Drought Persistence in Models and Observations

NASA Astrophysics Data System (ADS)

Moon, Heewon; Gudmundsson, Lukas; Seneviratne, Sonia

2017-04-01

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.

Why Is Rainfall Error Analysis Requisite for Data Assimilation and Climate Modeling?

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.

2004-01-01

Given the large temporal and spatial variability of precipitation processes, errors in rainfall observations are difficult to quantify yet crucial to making effective use of rainfall data for improving atmospheric analysis, weather forecasting, and climate modeling. We highlight the need for developing a quantitative understanding of systematic and random errors in precipitation observations by examining explicit examples of how each type of errors can affect forecasts and analyses in global data assimilation. We characterize the error information needed from the precipitation measurement community and how it may be used to improve data usage within the general framework of analysis techniques, as well as accuracy requirements from the perspective of climate modeling and global data assimilation.

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

Hansen, Gerrit; Stone, Dáithí

Impacts of recent regional changes in climate on natural and human systems are documented across the globe, yet studies explicitly linking these observations to anthropogenic forcing of the climate are scarce. Here in this work, we provide a systematic assessment of the role of anthropogenic climate change for the range of impacts of regional climate trends reported in the IPCC’s Fifth Assessment Report. We find that almost two-thirds of the impacts related to atmospheric and ocean temperature can be confidently attributed to anthropogenic forcing. In contrast, evidence connecting changes in precipitation and their respective impacts to human influence is stillmore » weak. Moreover, anthropogenic climate change has been a major influence for approximately three-quarters of the impacts observed on continental scales. Finally, hence the effects of anthropogenic emissions can now be discerned not only globally, but also at more regional and local scales for a variety of natural and human systems.« less

Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

NASA Technical Reports Server (NTRS)

Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

2015-01-01

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

Evaluating the sensitivity of agricultural model performance to different climate inputs

PubMed Central

Glotter, Michael J.; Moyer, Elisabeth J.; Ruane, Alex C.; Elliott, Joshua W.

2017-01-01

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled to observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections, but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely-used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources – reanalysis, reanalysis bias-corrected with observed climate, and a control dataset – and compared to observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by un-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. However, some issues persist for all choices of climate inputs: crop yields appear oversensitive to precipitation fluctuations but undersensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves. PMID:29097985

Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

NASA Astrophysics Data System (ADS)

Quetin, G. R.; Swann, A. L. S.

2017-12-01

Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models.

Emergent Constraints for Cloud Feedbacks and Climate Sensitivity

DOE PAGES

Klein, Stephen A.; Hall, Alex

2015-10-26

Emergent constraints are physically explainable empirical relationships between characteristics of the current climate and long-term climate prediction that emerge in collections of climate model simulations. With the prospect of constraining long-term climate prediction, scientists have recently uncovered several emergent constraints related to long-term cloud feedbacks. We review these proposed emergent constraints, many of which involve the behavior of low-level clouds, and discuss criteria to assess their credibility. With further research, some of the cases we review may eventually become confirmed emergent constraints, provided they are accompanied by credible physical explanations. Because confirmed emergent constraints identify a source of model errormore » that projects onto climate predictions, they deserve extra attention from those developing climate models and climate observations. While a systematic bias cannot be ruled out, it is noteworthy that the promising emergent constraints suggest larger cloud feedback and hence climate sensitivity.« less

Sensitivity of the Tropical Atmospheric Energy Balance to ENSO-Related SST Changes: Comparison of Climate Model Simulations to Observed Responses

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Fitzjarrald, Dan; Marshall, Susan; Oglesby, Robert; Roads, John; Arnold, James E. (Technical Monitor)

