from a deep, alpine lake (Lugu Hu) in southwest China, an area strongly influenced by the southwest (or the Indian) summer monsoon. Changes in diatom assemblage composition, notably the abundance of the two dominant planktonic species, Cyclotella rhomboideo-elliptica and Cyclostephanos dubius, reflect the effects of climate variability on nutrient dynamics, mediated via thermal stratification (internal nutrient cycling) and catchment-vegetation processes. Statistical analyses of the climate-diatom interactions highlight the strong effect of changing orbitally-induced solar radiation during the Holocene, presumably via its effect on the lake's thermal budget. In a partial redundancy analysis, climate (solar insolation) and proxies reflecting catchment process (pollen percentages, C/N ratio) were the most important drivers of diatom ecological change, showing the strong effects of climate-catchment-vegetation interactions on lake functioning. This diatom record reflects long-term ontogeny of the lake-catchment ecosystem and suggests that climatic changes (both temperature and precipitation) impact lake ecology indirectly through shifts in thermal stratification and catchment nutrient exports.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC52B..07B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC52B..07B"><span>Detection of non-natural springtime precipitation change over northern South America</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barkhordarian, A.; Behrangi, A.; Mechoso, C. R.</p> <p>2017-12-01</p> <p>Here we determine whether the climate over South America has changed as a result of human activity since the beginning of the industrial revolution. To this end, we assess whether the observed changes are likely to have been due to natural (internal) variability alone, and if not, whether they are consistent with what models simulate as response to anthropogenic and natural forcing. Internal variability is estimated using 12,000-year control runs derived from CMIP5 archive. Results indicate that, in the past decades, trends in springtime (ASO, August-October) precipitation over South America have a magnitude that is beyond the estimated range due to natural (internal) variability or natural forcings alone. Evidence for the presence of an external driving factor is clearly detectable in the observed precipitation record (with less than 5% risk of error). The regression results illustrate the concerted emergence of an anthropogenic signal consistent with greenhouse gas (GHG) in observed decreasing 30-year trends of precipitation ending in 1998 and later on. In addition, the fingerprint of land-use-change signal is detectable in the observed precipitation decrease over 1983-2012. While the influence of GHG signal is detectable in precipitation, an observed decrease up to 10 mm/decade drying over the Amazon region, is much larger than the changes simulated by global and regional climate models as response to GHG forcing. We further show that the projected increasing trend of vapor pressure deficit (VPD), an indicator of background aridity, by the climate models with GHG forcing is much smaller than that observed over the Amazon rainforest. This may imply that models may underestimate the resulting reductions in forest CO2 uptake that could function as a positive feedback to rising temperature and reducing precipitation. Taking the ensemble of 23 IPCC models as a crude metric of probabilities, we further show that with 19 out of 24 models the effect of GS signal (greenhouse gas and anthropogenic aerosols) based on RCP4.5 scenario has already a detectable influence in the observed drying over Amazon region. This may imply that the observed drier air conditions plus higher surface air temperature during austral spring serve as an illustration of plausible future expected change in the region.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150004431','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150004431"><span>Climate Change Effects on Agriculture: Economic Responses to Biophysical Shocks</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlik, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina</p> <p>2014-01-01</p> <p>Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(sup 2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3948295','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3948295"><span>Climate change effects on agriculture: Economic responses to biophysical shocks</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d’Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk</p> <p>2014-01-01</p> <p>Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change. PMID:24344285</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24344285','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24344285"><span>Climate change effects on agriculture: economic responses to biophysical shocks.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Nelson, Gerald C; Valin, Hugo; Sands, Ronald D; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d'Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk</p> <p>2014-03-04</p> <p>Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26324900','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26324900"><span>Slowing down of North Pacific climate variability and its implications for abrupt ecosystem change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Boulton, Chris A; Lenton, Timothy M</p> <p>2015-09-15</p> <p>Marine ecosystems are sensitive to stochastic environmental variability, with higher-amplitude, lower-frequency--i.e., "redder"--variability posing a greater threat of triggering large ecosystem changes. Here we show that fluctuations in the Pacific Decadal Oscillation (PDO) index have slowed down markedly over the observational record (1900-present), as indicated by a robust increase in autocorrelation. This "reddening" of the spectrum of climate variability is also found in regionally averaged North Pacific sea surface temperatures (SSTs), and can be at least partly explained by observed deepening of the ocean mixed layer. The progressive reddening of North Pacific climate variability has important implications for marine ecosystems. Ecosystem variables that respond linearly to climate forcing will have become prone to much larger variations over the observational record, whereas ecosystem variables that respond nonlinearly to climate forcing will have become prone to more frequent "regime shifts." Thus, slowing down of North Pacific climate variability can help explain the large magnitude and potentially the quick succession of well-known abrupt changes in North Pacific ecosystems in 1977 and 1989. When looking ahead, despite model limitations in simulating mixed layer depth (MLD) in the North Pacific, global warming is robustly expected to decrease MLD. This could potentially reverse the observed trend of slowing down of North Pacific climate variability and its effects on marine ecosystems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26027582','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26027582"><span>Influence of climate variability on acute myocardial infarction mortality in Havana, 2001-2012.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Rivero, Alina; Bolufé, Javier; Ortiz, Paulo L; Rodríguez, Yunisleydi; Reyes, María C</p> <p>2015-04-01</p> <p>Death from acute myocardial infarction is due to many factors; influences on risk to the individual include habits, lifestyle and behavior, as well as weather, climate and other environmental components. Changing climate patterns make it especially important to understand how climatic variability may influence acute myocardial infarction mortality. Describe the relationship between climate variability and acute myocardial infarction mortality during the period 2001-2012 in Havana. An ecological time-series study was conducted. The universe comprised 23,744 deaths from acute myocardial infarction (ICD-10: I21-I22) in Havana residents from 2001 to 2012. Climate variability and seasonal anomalies were described using the Bultó-1 bioclimatic index (comprising variables of temperature, humidity, precipitation, and atmospheric pressure), along with series analysis to determine different seasonal-to-interannual climate variation signals. The role played by climate variables in acute myocardial infarction mortality was determined using factor analysis. The Mann-Kendall and Pettitt statistical tests were used for trend analysis with a significance level of 5%. The strong association between climate variability conditions described using the Bultó-1 bioclimatic index and acute myocardial infarctions accounts for the marked seasonal pattern in AMI mortality. The highest mortality rate occurred during the dry season, i.e., the winter months in Cuba (November-April), with peak numbers in January, December and March. The lowest mortality coincided with the rainy season, i.e., the summer months (May-October). A downward trend in total number of deaths can be seen starting with the change point in April 2009. Climate variability is inversely associated with an increase in acute myocardial infarction mortality as is shown by the Bultó-1 index. This inverse relationship accounts for acute myocardial infarction mortality's seasonal pattern.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPP23D..07R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPP23D..07R"><span>Central Tropical Pacific Variability And ENSO Response To Changing Climate Boundary Conditions: Evidence From Individual Line Island Foraminifera</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rustic, G. T.; Polissar, P. J.; Ravelo, A. C.; White, S. M.</p> <p>2017-12-01</p> <p>The El Niño Southern Oscillation (ENSO) plays a dominant role in Earth's climate variability. Paleoceanographic evidence suggests that ENSO has changed in the past, and these changes have been linked to large-scale climatic shifts. While a close relationship between ENSO evolution and climate boundary conditions has been predicted, testing these predictions remains challenging. These climate boundary conditions, including insolation, the mean surface temperature gradient of the tropical Pacific, global ice volume, and tropical thermocline depth, often co-vary and may work together to suppress or enhance the ocean-atmosphere feedbacks that drive ENSO variability. Furthermore, suitable paleo-archives spanning multiple climate states are sparse. We have aimed to test ENSO response to changing climate boundary conditions by generating new reconstructions of mixed-layer variability from sedimentary archives spanning the last three glacial-interglacial cycles from the Central Tropical Pacific Line Islands, where El Niño is strongly expressed. We analyzed Mg/Ca ratios from individual foraminifera to reconstruct mixed-layer variability at discrete time intervals representing combinations of climatic boundary conditions from the middle Holocene to Marine Isotope Stage (MIS) 8. We observe changes in the mixed-layer temperature variability during MIS 5 and during the previous interglacial (MIS 7) showing significant reductions in ENSO amplitude. Differences in variability during glacial and interglacial intervals are also observed. Additionally, we reconstructed mixed-layer and thermocline conditions using multi-species Mg/Ca and stable isotope measurements to more fully characterize the state of the Central Tropical Pacific during these intervals. These reconstructions provide us with a unique view of Central Tropical Pacific variability and water-column structure at discrete intervals under varying boundary climate conditions with which to assess factors that shape ENSO variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMIN13B1666B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMIN13B1666B"><span>Teleconnection Locator: TeleLoc</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bowen, M. K.; Duffy, D.</p> <p>2016-12-01</p> <p>Extreme climate events, such as tropical storms, droughts, and floods, have an enormous impact on all aspects of society. Being able to detect the causes of such events on a global scale is paramount to being able to predict when and where these events will occur. These teleconnections, where a small change in a closed, complex system creates drastic disturbances elsewhere in the system, are generally represented by an index, one of the most famous being the El Nino Southern Oscillation (ENSO). However, due to the enormity, complexity, and technical challenges surrounding climate and its data, it is hypothesized that many of these teleconnections have as of yet gone undiscovered. TeleLoc (Teleconnection Locator) is a machine-learning framework combining a number of techniques for finding correlations between weather trends and extreme climate events. The current focus is on connecting global trends with tropical cyclones. A combination of two data sets, The International Best Track Archive for Climate Stewardship (IBTrACS) and the Modern-Era Retrospective analysis for Research and Applications (MERRA2), are being utilized. PostGIS is used for raw data storage, and a Python API has been developed as the core of the framework. Cyclones are first clustered using a combination of Symbolic Aggregate ApproXimation (this allows for a symbolic, sequential representation of the various time-series variables of interest) and DBSCAN. This serves to break the events into subcategories, which alleviates computational load for the next step. Events which are clustered together (those with similar characteristics) are compared against global climate variables of interest, which are also converted to a symbolic form, leading up to the event using Association Rule Mining. Results will be shown where cyclones have been clustered, specifically in the West Pacific storm basin, as well as the global variable symbolic subsections with a high support that have been singled out for analysis.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916788H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916788H"><span>The PIRATA Observing System in the Tropical Atlantic: Enhancements and perspectives</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hernandez, Fabrice; Araujo, Moacyr; Bourlès, Bernard; Brandt, Peter; Campos, Edmo; Giordani, Hervé; Lumpkin, Rick; McPhaden, Michael J.; Nobre, Paulo; Saravanan, Ramalingam</p> <p>2017-04-01</p> <p>PIRATA (Prediction and Research Moored Array in the Tropical Atlantic) is a multinational program established to improve our knowledge and understanding of ocean-atmosphere variability in the tropical Atlantic, a region that strongly influences the regional hydro-climates and, consequently, the economies of the regions bordering the Atlantic Ocean (e.g. West Africa, North-Eastern Brazil, the West Indies and the United States). PIRATA is motivated not only by fundamental scientific questions but also by societal needs for improved prediction of climatic variability and its impacts. PIRATA, initiated in 1997, is based around an array of moored buoys providing meteorological and oceanographic measurements transmitted in real-time, disseminated via GTS and Global Data Servers. Then, through yearly mooring maintenance, recorded high frequency data are collected and calibrated. The dedicated cruises of yearly maintenance allow complementary acquisition of a large number of measurements along repeated ship track lines and also provide platforms for deployments of other components of the observing system. Several kinds of operations are carried out in collaboration with other international programs. PIRATA provides invaluable data for numerous and varied applications, among which are analyses of climate variability on intraseasonal-to-decadal timescales, equatorial dynamics, mixed-layer temperature and salinity budgets, air-sea fluxes, data assimilation, and weather and climate forecasts. PIRATA is now 20 years old, well established and recognized as the backbone of the tropical Atlantic sustained observing system. Several enhancements have been achieved during recent years, including progressive updating of mooring systems and sensors, also in collaborations with and as a contribution to other programs (such as EU PREFACE and AtlantOS). Recent major accomplishments in terms of air-sea exchanges and climate predictability will be highlighted in this presentation. Future perspectives for the network will also be discussed in the framework of a sustainable Atlantic Ocean Observing System.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.9354M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.9354M"><span>Physically-based distributed mass balance modeling of a tropical glacier: An application to backward modeling of past climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moelg, T.; Cullen, N. J.; Hardy, D. R.; Winkler, M.; Kaser, G.</p> <p>2009-04-01</p> <p>The use of spatially distributed (2-D) mass balance models has increased in recent years, but mostly focuses on extratropical glacier surfaces. Here we present the first application of a process-based 2-D model to an African glacier: Kersten Glacier on Kilimanjaro. Multi-year data from an automatic weather station (AWS) at 5873 m a.s.l. (500 hPa) serve to force the model. Validation variables comprise surface temperature, surface height change, snow depth, and incoming radiation - all of which indicate a good model performance. Analyses of the interannual variability in the most significant total mass budget terms (surface accumulation, melt, and sublimation), as well as in the related energy fluxes, exhibit a strong link to atmospheric moisture of a particular year. This is because net shortwave radiation (a result of both cloudiness and surface albedo) is the most variable energy flux on monthly to annual time scales. Internal accumulation (refreezing of melt water), however, shows a time lag and is strongest after a very wet year. Due to the limited validation data at lower elevations, we also perform a detailed sensitivity study by varying 17 model parameters - which yields a total mass loss estimate of 522 +/- 105 kg/m2/year under present climate conditions. Moreover, the verified model allows us to perform backward modeling of the last maximum extent of Kersten Glacier in the 1880s, which is indicated by a well preserved terminal moraine. This step reveals decreases in precipitation (30-45%), water vapor pressure (0.1-0.3 hPa) and cloud cover (2-4 percentage units) as the most likely local climate change between late 19th century and present. Thus, the study also demonstrates how 2-D modeling can help reconstruct past climate for a remote place prior to the availability of measurements. In our case these findings have great relevance for the debate of surface versus mid-tropospheric climate change in the tropics.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009pess.conf..331A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009pess.conf..331A"><span>Organizational Climate Assessment: a Systemic Perspective</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Argentero, Piergiorgio; Setti, Ilaria</p> <p></p> <p>A number of studies showed how the set up of an involving and motivating work environment represents a source for organizational competitive advantage: in this view organizational climate (OC) research occupies a preferred position in current I/O psychology. The present study is a review carried out to establish the breadth of the literature on the characteristics of OC assessment considered in a systemic perspective. An organization with a strong climate is a work environment whose members have similar understanding of the norms and practices and share the same expectations. OC should be considered as a sort of emergent entity and, as such, it can be studied only within a systemic perspective because it is linked with some organizational variables, in terms of antecedents (such as the organization's internal structure and its environmental features) and consequences (such as job performance, psychological well-being and withdrawal) of the climate itself. In particular, when employees have a positive view of their organizational environment, consistently with their values and interests, they are more likely to identify their personal goals with those of the organization and, in turn, to invest a greater effort to pursue them: the employees' perception of the organizational environment is positively related to the key outcomes such as job involvement, effort and performance. OC analysis could also be considered as an effective Organizational Development (OD) tool: in particular, the Survey Feedback, that is the return of the OC survey results, could be an effective instrument to assess the efficacy of specific OD programs, such as Team Building, TQM and Gainsharing. The present study is focused on the interest to investigate all possible variables which are potential moderators of the climate - outcome relationship: therefore future researches in the OC field should consider a great variety of organizational variables, considered in terms of antecedents and effects of OC, and OC studies should be conducted as cross-level and multilevel researches.