2001-01-01

This paper focuses on how fresh water and radiative fluxes over the tropical oceans change during ENSO warm and cold events and how these changes affect the tropical energy balance. At present, ENSO remains the most prominent known mode of natural variability at interannual time scales. While this natural perturbation to climate is quite distinct from possible anthropogenic changes in climate, adjustments in the tropical water and energy budgets during ENSO may give insight into feedback processes involving water vapor and cloud feedbacks. Although great advances have been made in understanding this phenomenon and realizing prediction skill over the past decade, our ability to document the coupled water and energy changes observationally and to represent them in climate models seems far from settled (Soden, 2000 J Climate). In a companion paper we have presented observational analyses, based principally on space-based measurements which document systematic changes in rainfall, evaporation, and surface and top-of-atmosphere (TOA) radiative fluxes. Here we analyze several contemporary climate models run with observed SSTs over recent decades and compare SST-induced changes in radiation, precipitation, evaporation, and energy transport to observational results. Among these are the NASA / NCAR Finite Volume Model, the NCAR Community Climate Model, the NCEP Global Spectral Model, and the NASA NSIPP Model. Key disagreements between model and observational results noted in the recent literature are shown to be due predominantly to observational shortcomings. A reexamination of the Langley 8-Year Surface Radiation Budget data reveals errors in the SST surface longwave emission due to biased SSTs. Subsequent correction allows use of this data set along with ERBE TOA fluxes to infer net atmospheric radiative heating. Further analysis of recent rainfall algorithms provides new estimates for precipitation variability in line with interannual evaporation changes inferred from the da Silva, Young, Levitus COADS analysis. The overall results from our analysis suggest an increase (decrease) of the hydrologic cycle during ENSO warm (cold) events at the rate of about 5 W/sq m per K of SST change. Model results agree reasonably well with this estimate of sensitivity. This rate is slightly less than that which would be expected for constant relative humidity over the tropical oceans. There remain, however, significant quantitative uncertainties in cloud forcing changes in the models as compared to observations. These differences are examined in relationship to model convection and cloud parameterizations Analysis of the possible sampling and measurement errors compared to systematic model errors is also presented.

Impact of lateral boundary conditions on regional analyses

NASA Astrophysics Data System (ADS)

Chikhar, Kamel; Gauthier, Pierre

2017-04-01

Regional and global climate models are usually validated by comparison to derived observations or reanalyses. Using a model in data assimilation results in a direct comparison to observations to produce its own analyses that may reveal systematic errors. In this study, regional analyses over North America are produced based on the fifth-generation Canadian Regional Climate Model (CRCM5) combined with the variational data assimilation system of the Meteorological Service of Canada (MSC). CRCM5 is driven at its boundaries by global analyses from ERA-interim or produced with the global configuration of the CRCM5. Assimilation cycles for the months of January and July 2011 revealed systematic errors in winter through large values in the mean analysis increments. This bias is attributed to the coupling of the lateral boundary conditions of the regional model with the driving data particularly over the northern boundary where a rapidly changing large scale circulation created significant cross-boundary flows. Increasing the time frequency of the lateral driving and applying a large-scale spectral nudging improved significantly the circulation through the lateral boundaries which translated in a much better agreement with observations.

Constraining the temperature history of the past millennium using early instrumental observations

NASA Astrophysics Data System (ADS)

Brohan, P.; Allan, R.; Freeman, E.; Wheeler, D.; Wilkinson, C.; Williamson, F.

2012-05-01

The current assessment that twentieth-century global temperature change is unusual in the context of the last thousand years relies on estimates of temperature changes from natural proxies (tree-rings, ice-cores etc.) and climate model simulations. Confidence in such estimates is limited by difficulties in calibrating the proxies and systematic differences between proxy reconstructions and model simulations. As the difference between the estimates extends into the relatively recent period of the early nineteenth century it is possible to compare them with a reliable instrumental estimate of the temperature change over that period, provided that enough early thermometer observations, covering a wide enough expanse of the world, can be collected. One organisation which systematically made observations and collected the results was the English East-India Company (EEIC), and their archives have been preserved in the British Library. Inspection of those archives revealed 900 log-books of EEIC ships containing daily instrumental measurements of temperature and pressure, and subjective estimates of wind speed and direction, from voyages across the Atlantic and Indian Oceans between 1789 and 1834. Those records have been extracted and digitised, providing 273 000 new weather records offering an unprecedentedly detailed view of the weather and climate of the late eighteenth and early nineteenth centuries. The new thermometer observations demonstrate that the large-scale temperature response to the Tambora eruption and the 1809 eruption was modest (perhaps 0.5 °C). This provides a powerful out-of-sample validation for the proxy reconstructions - supporting their use for longer-term climate reconstructions. However, some of the climate model simulations in the CMIP5 ensemble show much larger volcanic effects than this - such simulations are unlikely to be accurate in this respect.

Constraining the temperature history of the past millennium using early instrumental observations

NASA Astrophysics Data System (ADS)

Brohan, P.; Allan, R.; Freeman, E.; Wheeler, D.; Wilkinson, C.; Williamson, F.