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC41B1015W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC41B1015W"><span>Interannual to Decadal SST Variability in the Tropical Indian Ocean</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, G.; Newman, M.; Han, W.</p> <p>2017-12-01</p> <p>The Indian Ocean has received increasing attention in recent years for its large impacts on regional and global climate. However, due mainly to the close interdependence of the climate variation within the Tropical Pacific and the Indian Ocean, the internal sea surface temperature (SST) variability within the Indian Ocean has not been studied extensively on longer time scales. In this presentation we will show analysis of the interannual to decadal SST variability in the Tropical Indian Ocean in observations and Linear Inverse Model (LIM) results. We also compare the decoupled Indian Ocean SST variability from the Pacific against fully coupled one based on LIM integrations, to test the factors influence the features of the leading SST modes in the Indian Ocean. The result shows the Indian Ocean Basin (IOB) mode, which is strongly related to global averaged SST variability, passively responses to the Pacific variation. Without tropical Indo-Pacific coupling interaction, the intensity of IOB significantly decreases by 80%. The Indian Ocean Dipole (IOD) mode demonstrates its independence from the Pacific SST variability since the IOD does not change its long-term characteristics at all without inter-basin interactions. The overall SSTA variance decreases significantly in the Tropical Indian Ocean in the coupling restricted LIM runs, especially when the one-way impact from the Pacific to the Indian Ocean is turned off, suggesting that most of the variability in the Indian Ocean comes from the Pacific influence. On the other hand, the Indian Ocean could also transport anomalies to the Pacific, making the interaction a complete two-way process.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_23 --> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70034288','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70034288"><span>Climatic extremes improve predictions of spatial patterns of tree species</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.</p> <p>2009-01-01</p> <p>Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AWUTP..58...64C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AWUTP..58...64C"><span>Clouds and the Near-Earth Environment: Possible Links</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Condurache-Bota, Simona; Voiculescu, Mirela; Dragomir, Carmelia</p> <p>2015-12-01</p> <p>Climate variability is a hot topic not only for scientists and policy-makers, but also for each and every one of us. The anthropogenic activities are considered to be responsible for most climate change, however there are large uncertainties about the magnitude of effects of solar variability and other extraterrestrial influences, such as galactic cosmic rays on terrestrial climate. Clouds play an important role due to feedbacks of the radiation budget: variation of cloud cover/composition affects climate, which, in turn, affects cloud cover via atmospheric dynamics and sea temperature variations. Cloud formation and evolution are still under scientific scrutiny, since their microphysics is still not understood. Besides atmospheric dynamics and other internal climatic parameters, extraterrestrial sources of cloud cover variation are considered. One of these is the solar wind, whose effect on cloud cover might be modulated by the global atmospheric electrical circuit. Clouds height and composition, their seasonal variation and latitudinal distribution should be considered when trying to identify possible mechanisms by which solar energy is transferred to clouds. The influence of the solar wind on cloud formation can be assessed also through the ap index - the geomagnetic storm index, which can be readily connected with interplanetary magnetic field, IMF structure. This paper proposes to assess the possible relationship between both cloud cover and solar wind proxies, as the ap index, function of cloud height and composition and also through seasonal studies. The data covers almost three solar cycles (1984-2009). Mechanisms are looked for by investigating observed trends or correlation at local/seasonal scale</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150022193','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150022193"><span>Stability of ENSO and Its Tropical Pacific Teleconnections over the Last Millennium</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lewis, Sophie; Legrande, A. N.</p> <p>2015-01-01</p> <p>Determining past changes in the amplitude, frequency and teleconnections of the El Nio Southern Oscillation (ENSO) is important for understanding its potential sensitivity to future anthropogenic climate change. Palaeo-reconstructions from proxy records provide long-term information of ENSO interactions with the background climatic state through time. However, it remains unclear how ENSO characteristics have changed through time, and precisely which signals proxies record. Proxy interpretations are underpinned by the assumption of stationarity in relationships between local and remote climates, and often utilise archives from single locations located in the Pacific Ocean to reconstruct ENSO histories. Here, we investigate the stationarity of ENSO teleconnections using the Last Millennium experiment of CMIP5 (Coupled Model Intercomparison Project phase 5) (Taylor et al., 2012). We show that modelled ENSO characteristics vary on decadal- to centennial-scales, resulting from internal variability and external forcings, such as tropical volcanic eruptions. Furthermore, the relationship between ENSO conditions and local climates across the Pacific basin varies throughout the Last Millennium. Results show the stability of teleconnections is regionally dependent and proxies may reveal complex changes in teleconnected patterns, rather than large-scale changes in base ENSO characteristics. As such, proxy insights into ENSO likely require evidence to be synthesised over large spatial areas in order to deconvolve changes occurring in the NINO3.4 region from those pertaining to proxy-relevant local climatic variables. To obtain robust histories of the ENSO and its remote impacts, we recommend interpretations of proxy records should be considered in conjunction with palaeo-reconstructions from within the Central Pacific</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24101485','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24101485"><span>Delayed detection of climate mitigation benefits due to climate inertia and variability.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tebaldi, Claudia; Friedlingstein, Pierre</p> <p>2013-10-22</p> <p>Climate change mitigation acts by reducing greenhouse gas emissions, and thus curbing, or even reversing, the increase in their atmospheric concentration. This reduces the associated anthropogenic radiative forcing, and hence the size of the warming. Because of the inertia and internal variability affecting the climate system and the global carbon cycle, it is unlikely that a reduction in warming would be immediately discernible. Here we use 21st century simulations from the latest ensemble of Earth System Model experiments to investigate and quantify when mitigation becomes clearly discernible. We use one of the scenarios as a reference for a strong mitigation strategy, Representative Concentration Pathway (RCP) 2.6 and compare its outcome with either RCP4.5 or RCP8.5, both of which are less severe mitigation pathways. We analyze global mean atmospheric CO2, and changes in annually and seasonally averaged surface temperature at global and regional scales. For global mean surface temperature, the median detection time of mitigation is about 25-30 y after RCP2.6 emissions depart from the higher emission trajectories. This translates into detection of a mitigation signal by 2035 or 2045, depending on whether the comparison is with RCP8.5 or RCP4.5, respectively. The detection of climate benefits of emission mitigation occurs later at regional scales, with a median detection time between 30 and 45 y after emission paths separate. Requiring a 95% confidence level induces a delay of several decades, bringing detection time toward the end of the 21st century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70041536','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70041536"><span>Do bioclimate variables improve performance of climate envelope models?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.</p> <p>2012-01-01</p> <p>Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC43E..01L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC43E..01L"><span>The West African monsoon: Contribution of the AMMA multidisciplinary programme to the study of a regional climate system.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lebel, T.; Janicot, S.; Redelsperger, J. L.; Parker, D. J.; Thorncroft, C. D.</p> <p>2015-12-01</p> <p>The AMMA international project aims at improving our knowledge and understanding of the West African monsoon and its variability with an emphasis on daily-to-interannual timescales. AMMA is motivated by an interest in fundamental scientific issues and by the societal need for improved prediction of the WAM and its impacts on water resources, health and food security for West African nations. The West African monsoon (WAM) has a distinctive annual cycle in rainfall that remains a challenge to understand and predict. The location of peak rainfall, which resides in the Northern Hemisphere throughout the year, moves from the ocean to the land in boreal spring. Around the end of June there is a rapid shift in the location of peak rainfall between the coast and around 10°N where it remains until about the end of August. In September the peak rainfall returns equatorward at a relatively steady pace and is located over the ocean again by November. The fact that the peak rainfall migrates irregularly compared to the peak solar heating is due to the interactions that occur between the land, the atmosphere and the ocean. To gain a better understanding of this complex climate system, a large international research programme was launched in 2002, the biggest of its kind into environment and climate ever attempted in Africa. AMMA has involved a comprehensive field experiment bringing together ocean, land and atmospheric measurements, on timescales ranging from hourly and daily variability up to the changes in seasonal activity over a number of years. This presentation will focus on the description of the field programme and its accomplishments, and address some key questions that have been recently identified to form the core of AMMA-Phase 2.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC43E..01L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC43E..01L"><span>The West African monsoon: Contribution of the AMMA multidisciplinary programme to the study of a regional climate system.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lebel, T.; Janicot, S.; Redelsperger, J. L.; Parker, D. J.; Thorncroft, C. D.</p> <p>2014-12-01</p> <p>The AMMA international project aims at improving our knowledge and understanding of the West African monsoon and its variability with an emphasis on daily-to-interannual timescales. AMMA is motivated by an interest in fundamental scientific issues and by the societal need for improved prediction of the WAM and its impacts on water resources, health and food security for West African nations. The West African monsoon (WAM) has a distinctive annual cycle in rainfall that remains a challenge to understand and predict. The location of peak rainfall, which resides in the Northern Hemisphere throughout the year, moves from the ocean to the land in boreal spring. Around the end of June there is a rapid shift in the location of peak rainfall between the coast and around 10°N where it remains until about the end of August. In September the peak rainfall returns equatorward at a relatively steady pace and is located over the ocean again by November. The fact that the peak rainfall migrates irregularly compared to the peak solar heating is due to the interactions that occur between the land, the atmosphere and the ocean. To gain a better understanding of this complex climate system, a large international research programme was launched in 2002, the biggest of its kind into environment and climate ever attempted in Africa. AMMA has involved a comprehensive field experiment bringing together ocean, land and atmospheric measurements, on timescales ranging from hourly and daily variability up to the changes in seasonal activity over a number of years. This presentation will focus on the description of the field programme and its accomplishments, and address some key questions that have been recently identified to form the core of AMMA-Phase 2.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.1281B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.1281B"><span>Seasonally resolved climate variability during the last interglacial from southern Caribbean corals</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brocas, William; Felis, Thomas; Kölling, Martin; Scholz, Denis; Lohmann, Gerrit; Scheffers, Sanders</p> <p>2013-04-01</p> <p>A range of future climate scenarios have been predicted for a warmer Earth as a result of varying anthropogenic greenhouse emissions. The Last Interglacial period (~125,000 years ago, Marine Isotope Stage 5) offers a period in time which is estimated to have been in the range of 0.1 to > 2oC warmer than present (AD 1961-1990). Although this period is not considered completely analogous for future climate states, the mechanisms behind such changes have the potential to be well understood. Here we present the initial findings of a study which aims to augment current understanding by quantifying the climate dynamics of the tropical southern Caribbean using high resolution marine climate archives. In doing so, we highlight geochemical proxies obtained from aragonitic coral skeletons as a proxy for seasonality and interannual to decadal climate variability. Unique fossil coral material has been collected from an uplifted reef terrace on the island of Bonaire (Netherlands Antilles), which according to 230Th/U dating, was deposited during the Last Interglacial. The sampling technique employed here has been focused using C/T scanning and X-radiography which revealed annual density bands in 21 individual coral colonies. Due to a high average extension rate of greater than 6mm/year, monthly records are available which represent growth periods from 9 to 40 years and so cover various time windows across the Last Interglacial. We discuss the results from geochemical signals of Sr/Ca and oxygen isotope ratios (δ18O) which reflect, respectively, regional temperature and hydrological balance at the sea surface. The finding that Sr/Ca and δ18O cycles occur alongside visible annual density bands allows the quality of the fossil coral material to be considered high and reliable. To further supplement the interpretation of these records greyscale increment analysis, Mg/Ca and δ13C records are presented. The implications of these findings, when compared to Holocene records, identify the variability of internal and external forcing mechanisms behind the local behaviour of climate patterns and phenomena. By comparing our findings to "state of the art" climate models, the reconstructed index states of such patterns can be placed into a larger spatial context. This work is a contribution to the DFG Programme INTERDYNAMIC</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.noaa.gov/climate','SCIGOVWS'); return false;" href="http://www.noaa.gov/climate"><span>Climate | National Oceanic and Atmospheric Administration</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.science.gov/aboutsearch.html">Science.gov Websites</a></p> <p></p> <p></p> <p>to help people understand and prepare for <em>climate</em> variability and <em>change</em>. <em>Climate</em>. NOAA From to help people understand and prepare for <em>climate</em> variability and <em>change</em>. LATEST FEATURES // Ocean Jump to Content Enter Search Terms Weather <em>Climate</em> Oceans & Coasts Fisheries Satellites</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1613307H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1613307H"><span>Detection and attribution of extreme weather disasters</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Huggel, Christian; Stone, Dáithí; Hansen, Gerrit</p> <p>2014-05-01</p> <p>Single disasters related to extreme weather events have caused loss and damage on the order of up to tens of billions US dollars over the past years. Recent disasters fueled the debate about whether and to what extent these events are related to climate change. In international climate negotiations disaster loss and damage is now high on the agenda, and related policy mechanisms have been discussed or are being implemented. In view of funding allocation and effective risk reduction strategies detection and attribution to climate change of extreme weather events and disasters is a key issue. Different avenues have so far been taken to address detection and attribution in this context. Physical climate sciences have developed approaches, among others, where variables that are reasonably sampled over climatically relevant time periods and related to the meteorological characteristics of the extreme event are examined. Trends in these variables (e.g. air or sea surface temperatures) are compared between observations and climate simulations with and without anthropogenic forcing. Generally, progress has been made in recent years in attribution of changes in the chance of some single extreme weather events to anthropogenic climate change but there remain important challenges. A different line of research is primarily concerned with losses related to the extreme weather events over time, using disaster databases. A growing consensus is that the increase in asset values and in exposure are main drivers of the strong increase of economic losses over the past several decades, and only a limited number of studies have found trends consistent with expectations from climate change. Here we propose a better integration of existing lines of research in detection and attribution of extreme weather events and disasters by applying a risk framework. Risk is thereby defined as a function of the probability of occurrence of an extreme weather event, and the associated consequences, with consequences being a function of the intensity of the physical weather event, the exposure and value of assets, and vulnerabilities. We have examined selected major extreme events and disasters, including superstorm Sandy in 2012, the Pakistan floods and the heat wave in Russia in 2010, the 2010 floods in Colombia and the 2011 floods in Australia. We systematically analyzed to what extent (anthropogenic) climate change may have contributed to intensity and frequency of the event, along with changes in the other risk variables, to eventually reach a more comprehensive understanding of the relative role of climate change in recent loss and damage of extreme weather events.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H33Q..03L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H33Q..03L"><span>A Bottom-up Vulnerability Analysis of Water Systems with Decentralized Decision Making and Demographic Shifts- the Case of Jordan.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lachaut, T.; Yoon, J.; Klassert, C. J. A.; Talozi, S.; Mustafa, D.; Knox, S.; Selby, P. D.; Haddad, Y.; Gorelick, S.; Tilmant, A.</p> <p>2016-12-01</p> <p>Probabilistic approaches to uncertainty in water systems management can face challenges of several types: non stationary climate, sudden shocks such as conflict-driven migrations, or the internal complexity and dynamics of large systems. There has been a rising trend in the development of bottom-up methods that place focus on the decision side instead of probability distributions and climate scenarios. These approaches are based on defining acceptability thresholds for the decision makers and considering the entire range of possibilities over which such thresholds are crossed. We aim at improving the knowledge on the applicability and relevance of this approach by enlarging its scope beyond climate uncertainty and single decision makers; thus including demographic shifts, internal system dynamics, and multiple stakeholders at different scales. This vulnerability analysis is part of the Jordan Water Project and makes use of an ambitious multi-agent model developed by its teams with the extensive cooperation of the Ministry of Water and Irrigation of Jordan. The case of Jordan is a relevant example for migration spikes, rapid social changes, resource depletion and climate change impacts. The multi-agent modeling framework used provides a consistent structure to assess the vulnerability of complex water resources systems with distributed acceptability thresholds and stakeholder interaction. A proof of concept and preliminary results are presented for a non-probabilistic vulnerability analysis that involves different types of stakeholders, uncertainties other than climatic and the integration of threshold-based indicators. For each stakeholder (agent) a vulnerability matrix is constructed over a multi-dimensional domain, which includes various hydrologic and/or demographic variables.