2012-10-01

The current assessment that twentieth-century global temperature change is unusual in the context of the last thousand years relies on estimates of temperature changes from natural proxies (tree-rings, ice-cores, etc.) and climate model simulations. Confidence in such estimates is limited by difficulties in calibrating the proxies and systematic differences between proxy reconstructions and model simulations. As the difference between the estimates extends into the relatively recent period of the early nineteenth century it is possible to compare them with a reliable instrumental estimate of the temperature change over that period, provided that enough early thermometer observations, covering a wide enough expanse of the world, can be collected. One organisation which systematically made observations and collected the results was the English East India Company (EEIC), and their archives have been preserved in the British Library. Inspection of those archives revealed 900 log-books of EEIC ships containing daily instrumental measurements of temperature and pressure, and subjective estimates of wind speed and direction, from voyages across the Atlantic and Indian Oceans between 1789 and 1834. Those records have been extracted and digitised, providing 273 000 new weather records offering an unprecedentedly detailed view of the weather and climate of the late eighteenth and early nineteenth centuries. The new thermometer observations demonstrate that the large-scale temperature response to the Tambora eruption and the 1809 eruption was modest (perhaps 0.5 °C). This provides an out-of-sample validation for the proxy reconstructions - supporting their use for longer-term climate reconstructions. However, some of the climate model simulations in the CMIP5 ensemble show much larger volcanic effects than this - such simulations are unlikely to be accurate in this respect.

Transmissivity of the atmosphere above the Russian territory: observed climatic changes

NASA Astrophysics Data System (ADS)

Makhotkin, A. N.; Makhotkina, E. L.; Plakhina, I. N.

2018-01-01

We report the systematic investigation of spatial-temporal changes of integral and aerosol atmosphere turbidity above the territory of Russia in the period 1976-2016. The data referring both to the whole territory of Russia and some certain regions are discussed.

Two different regimes of anomalous walker circulation over the Indian and Pacific Oceans before and after the late 1970s

NASA Astrophysics Data System (ADS)

Kawamura, Ryuichi; Aruga, Hiromitsu; Matsuura, Tomonori; Iizuka, Satoshi

Using the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data aided by a coupled ocean-atmosphere model, we investigated two different regimes of anomalous Walker circulation system over the Pacific and Indian Oceans before and after a climate shift, which occurred in the late 1970s. During the period before the climate shift, an upper-level velocity potential anomaly systematically moves eastward from the tropical Indian Ocean to the warm pool region of the western Pacific during the growth phase of El Niño-Southern Oscillation (ENSO). In the meantime, the activities of South Asian and Australian summer monsoon systems are directly affected by the evolution of the anomalous Walker circulation. During the period after the climate shift, in contrast, an upperlevel velocity potential anomaly in the vicinity of the Philippine Sea and maritime continent is observed to expand westward into the northern Indian Ocean and South Asia during the decay phase of ENSO. This feature is identified with a major precursory signal of an anomalous South Asian summer monsoon in the preceding spring. The model captures a systematic eastward propagation similar to that observed prior to the late 1970s, but fails to reproduce the westward extension of the velocity potential anomaly observed to prevail after the late 1970s. The model results suggest that the cross-basin connection between the two oceans is a prerequisite for the turnabout of ENSO prior to the climate shift, in terms of the occurrence of westerly wind bursts.

Tuning a climate model using nudging to reanalysis.

NASA Astrophysics Data System (ADS)

Cheedela, S. K.; Mapes, B. E.

2014-12-01

Tuning a atmospheric general circulation model involves a daunting task of adjusting non-observable parameters to adjust the mean climate. These parameters arise from necessity to describe unresolved flow through parametrizations. Tuning a climate model is often done with certain set of priorities, such as global mean temperature, net top of the atmosphere radiation. These priorities are hard enough to reach let alone reducing systematic biases in the models. The goal of currently study is to explore alternate ways to tune a climate model to reduce some systematic biases that can be used in synergy with existing efforts. Nudging a climate model to a known state is a poor man's inverse of tuning process described above. Our approach involves nudging the atmospheric model to state of art reanalysis fields thereby providing a balanced state with respect to the global mean temperature and winds. The tendencies derived from nudging are negative of errors from physical parametrizations as the errors from dynamical core would be small. Patterns of nudging are compared to the patterns of different physical parametrizations to decipher the cause for certain biases in relation to tuning parameters. This approach might also help in understanding certain compensating errors that arise from tuning process. ECHAM6 is a comprehensive general model, also used in recent Coupled Model Intercomparision Project(CMIP5). The approach used to tune it and effect of certain parameters that effect its mean climate are reported clearly, hence it serves as a benchmark for our approach. Our planned experiments include nudging ECHAM6 atmospheric model to European Center Reanalysis (ERA-Interim) and reanalysis from National Center for Environmental Prediction (NCEP) and decipher choice of certain parameters that lead to systematic biases in its simulations. Of particular interest are reducing long standing biases related to simulation of Asian summer monsoon.