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26027583','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26027583"><span>Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R</p> <p>2015-04-01</p> <p>Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1406716-recent-changes-county-level-corn-yield-variability-united-states-from-observations-crop-models','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1406716-recent-changes-county-level-corn-yield-variability-united-states-from-observations-crop-models"><span>Recent changes in county-level corn yield variability in the United States from observations and crop models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Leng, Guoyong</p> <p></p> <p>The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated the change trend of corn yield variability, in projecting its future changes.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=Risk+AND+feelings&pg=3&id=ED559550','ERIC'); return false;" href="https://eric.ed.gov/?q=Risk+AND+feelings&pg=3&id=ED559550"><span>Violence and Disorder, School Climate, and PBIS: The Relationship among School Climate, Student Outcomes, and the Use of Positive Behavioral Interventions and Supports</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Eacho, Thomas Christopher</p> <p>2013-01-01</p> <p>The primary purpose of this study was to examine the relationship between school climate and student outcome variables. The secondary purpose was to examine the relationship between the use of Positive Behavioral Interventions and Supports (PBIS) and the same student outcome variables. Variables depicting student perceptions of school climate,…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913896V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913896V"><span>Uncertainty in projected point precipitation extremes for hydrological impact analysis of climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Van Uytven, Els; Willems, Patrick</p> <p>2017-04-01</p> <p>Current trends in the hydro-meteorological variables indicate the potential impact of climate change on hydrological extremes. Therefore, they trigger an increased importance climate adaptation strategies in water management. The impact of climate change on hydro-meteorological and hydrological extremes is, however, highly uncertain. This is due to uncertainties introduced by the climate models, the internal variability inherent to the climate system, the greenhouse gas scenarios and the statistical downscaling methods. In view of the need to define sustainable climate adaptation strategies, there is a need to assess these uncertainties. This is commonly done by means of ensemble approaches. Because more and more climate models and statistical downscaling methods become available, there is a need to facilitate the climate impact and uncertainty analysis. A Climate Perturbation Tool has been developed for that purpose, which combines a set of statistical downscaling methods including weather typing, weather generator, transfer function and advanced perturbation based approaches. By use of an interactive interface, climate impact modelers can apply these statistical downscaling methods in a semi-automatic way to an ensemble of climate model runs. The tool is applicable to any region, but has been demonstrated so far to cases in Belgium, Suriname, Vietnam and Bangladesh. Time series representing future local-scale precipitation, temperature and potential evapotranspiration (PET) conditions were obtained, starting from time series of historical observations. Uncertainties on the future meteorological conditions are represented in two different ways: through an ensemble of time series, and a reduced set of synthetic scenarios. The both aim to span the full uncertainty range as assessed from the ensemble of climate model runs and downscaling methods. For Belgium, for instance, use was made of 100-year time series of 10-minutes precipitation observations and daily temperature and PET observations at Uccle and a large ensemble of 160 global climate model runs (CMIP5). They cover all four representative concentration pathway based greenhouse gas scenarios. While evaluating the downscaled meteorological series, particular attention was given to the performance of extreme value metrics (e.g. for precipitation, by means of intensity-duration-frequency statistics). Moreover, the total uncertainty was decomposed in the fractional uncertainties for each of the uncertainty sources considered. Research assessing the additional uncertainty due to parameter and structural uncertainties of the hydrological impact model is ongoing.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.5600K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.5600K"><span>Impacts of boundary condition changes on regional climate projections over West Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kim, Jee Hee; Kim, Yeonjoo; Wang, Guiling</p> <p>2017-06-01</p> <p>Future projections using regional climate models (RCMs) are driven with boundary conditions (BCs) typically derived from global climate models. Understanding the impact of the various BCs on regional climate projections is critical for characterizing their robustness and uncertainties. In this study, the International Center for Theoretical Physics Regional Climate Model Version 4 (RegCM4) is used to investigate the impact of different aspects of boundary conditions, including lateral BCs and sea surface temperature (SST), on projected future changes of regional climate in West Africa, and BCs from the coupled European Community-Hamburg Atmospheric Model 5/Max Planck Institute Ocean Model are used as an example. Historical, future, and several sensitivity experiments are conducted with various combinations of BCs and CO2 concentration, and differences among the experiments are compared to identify the most important drivers for RCMs. When driven by changes in all factors, the RegCM4-produced future climate changes include significantly drier conditions in Sahel and wetter conditions along the Guinean coast. Changes in CO2 concentration within the RCM domain alone or changes in wind vectors at the domain boundaries alone have minor impact on projected future climate changes. Changes in the atmospheric humidity alone at the domain boundaries lead to a wetter Sahel due to the northward migration of rain belts during summer. This impact, although significant, is offset and dominated by changes of other BC factors (primarily temperature) that cause a drying signal. Future changes of atmospheric temperature at the domain boundaries combined with SST changes over oceans are sufficient to cause a future climate that closely resembles the projection that accounts for all factors combined. Therefore, climate variability and changes simulated by RCMs depend primarily on the variability and change of temperature aspects of the RCM BCs. Moreover, it is found that the response of the RCM climate to different climate change factors is roughly linear in that the projected changes driven by combined factors are close to the sum of projected changes due to each individual factor alone at least for long-term averages. Findings from this study are important for understanding the source(s) of uncertainties in regional climate projections and for designing innovative approaches to climate downscaling and impact assessment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMPA23A2189A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMPA23A2189A"><span>The Power of Cooperation in International Paleoclimate Science: Examples from the PAGES 2k Network and the Ocean2k Working Group</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Addison, J. A.</p> <p>2015-12-01</p> <p>The Past Global Changes (PAGES) project of IGBP and Future Earth supports research to understand the Earth's past environment to improve future climate predictions and inform strategies for sustainability. Within this framework, the PAGES 2k Network was established to provide a focus on the past 2000 years, a period that encompasses Medieval Climate Anomaly warming, Little Ice Age cooling, and recent anthropogenically-forced climate change. The results of these studies are used for testing earth system models, and for understanding decadal- to centennial-scale variability, which is needed for long-term planning. International coordination and cooperation among the nine regional Working Groups that make up the 2k Network has been critical to the success of PAGES 2k. The collaborative approach is moving toward scientific achievements across the regional groups, including: (i) the development of a community-driven open-access proxy climate database; (ii) integration of multi-resolution proxy records; (iii) development of multivariate climate reconstructions; and (iv) a leap forward in the spatial resolution of paleoclimate reconstructions. The last addition to the 2k Network, the Ocean2k Working Group has further innovated the collaborative approach by: (1) creating an open, receptive environment to discuss ideas exclusively in the virtual space; (2) employing an array of real-time collaborative software tools to enable communication, group document writing, and data analysis; (3) consolidating executive leadership teams to oversee project development and manage grassroots-style volunteer pools; and (4) embracing the value-added role that international and interdisciplinary science can play in advancing paleoclimate hypotheses critical to understanding future change. Ongoing efforts for the PAGES 2k Network are focused on developing new standards for data quality control and archiving. These tasks will provide the foundation for new and continuing "trans-regional" 2k projects which address paleoclimate science that transcend regional boundaries. The PAGES 2k Network encourages participation by all investigators interested in this community-wide project.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ThApC.131.1449J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ThApC.131.1449J"><span>Mechanism of ENSO influence on the South Asian monsoon rainfall in global model simulations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Joshi, Sneh; Kar, Sarat C.</p> <p>2018-02-01</p> <p>Coupled ocean atmosphere global climate models are increasingly being used for seasonal scale simulation of the South Asian monsoon. In these models, sea surface temperatures (SSTs) evolve as coupled air-sea interaction process. However, sensitivity experiments with various SST forcing can only be done in an atmosphere-only model. In this study, the Global Forecast System (GFS) model at T126 horizontal resolution has been used to examine the mechanism of El Niño-Southern Oscillation (ENSO) forcing on the monsoon circulation and rainfall. The model has been integrated (ensemble) with observed, climatological and ENSO SST forcing to document the mechanism on how the South Asian monsoon responds to basin-wide SST variations in the Indian and Pacific Oceans. The model simulations indicate that the internal variability gets modulated by the SSTs with warming in the Pacific enhancing the ensemble spread over the monsoon region as compared to cooling conditions. Anomalous easterly wind anomalies cover the Indian region both at 850 and 200 hPa levels during El Niño years. The locations and intensity of Walker and Hadley circulations are altered due to ENSO SST forcing. These lead to reduction of monsoon rainfall over most parts of India during El Niño events compared to La Niña conditions. However, internally generated variability is a major source of uncertainty in the model-simulated climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NatCC...6..280B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NatCC...6..280B"><span>Mapping the future expansion of Arctic open water</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barnhart, Katherine R.; Miller, Christopher R.; Overeem, Irina; Kay, Jennifer E.</p> <p>2016-03-01</p> <p>Sea ice impacts most of the Arctic environment, from ocean circulation and marine ecosystems to animal migration and marine transportation. Sea ice has thinned and decreased in age over the observational record. Ice extent has decreased. Reduced ice cover has warmed the surface ocean, accelerated coastal erosion and impacted biological productivity. Declines in Arctic sea-ice extent cannot be explained by internal climate variability alone and can be attributed to anthropogenic effects. However, extent is a poor measure of ice decline at specific locations as it integrates over the entire Arctic basin and thus contains no spatial information. The open water season, in contrast, is a metric that represents the duration of open water over a year at an individual location. Here we present maps of the open water season over the period 1920-2100 using daily output from a 30-member initial-condition ensemble of business-as-usual climate simulations that characterize the expansion of Arctic open water, determine when the open water season will move away from pre-industrial conditions (`shift’ time) and identify when human forcing will take the Arctic sea-ice system outside its normal bounds (`emergence’ time). The majority of the Arctic nearshore regions began shifting in 1990 and will begin leaving the range of internal variability in 2040. Models suggest that ice will cover coastal regions for only half of the year by 2070.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3620768','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3620768"><span>Climate Change, Human Health, and Biomedical Research: Analysis of the National Institutes of Health Research Portfolio</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Balbus, John M.; Christian, Carole; Haque, Ehsanul; Howe, Sally E.; Newton, Sheila A.; Reid, Britt C.; Roberts, Luci; Wilhelm, Erin; Rosenthal, Joshua P.</p> <p>2013-01-01</p> <p>Background: According to a wide variety of analyses and projections, the potential effects of global climate change on human health are large and diverse. The U.S. National Institutes of Health (NIH), through its basic, clinical, and population research portfolio of grants, has been increasing efforts to understand how the complex interrelationships among humans, ecosystems, climate, climate variability, and climate change affect domestic and global health. Objectives: In this commentary we present a systematic review and categorization of the fiscal year (FY) 2008 NIH climate and health research portfolio. Methods: A list of candidate climate and health projects funded from FY 2008 budget appropriations were identified and characterized based on their relevance to climate change and health and based on climate pathway, health impact, study type, and objective. Results: This analysis identified seven FY 2008 projects focused on climate change, 85 climate-related projects, and 706 projects that focused on disease areas associated with climate change but did not study those associations. Of the nearly 53,000 awards that NIH made in 2008, approximately 0.17% focused on or were related to climate. Conclusions: Given the nature and scale of the potential effects of climate change on human health and the degree of uncertainty that we have about these effects, we think that it is helpful for the NIH to engage in open discussions with science and policy communities about government-wide needs and opportunities in climate and health, and about how NIH’s strengths in human health research can contribute to understanding the health implications of global climate change. This internal review has been used to inform more recent initiatives by the NIH in climate and health. PMID:23552460</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_24 --> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23552460','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23552460"><span>Climate change, human health, and biomedical research: analysis of the National Institutes of Health research portfolio.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jessup, Christine M; Balbus, John M; Christian, Carole; Haque, Ehsanul; Howe, Sally E; Newton, Sheila A; Reid, Britt C; Roberts, Luci; Wilhelm, Erin; Rosenthal, Joshua P</p> <p>2013-04-01</p> <p>According to a wide variety of analyses and projections, the potential effects of global climate change on human health are large and diverse. The U.S. National Institutes of Health (NIH), through its basic, clinical, and population research portfolio of grants, has been increasing efforts to understand how the complex interrelationships among humans, ecosystems, climate, climate variability, and climate change affect domestic and global health. In this commentary we present a systematic review and categorization of the fiscal year (FY) 2008 NIH climate and health research portfolio. A list of candidate climate and health projects funded from FY 2008 budget appropriations were identified and characterized based on their relevance to climate change and health and based on climate pathway, health impact, study type, and objective. This analysis identified seven FY 2008 projects focused on climate change, 85 climate-related projects, and 706 projects that focused on disease areas associated with climate change but did not study those associations. Of the nearly 53,000 awards that NIH made in 2008, approximately 0.17% focused on or were related to climate. Given the nature and scale of the potential effects of climate change on human health and the degree of uncertainty that we have about these effects, we think that it is helpful for the NIH to engage in open discussions with science and policy communities about government-wide needs and opportunities in climate and health, and about how NIH's strengths in human health research can contribute to understanding the health implications of global climate change. This internal review has been used to inform more recent initiatives by the NIH in climate and health.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24465610','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24465610"><span>Effects of climatic factors and ecosystem responses on the inter-annual variability of evapotranspiration in a coniferous plantation in subtropical China.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui</p> <p>2014-01-01</p> <p>Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003-2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003-2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May-June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3899034','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3899034"><span>Effects of Climatic Factors and Ecosystem Responses on the Inter-Annual Variability of Evapotranspiration in a Coniferous Plantation in Subtropical China</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui</p> <p>2014-01-01</p> <p>Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003–2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003–2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May–June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation. PMID:24465610</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1713065F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1713065F"><span>Determination of Arctic sea ice variability modes on interannual timescales via nonhierarchical clustering</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fučkar, Neven-Stjepan; Guemas, Virginie; Massonnet, François; Doblas-Reyes, Francisco</p> <p>2015-04-01</p> <p>Over the modern observational era, the northern hemisphere sea ice concentration, age and thickness have experienced a sharp long-term decline superimposed with strong internal variability. Hence, there is a crucial need to identify robust patterns of Arctic sea ice variability on interannual timescales and disentangle them from the long-term trend in noisy datasets. The principal component analysis (PCA) is a versatile and broadly used method for the study of climate variability. However, the PCA has several limiting aspects because it assumes that all modes of variability have symmetry between positive and negative phases, and suppresses nonlinearities by using a linear covariance matrix. Clustering methods offer an alternative set of dimension reduction tools that are more robust and capable of taking into account possible nonlinear characteristics of a climate field. Cluster analysis aggregates data into groups or clusters based on their distance, to simultaneously minimize the distance between data points in a given cluster and maximize the distance between the centers of the clusters. We extract modes of Arctic interannual sea-ice variability with nonhierarchical K-means cluster analysis and investigate the mechanisms leading to these modes. Our focus is on the sea ice thickness (SIT) as the base variable for clustering because SIT holds most of the climate memory for variability and predictability on interannual timescales. We primarily use global reconstructions of sea ice fields with a state-of-the-art ocean-sea-ice model, but we also verify the robustness of determined clusters in other Arctic sea ice datasets. Applied cluster analysis over the 1958-2013 period shows that the optimal number of detrended SIT clusters is K=3. Determined SIT cluster patterns and their time series of occurrence are rather similar between different seasons and months. Two opposite thermodynamic modes are characterized with prevailing negative or positive SIT anomalies over the Arctic basin. The intermediate mode, with negative anomalies centered on the East Siberian shelf and positive anomalies along the North American side of the basin, has predominately dynamic characteristics. The associated sea ice concentration (SIC) clusters vary more between different seasons and months, but the SIC patterns are physically framed by the SIT cluster patterns.