Drought Persistence Errors in Global Climate Models

NASA Astrophysics Data System (ADS)

Moon, H.; Gudmundsson, L.; Seneviratne, S. I.

2018-04-01

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.

TThe role of nitrogen availability in land-atmosphere interactions: a systematic evaluation of carbon-nitrogen coupling in a global land surface model using plot-level nitrogen fertilization experiments

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Goodale, C. L.; Bonan, G. B.; Mahowald, N. M.; Ricciuto, D. M.; Thornton, P. E.

2010-12-01

Recent research from global land surface models emphasizes the important role of nitrogen cycling on global climate, via its control on the terrestrial carbon balance. Despite the implications of nitrogen cycling on global climate predictions, the research community has not performed a systematic evaluation of nitrogen cycling in global models. Here, we present such an evaluation for one global land model, CLM-CN. In the evaluation we simulated 45 plot-scale nitrogen-fertilization experiments distributed across 33 temperate and boreal forest sites. Model predictions were evaluated against field observations by comparing the vegetation and soil carbon responses to the additional nitrogen. Aggregated across all experiments, the model predicted a larger vegetation carbon response and a smaller soil carbon response than observed; the responses partially offset each other, leading to a slightly larger total ecosystem carbon response than observed. However, the model-observation agreement improved for vegetation carbon when the sites with observed negative carbon responses to nitrogen were excluded, which may be because the model lacks mechanisms whereby nitrogen additions increase tree mortality. Among experiments, younger forests and boreal forests’ vegetation carbon responses were less than predicted and mature forests (> 40 years old) were greater than predicted. Specific to the CLM-CN, this study used a systematic evaluation to identify key areas to focus model development, especially soil carbon- nitrogen interactions and boreal forest nitrogen cycling. Applicable to the modeling community, this study demonstrates a standardized protocol for comparing carbon-nitrogen interactions among global land models.

Evaluation of climatic changes in South-Asia

NASA Astrophysics Data System (ADS)

Kjellstrom, Erik; Rana, Arun; Grigory, Nikulin; Renate, Wilcke; Hansson, Ulf; Kolax, Michael

2016-04-01

Literature has sufficient evidences of climate change impact all over the world and its impact on various sectors. In light of new advancements made in climate modeling, availability of several climate downscaling approaches, the more robust bias correction methods with varying complexities and strengths, in the present study we performed a systematic evaluation of climate change impact over South-Asia region. We have used different Regional Climate Models (RCMs) (from CORDEX domain), (Global Climate Models GCMs) and gridded observations for the study area to evaluate the models in historical/control period (1980-2010) and changes in future period (2010-2099). Firstly, GCMs and RCMs are evaluated against the Gridded observational datasets in the area using precipitation and temperature as indicative variables. Observational dataset are also evaluated against the reliable set of observational dataset, as pointed in literature. Bias, Correlation, and changes (among other statistical measures) are calculated for the entire region and both the variables. Eventually, the region was sub-divided into various smaller domains based on homogenous precipitation zones to evaluate the average changes over time period. Spatial and temporal changes for the region are then finally calculated to evaluate the future changes in the region. Future changes are calculated for 2 Representative Concentration Pathways (RCPs), the middle emission (RCP4.5) and high emission (RCP8.5) and for both climatic variables, precipitation and temperature. Lastly, Evaluation of Extremes is performed based on precipitation and temperature based indices for whole region in future dataset. Results have indicated that the whole study region is under extreme stress in future climate scenarios for both climatic variables i.e. precipitation and temperature. Precipitation variability is dependent on the location in the area leading to droughts and floods in various regions in future. Temperature is hinting towards a constant increase throughout the region regardless of location.

Developing quantitative criteria to evaluate AOGCMs for application to regional climate assessments

NASA Astrophysics Data System (ADS)

Hayhoe, K.; Wake, C.; Bradbury, J.; Degaetano, A.; Hertel, A.

2006-12-01

Climate projections are the foundation for regional assessments of potential climate impacts. However, the soundness of regional assessments depends on the ability of global climate models to reproduce key processes responsible for regional climate trends. Here, we develop a systematic method to compare observed climate with historical atmosphere-ocean general circulation model (AOGCM) simulations, to assess the degree to which AOGCMs are able to reproduce regional circulation patterns. Applying this methodology to the U.S. Northeast (NE), we find that nearly all AOGCMs simulate a reasonable winter NAO pattern and seasonal positions of the Jet Stream and the East Coast Trough. However, not all models capture observed correlations between these circulation patterns and seasonal climate anomalies in the NE. Using only those AOGCMs that meet the criteria in each of these areas, we then develop projections of future climate change in the NE. The primary changes projected to occur over the next century - slightly greater temperature increases in summer than winter, and increases in winter precipitation - are consistent with projected trends in regional climate processes and are relatively independent of model or scale. These suggest confidence in the direction and potential range of the most notable regional climate trends, with the absolute magnitude of change depending on both the sensitivity of the climate system to human forcing as well as on human emissions over coming decades.

SAM-CAAM: A Concept for Acquiring Systematic Aircraft Measurements to Characterize Aerosol Air Masses.

PubMed

Kahn, Ralph A; Berkoff, Tim A; Brock, Charles; Chen, Gao; Ferrare, Richard A; Ghan, Steven; Hansico, Thomas F; Hegg, Dean A; Martins, J Vanderlei; McNaughton, Cameron S; Murphy, Daniel M; Ogren, John A; Penner, Joyce E; Pilewskie, Peter; Seinfeld, John H; Worsnop, Douglas R

2017-10-01

A modest operational program of systematic aircraft measurements can resolve key satellite-aerosol-data-record limitations. Satellite observations provide frequent, global aerosol-amount maps, but offer only loose aerosol property constraints needed for climate and air quality applications. We define and illustrate the feasibility of flying an aircraft payload to measure key aerosol optical, microphysical, and chemical properties in situ . The flight program could characterize major aerosol air-mass types statistically, at a level-of-detail unobtainable from space. It would: (1) enhance satellite aerosol retrieval products with better climatology assumptions, and (2) improve translation between satellite-retrieved optical properties and species-specific aerosol mass and size simulated in climate models to assess aerosol forcing, its anthropogenic components, and other environmental impacts. As such, Systematic Aircraft Measurements to Characterize Aerosol Air Masses (SAM-CAAM) could add value to data records representing several decades of aerosol observations from space, improve aerosol constraints on climate modeling , help interrelate remote-sensing, in situ, and modeling aerosol-type definitions , and contribute to future satellite aerosol missions. Fifteen Required Variables are identified, and four Payload Options of increasing ambition are defined, to constrain these quantities. "Option C" could meet all the SAM-CAAM objectives with about 20 instruments, most of which have flown before, but never routinely several times per week, and never as a group. Aircraft integration, and approaches to data handling, payload support, and logistical considerations for a long-term, operational mission are discussed. SAM-CAAM is feasible because, for most aerosol sources and specified seasons, particle properties tend to be repeatable , even if aerosol loading varies.

Tuning the climate sensitivity of a global model to match 20th Century warming

NASA Astrophysics Data System (ADS)

Mauritsen, T.; Roeckner, E.

2015-12-01

A climate models ability to reproduce observed historical warming is sometimes viewed as a measure of quality. Yet, for practical reasons historical warming cannot be considered a purely empirical result of the modelling efforts because the desired result is known in advance and so is a potential target of tuning. Here we explain how the latest edition of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2) atmospheric model (ECHAM6.3) had its climate sensitivity systematically tuned to about 3 K; the MPI model to be used during CMIP6. This was deliberately done in order to improve the match to observed 20th Century warming over the previous model generation (MPI-ESM, ECHAM6.1) which warmed too much and had a sensitivity of 3.5 K. In the process we identified several controls on model cloud feedback that confirm recently proposed hypotheses concerning trade-wind cumulus and high-latitude mixed-phase clouds. We then evaluate the model fidelity with centennial global warming and discuss the relative importance of climate sensitivity, forcing and ocean heat uptake efficiency in determining the response as well as possible systematic biases. The activity of targeting historical warming during model development is polarizing the modeling community with 35 percent of modelers stating that 20th Century warming was rated very important to decisive, whereas 30 percent would not consider it at all. Likewise, opinions diverge as to which measures are legitimate means for improving the model match to observed warming. These results are from a survey conducted in conjunction with the first WCRP Workshop on Model Tuning in fall 2014 answered by 23 modelers. We argue that tuning or constructing models to match observed warming to some extent is practically unavoidable, and as such, in many cases might as well be done explicitly. For modeling groups that have the capability to tune both their aerosol forcing and climate sensitivity there is now a unique opportunity to explore the bounds of our understanding - a low sensitivity model could be sustained by weak aerosol forcing, and a highly sensitive model could potentially be constructed to match observed warming by strong compensating aerosol cooling. This next natural step could constitute a new paradigm in climate modeling.

Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands.

PubMed

Lee, Se-Yeun; Ryan, Maureen E; Hamlet, Alan F; Palen, Wendy J; Lawler, Joshua J; Halabisky, Meghan

2015-01-01

Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types. Here, we develop and demonstrate a new method for projecting climate-induced hydrologic changes in montane wetlands. Using observed wetland water levels and soil moisture simulated by the physically based Variable Infiltration Capacity (VIC) hydrologic model, we developed site-specific regression models relating soil moisture to observed wetland water levels to simulate the hydrologic behavior of four types of montane wetlands (ephemeral, intermediate, perennial, permanent wetlands) in the U. S. Pacific Northwest. The hybrid models captured observed wetland dynamics in many cases, though were less robust in others. We then used these models to a) hindcast historical wetland behavior in response to observed climate variability (1916-2010 or later) and classify wetland types, and b) project the impacts of climate change on montane wetlands using global climate model scenarios for the 2040s and 2080s (A1B emissions scenario). These future projections show that climate-induced changes to key driving variables (reduced snowpack, higher evapotranspiration, extended summer drought) will result in earlier and faster drawdown in Pacific Northwest montane wetlands, leading to systematic reductions in water levels, shortened wetland hydroperiods, and increased probability of drying. Intermediate hydroperiod wetlands are projected to experience the greatest changes. For the 2080s scenario, widespread conversion of intermediate wetlands to fast-drying ephemeral wetlands will likely reduce wetland habitat availability for many species.

Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands

PubMed Central

Hamlet, Alan F.; Palen, Wendy J.; Lawler, Joshua J.; Halabisky, Meghan

2015-01-01

Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types. Here, we develop and demonstrate a new method for projecting climate-induced hydrologic changes in montane wetlands. Using observed wetland water levels and soil moisture simulated by the physically based Variable Infiltration Capacity (VIC) hydrologic model, we developed site-specific regression models relating soil moisture to observed wetland water levels to simulate the hydrologic behavior of four types of montane wetlands (ephemeral, intermediate, perennial, permanent wetlands) in the U. S. Pacific Northwest. The hybrid models captured observed wetland dynamics in many cases, though were less robust in others. We then used these models to a) hindcast historical wetland behavior in response to observed climate variability (1916–2010 or later) and classify wetland types, and b) project the impacts of climate change on montane wetlands using global climate model scenarios for the 2040s and 2080s (A1B emissions scenario). These future projections show that climate-induced changes to key driving variables (reduced snowpack, higher evapotranspiration, extended summer drought) will result in earlier and faster drawdown in Pacific Northwest montane wetlands, leading to systematic reductions in water levels, shortened wetland hydroperiods, and increased probability of drying. Intermediate hydroperiod wetlands are projected to experience the greatest changes. For the 2080s scenario, widespread conversion of intermediate wetlands to fast-drying ephemeral wetlands will likely reduce wetland habitat availability for many species. PMID:26331850

Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions

USGS Publications Warehouse

Jackson, Stephen T.; Betancourt, Julio L.; Booth, Robert K.; Gray, Stephen T.

2009-01-01

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions

USGS Publications Warehouse

Jackson, S.T.; Betancourt, J.L.; Booth, R.K.; Gray, S.T.

2009-01-01

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and morefundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions

PubMed Central

Jackson, Stephen T.; Betancourt, Julio L.; Booth, Robert K.; Gray, Stephen T.

2009-01-01

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics. PMID:19805104

Physical and Social-Motivational Contextual Correlates of Youth Physical Activity in Underresourced Afterschool Programs.