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ESSD....9..471J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ESSD....9..471J"><span>Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jones, Philip D.; Harpham, Colin; Troccoli, Alberto; Gschwind, Benoit; Ranchin, Thierry; Wald, Lucien; Goodess, Clare M.; Dorling, Stephen</p> <p>2017-07-01</p> <p>The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979-2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from <a href="ftp://ecem.climate.copernicus.eu" target="_blank">ftp://ecem.climate.copernicus.eu</a>. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160009138&hterms=India+climate+change&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DIndia%2Bclimate%2Bchange','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160009138&hterms=India+climate+change&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DIndia%2Bclimate%2Bchange"><span>Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos</p> <p>2016-01-01</p> <p>We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1261480-response-guided-community-detection-application-climate-index-discovery','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1261480-response-guided-community-detection-application-climate-index-discovery"><span>Response-Guided Community Detection: Application to Climate Index Discovery</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Bello, Gonzalo; Angus, Michael; Pedemane, Navya</p> <p></p> <p>Discovering climate indices-time series that summarize spatiotemporal climate patterns-is a key task in the climate science domain. In this work, we approach this task as a problem of response-guided community detection; that is, identifying communities in a graph associated with a response variable of interest. To this end, we propose a general strategy for response-guided community detection that explicitly incorporates information of the response variable during the community detection process, and introduce a graph representation of spatiotemporal data that leverages information from multiple variables. We apply our proposed methodology to the discovery of climate indices associated with seasonal rainfall variability.more » Our results suggest that our methodology is able to capture the underlying patterns known to be associated with the response variable of interest and to improve its predictability compared to existing methodologies for data-driven climate index discovery and official forecasts.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160012261&hterms=leadership&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dleadership','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160012261&hterms=leadership&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dleadership"><span>The Vulnerability, Impacts, Adaptation and Climate Services Advisory Board (VIACS AB V1.0) Contribution to CMIP6</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ruane, Alex C.; Teichmann, Claas; Arnell, Nigel W.; Carter, Timothy R.; Ebi, Kristie L.; Frieler, Katja; Goodess, Clare M.; Hewitson, Bruce; Horton, Radley; Kovats, R. Sari; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20160012261'); toggleEditAbsImage('author_20160012261_show'); toggleEditAbsImage('author_20160012261_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20160012261_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20160012261_hide"></p> <p>2016-01-01</p> <p>This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decisionmakers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs (observational datasets) and indicated user needs for the gridding and processing of model output.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GMD.....9.3493R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GMD.....9.3493R"><span>The Vulnerability, Impacts, Adaptation and Climate Services Advisory Board (VIACS AB v1.0) contribution to CMIP6</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ruane, Alex C.; Teichmann, Claas; Arnell, Nigel W.; Carter, Timothy R.; Ebi, Kristie L.; Frieler, Katja; Goodess, Clare M.; Hewitson, Bruce; Horton, Radley; Sari Kovats, R.; Lotze, Heike K.; Mearns, Linda O.; Navarra, Antonio; Ojima, Dennis S.; Riahi, Keywan; Rosenzweig, Cynthia; Themessl, Matthias; Vincent, Katharine</p> <p>2016-09-01</p> <p>This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decision-makers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs and indicated user needs for the gridding and processing of model output.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.cpc.ncep.noaa.gov/products/outreach/CDPW41/CDPW41.php','SCIGOVWS'); return false;" href="http://www.cpc.ncep.noaa.gov/products/outreach/CDPW41/CDPW41.php"><span>Climate Prediction Center - Outreach: 41st Annual Climate Diagnostics &</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.science.gov/aboutsearch.html">Science.gov Websites</a></p> <p></p> <p></p> <p>the University of Maine <em>Climate</em> <em>Change</em> Institute and School of Earth and <em>Climate</em> Sciences and is co (drought, heat waves, severe weather, tropical cyclones) in the framework of <em>climate</em> variability and <em>change</em> and including the use of paleoclimate data. Arctic <em>climate</em> variability and <em>change</em>, and linkages to</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/of/2011/1238/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/of/2011/1238/"><span>Dynamically downscaled climate simulations over North America: Methods, evaluation, and supporting documentation for users</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Hostetler, S.W.; Alder, J.R.; Allan, A.M.</p> <p>2011-01-01</p> <p>We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs. All simulations span the present (for example, 1968-1999), common periods of the future (2040-2069), and two simulations continuously cover 2010-2099. The trace gas concentrations in our simulations were the same as those of the GCMs: the IPCC 20th century time series for 1968-1999 and the A2 time series for simulations of the future. We demonstrate that RegCM3 is capable of producing present day annual and seasonal climatologies of air temperature and precipitation that are in good agreement with observations. Important features of the high-resolution climatology of temperature, precipitation, snow water equivalent (SWE), and soil moisture are consistently reproduced in all model runs over WNA and ENA. The simulations provide a potential range of future climate change for selected decades and display common patterns of the direction and magnitude of changes. As expected, there are some model to model differences that limit interpretability and give rise to uncertainties. Here, we provide background information about the GCMs and the RegCM3, a basic evaluation of the model output and examples of simulated future climate. We also provide information needed to access the web applications for visualizing and downloading the data, and give complete metadata that describe the variables in the datasets.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C51G..07M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C51G..07M"><span>Forecasting Glacier Evolution and Hindcasting Paleoclimates In Light of Mass Balance Nonlinearities</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Malone, A.; Doughty, A. M.; MacAyeal, D. R.</p> <p>2016-12-01</p> <p>Glaciers are commonly used barometers of present and past climate change, with their variations often being linked to shifts in the mean climate. Climate variability within a unchanging mean state, however, can produce short term mass balance and glacier length anomalies, complicating this linkage. Also, the mass balance response to this variability can be nonlinear, possibly impacting the longer term state of the glacier. We propose a conceptual model to understand these nonlinearities and quantify their impacts on the longer term mass balance and glacier length. The relationship between mass balance and elevation, i.e. the vertical balance profile (VBP), illuminates these nonlinearities (Figure A). The VBP, given here for a wet tropical glacier, is piecewise, which can lead to different mass balance responses to climate anomalies of similar magnitude but opposite sign. We simulate the mass balance response to climate variability by vertically (temperature anomalies) and horizontally (precipitation anomalies) transposing the VBP for the mean climate (Figure A). The resulting anomalous VBP is the superposition of the two translations. We drive a 1-D flowline model with 10,000 years of anomalous VBPs. The aggregate VBP for the mean climate including variability differs from the VBP for the mean climate excluding variability, having a higher equilibrium line altitude (ELA) and a negative mass balance (Figure B). Accordingly, the glacier retreats, and the equilibrium glacier length for the aggregate VBP is the same as the mean length from the 10,000 year flowline simulation (Figure C). The magnitude of the VBP shift and glacier retreat increases with greater temperature variability and larger discontinuities in the VBP slope. These results highlight the importance of both the climate mean and variability in determining the longer term state of the glacier. Thus, forecasting glacier evolution or hindcasting past climates should also include representation of climate variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70030000','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70030000"><span>Detection, attribution, and sensitivity of trends toward earlier streamflow in the Sierra Nevada</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Maurer, E.P.; Stewart, I.T.; Bonfils, Celine; Duffy, P.B.; Cayan, D.