PubMed

Zarrett, Nicole; Sorensen, Carl; Cook, Brittany Skiles

2015-08-01

Afterschool programs (ASPs) have become increasingly recognized as a key context to support youth daily physical activity (PA) accrual. The purpose of the present study was to assess the physical and social-motivational climate characteristics of ASPs associated with youth PA, and variations in contextual correlates of PA by youth sex. Systematic observations of 7 ASPs serving underserved youth (minority, low income) was conducted using the System for Observing Play and Leisure Activity in Youth and a social-motivational climate observation tool founded on self-determination theory. For five program days at each site, teams of two coders conducted continuous observations of youth PA (sedentary, moderate, vigorous), five physical features (e.g., equipment availability), eight staff interactions (e.g., encourage PA), and seven motivational climate components (e.g., inclusive). Aligned with previous research, regressions controlling for variations by site indicated that organized PA, provision of portable equipment, and staff PA participation and supervision are key correlates of youth PA. Moreover, as the first study to systematically observe motivational-context characteristics of ASPs, we identified several key modifiable motivational features that are necessary to address in order to increase youth engagement in PA during the out-of-school hours. Among motivational features assessed, "relatedness" components (positive peer relations, inclusive/cooperative activities) were primary correlates of girls' PA. In contrast, all three motivational features specified by self-determination theory (support for autonomy, mastery/competence, and inclusion/relatedness) were correlated with boys' PA. Findings are discussed in terms of policy and practice for understanding strengths and needs of ASPs to effectively engage youth in PA. © 2015 Society for Public Health Education.

Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

NASA Astrophysics Data System (ADS)

Schwarz, Jakob; Kirchengast, Gottfried; Schwaerz, Marc

2018-05-01

Global Navigation Satellite System (GNSS) radio occultation (RO) observations are highly accurate, long-term stable data sets and are globally available as a continuous record from 2001. Essential climate variables for the thermodynamic state of the free atmosphere - such as pressure, temperature, and tropospheric water vapor profiles (involving background information) - can be derived from these records, which therefore have the potential to serve as climate benchmark data. However, to exploit this potential, atmospheric profile retrievals need to be very accurate and the remaining uncertainties quantified and traced throughout the retrieval chain from raw observations to essential climate variables. The new Reference Occultation Processing System (rOPS) at the Wegener Center aims to deliver such an accurate RO retrieval chain with integrated uncertainty propagation. Here we introduce and demonstrate the algorithms implemented in the rOPS for uncertainty propagation from excess phase to atmospheric bending angle profiles, for estimated systematic and random uncertainties, including vertical error correlations and resolution estimates. We estimated systematic uncertainty profiles with the same operators as used for the basic state profiles retrieval. The random uncertainty is traced through covariance propagation and validated using Monte Carlo ensemble methods. The algorithm performance is demonstrated using test day ensembles of simulated data as well as real RO event data from the satellite missions CHAllenging Minisatellite Payload (CHAMP); Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC); and Meteorological Operational Satellite A (MetOp). The results of the Monte Carlo validation show that our covariance propagation delivers correct uncertainty quantification from excess phase to bending angle profiles. The results from the real RO event ensembles demonstrate that the new uncertainty estimation chain performs robustly. Together with the other parts of the rOPS processing chain this part is thus ready to provide integrated uncertainty propagation through the whole RO retrieval chain for the benefit of climate monitoring and other applications.

Is it feasible to estimate radiosonde biases from interlaced measurements?

NASA Astrophysics Data System (ADS)

Kremser, Stefanie; Tradowsky, Jordis S.; Rust, Henning W.; Bodeker, Greg E.

2018-05-01

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.

A Systematic Error Correction Method for TOVS Radiances

NASA Technical Reports Server (NTRS)

Joiner, Joanna; Rokke, Laurie; Einaudi, Franco (Technical Monitor)

2000-01-01

Treatment of systematic errors is crucial for the successful use of satellite data in a data assimilation system. Systematic errors in TOVS radiance measurements and radiative transfer calculations can be as large or larger than random instrument errors. The usual assumption in data assimilation is that observational errors are unbiased. If biases are not effectively removed prior to assimilation, the impact of satellite data will be lessened and can even be detrimental. Treatment of systematic errors is important for short-term forecast skill as well as the creation of climate data sets. A systematic error correction algorithm has been developed as part of a 1D radiance assimilation. This scheme corrects for spectroscopic errors, errors in the instrument response function, and other biases in the forward radiance calculation for TOVS. Such algorithms are often referred to as tuning of the radiances. The scheme is able to account for the complex, air-mass dependent biases that are seen in the differences between TOVS radiance observations and forward model calculations. We will show results of systematic error correction applied to the NOAA 15 Advanced TOVS as well as its predecessors. We will also discuss the ramifications of inter-instrument bias with a focus on stratospheric measurements.