</p> <p>2007-01-01</p> <p>Observed changes in the timing of snowmelt dominated streamflow in the western United States are often linked to anthropogenic or other external causes. We assess whether observed streamflow timing changes can be statistically attributed to external forcing, or whether they still lie within the bounds of natural (internal) variability for four large Sierra Nevada (CA) basins, at inflow points to major reservoirs. Streamflow timing is measured by "center timing" (CT), the day when half the annual flow has passed a given point. We use a physically based hydrology model driven by meteorological input from a global climate model to quantify the natural variability in CT trends. Estimated 50-year trends in CT due to natural climate variability often exceed estimated actual CT trends from 1950 to 1999. Thus, although observed trends in CT to date may be statistically significant, they cannot yet be statistically attributed to external influences on climate. We estimate that projected CT changes at the four major reservoir inflows will, with 90% confidence, exceed those from natural variability within 1-4 decades or 4-8 decades, depending on rates of future greenhouse gas emissions. To identify areas most likely to exhibit CT changes in response to rising temperatures, we calculate changes in CT under temperature increases from 1 to 5??. We find that areas with average winter temperatures between -2??C and -4??C are most likely to respond with significant CT shifts. Correspondingly, elevations from 2000 to 2800 in are most sensitive to temperature increases, with CT changes exceeding 45 days (earlier) relative to 1961-1990. Copyright 2007 by the American Geophysical Union.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp...72D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp...72D"><span>Impacts of internal variability on temperature and precipitation trends in large ensemble simulations by two climate models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dai, Aiguo; Bloecker, Christine E.</p> <p>2018-02-01</p> <p>It is known that internal climate variability (ICV) can influence trends seen in observations and individual model simulations over a period of decades. This makes it difficult to quantify the forced response to external forcing. Here we analyze two large ensembles of simulations from 1950 to 2100 by two fully-coupled climate models, namely the CESM1 and CanESM2, to quantify ICV's influences on estimated trends in annual surface air temperature (Tas) and precipitation (P) over different time periods. Results show that the observed trends since 1979 in global-mean Tas and P are within the spread of the CESM1-simulated trends while the CanESM2 overestimates the historical changes, likely due to its deficiencies in simulating historical non-CO2 forcing. Both models show considerable spreads in the Tas and P trends among the individual simulations, and the spreads decrease rapidly as the record length increases to about 40 (50) years for global-mean Tas (P). Because of ICV, local and regional P trends may remain statistically insignificant and differ greatly among individual model simulations over most of the globe until the later part of the twenty-first century even under a high emissions scenario, while local Tas trends since 1979 are already statistically significant over many low-latitude regions and are projected to become significant over most of the globe by the 2030s. The largest influences of ICV come from the Inter-decadal Pacific Oscillation and polar sea ice. In contrast to the realization-dependent ICV, the forced Tas response to external forcing has a temporal evolution that is similar over most of the globe (except its amplitude). For annual precipitation, however, the temporal evolution of the forced response is similar (opposite) to that of Tas over many mid-high latitude areas and the ITCZ (subtropical regions), but close to zero over the transition zones between the regions with positive and negative trends. The ICV in the transient climate change simulations is slightly larger than that in the control run for P (and other related variables such as water vapor), but similar for Tas. Thus, the ICV for P from a control run may need to be scaled up in detection and attribution analyses.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AdAtS..35...14C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AdAtS..35...14C"><span>Simulations of Eurasian winter temperature trends in coupled and uncoupled CFSv2</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Collow, Thomas W.; Wang, Wanqiu; Kumar, Arun</p> <p>2018-01-01</p> <p>Conflicting results have been presented regarding the link between Arctic sea-ice loss and midlatitude cooling, particularly over Eurasia. This study analyzes uncoupled (atmosphere-only) and coupled (ocean-atmosphere) simulations by the Climate Forecast System, version 2 (CFSv2), to examine this linkage during the Northern Hemisphere winter, focusing on the simulation of the observed surface cooling trend over Eurasia during the last three decades. The uncoupled simulations are Atmospheric Model Intercomparison Project (AMIP) runs forced with mean seasonal cycles of sea surface temperature (SST) and sea ice, using combinations of SST and sea ice from different time periods to assess the role that each plays individually, and to assess the role of atmospheric internal variability. Coupled runs are used to further investigate the role of internal variability via the analysis of initialized predictions and the evolution of the forecast with lead time. The AMIP simulations show a mean warming response over Eurasia due to SST changes, but little response to changes in sea ice. Individual runs simulate cooler periods over Eurasia, and this is shown to be concurrent with a stronger Siberian high and warming over Greenland. No substantial differences in the variability of Eurasian surface temperatures are found between the different model configurations. In the coupled runs, the region of significant warming over Eurasia is small at short leads, but increases at longer leads. It is concluded that, although the models have some capability in highlighting the temperature variability over Eurasia, the observed cooling may still be a consequence of internal variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1810725H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1810725H"><span>The Coordinated Ocean Wave Climate Project</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hemer, Mark; Dobrynin, Mikhail; Erikson, Li; Lionello, Piero; Mori, Nobuhito; Semedo, Alvaro; Wang, Xiaolan</p> <p>2016-04-01</p> <p>Future 21st Century changes in wind-wave climate have broad implications for marine and coastal infrastructure and ecosystems. Atmosphere-ocean general circulation models (GCM) are now routinely used for assessing and providing future projections of climatological parameters such as temperature and precipitation, but generally these provide no information on ocean wind-waves. To fill this information gap a growing number of studies are using GCM outputs and independently producing global and regional scale wind-wave climate projections. Furthermore, additional studies are actively coupling wind-wave dependent atmosphere-ocean exchanges into GCMs, to improve physical representation and quantify the impact of waves in the coupled climate system, and can also deliver wave characteristics as another variable in the climate system. To consolidate these efforts, understand the sources of variance between projections generated by different methodologies and International groups, and ultimately provide a robust picture of the role of wind-waves in the climate system and their projected changes, we present outcomes of the JCOMM supported Coordinated Ocean Wave Climate Project (COWCLIP). The objective of COWCLIP is twofold: to make community based ensembles of wave climate projections openly accessible, to provide the necessary information to support diligent marine and coastal impacts of climate change studies; and to understand the effects and feedback influences of wind-waves in the coupled ocean-atmosphere climate system. We will present the current status of COWCLIP, providing an overview of the objectives, analysis and results of the initial phase - now complete - and the progress of ongoing phases of the project.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/27884','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/27884"><span>Impacts of climate change and variability on transportation systems and infrastructure : Gulf Coast study, phase 2 : task 2 : climate variability and change in Mobile, Alabama.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a></p> <p></p> <p>2012-09-01</p> <p>Despite increasing confidence in global climate change projections in recent years, projections of : climate effects at local scales remains scarce. Location-specific risks to transportation systems : imposed by changes in climate are not yet well kn...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016CliPa..12.2255R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016CliPa..12.2255R"><span>Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rehfeld, Kira; Trachsel, Mathias; Telford, Richard J.; Laepple, Thomas</p> <p>2016-12-01</p> <p>Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen, foraminifera or chironomids are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that in our model experiments the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We furthermore show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable, such as summer temperatures in the model's Arctic, are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution. Expert knowledge on the ecophysiological drivers of the proxies, as well as statistical methods that go beyond the cross validation on modern calibration datasets, are crucial to avoid misinterpretation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29391875','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29391875"><span>Change in the magnitude and mechanisms of global temperature variability with warming.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Brown, Patrick T; Ming, Yi; Li, Wenhong; Hill, Spencer A</p> <p>2017-01-01</p> <p>Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC33H..04B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC33H..04B"><span>Change in the Magnitude and Mechanisms of Global Temperature Variability with Warming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brown, P. T.; Ming, Y.; Li, W.; Hill, S. A.</p> <p>2017-12-01</p> <p>Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_25 --> <div class="footer-extlink text-muted" style="margin-bottom:1rem; text-align:center;">Some links on this page may take you to non-federal websites. 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