Climate model biases in seasonality of continental water storage revealed by satellite gravimetry

USGS Publications Warehouse

Swenson, Sean; Milly, P.C.D.

2006-01-01

Satellite gravimetric observations of monthly changes in continental water storage are compared with outputs from five climate models. All models qualitatively reproduce the global pattern of annual storage amplitude, and the seasonal cycle of global average storage is reproduced well, consistent with earlier studies. However, global average agreements mask systematic model biases in low latitudes. Seasonal extrema of low‐latitude, hemispheric storage generally occur too early in the models, and model‐specific errors in amplitude of the low‐latitude annual variations are substantial. These errors are potentially explicable in terms of neglected or suboptimally parameterized water stores in the land models and precipitation biases in the climate models.

SAM-CAAM: A Concept for Acquiring Systematic Aircraft Measurements to Characterize Aerosol Air Masses

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

Kahn, Ralph A.; Berkoff, Tim A.; Brock, Charles

A modest operational program of systematic aircraft measurements can resolve key satellite aerosol data record limitations. Satellite observations provide frequent global aerosol amount maps but offer only loose aerosol property constraints needed for climate and air quality applications. In this paper, we define and illustrate the feasibility of flying an aircraft payload to measure key aerosol optical, microphysical, and chemical properties in situ. The flight program could characterize major aerosol airmass types statistically, at a level of detail unobtainable from space. It would 1) enhance satellite aerosol retrieval products with better climatology assumptions and 2) improve translation between satellite-retrieved opticalmore » properties and species-specific aerosol mass and size simulated in climate models to assess aerosol forcing, its anthropogenic components, and other environmental impacts. As such, Systematic Aircraft Measurements to Characterize Aerosol Air Masses (SAM-CAAM) could add value to data records representing several decades of aerosol observations from space; improve aerosol constraints on climate modeling; help interrelate remote sensing, in situ, and modeling aerosol-type definitions; and contribute to future satellite aerosol missions. Fifteen required variables are identified and four payload options of increasing ambition are defined to constrain these quantities. “Option C” could meet all the SAM-CAAM objectives with about 20 instruments, most of which have flown before, but never routinely several times per week, and never as a group. Aircraft integration and approaches to data handling, payload support, and logistical considerations for a long-term, operational mission are discussed. Finally, SAM-CAAM is feasible because, for most aerosol sources and specified seasons, particle properties tend to be repeatable, even if aerosol loading varies.« less

SAM-CAAM: A Concept for Acquiring Systematic Aircraft Measurements to Characterize Aerosol Air Masses

DOE PAGES

Kahn, Ralph A.; Berkoff, Tim A.; Brock, Charles; ...

2017-10-30

A modest operational program of systematic aircraft measurements can resolve key satellite aerosol data record limitations. Satellite observations provide frequent global aerosol amount maps but offer only loose aerosol property constraints needed for climate and air quality applications. In this paper, we define and illustrate the feasibility of flying an aircraft payload to measure key aerosol optical, microphysical, and chemical properties in situ. The flight program could characterize major aerosol airmass types statistically, at a level of detail unobtainable from space. It would 1) enhance satellite aerosol retrieval products with better climatology assumptions and 2) improve translation between satellite-retrieved opticalmore » properties and species-specific aerosol mass and size simulated in climate models to assess aerosol forcing, its anthropogenic components, and other environmental impacts. As such, Systematic Aircraft Measurements to Characterize Aerosol Air Masses (SAM-CAAM) could add value to data records representing several decades of aerosol observations from space; improve aerosol constraints on climate modeling; help interrelate remote sensing, in situ, and modeling aerosol-type definitions; and contribute to future satellite aerosol missions. Fifteen required variables are identified and four payload options of increasing ambition are defined to constrain these quantities. “Option C” could meet all the SAM-CAAM objectives with about 20 instruments, most of which have flown before, but never routinely several times per week, and never as a group. Aircraft integration and approaches to data handling, payload support, and logistical considerations for a long-term, operational mission are discussed. Finally, SAM-CAAM is feasible because, for most aerosol sources and specified seasons, particle properties tend to be repeatable, even if aerosol loading varies.« less

Constraining the temperature history of the past millennium using early instrumental observations

NASA Astrophysics Data System (ADS)

Brohan, P.

2012-12-01

The current assessment that twentieth-century global temperature change is unusual in the context of the last thousand years relies on estimates of temperature changes from natural proxies (tree-rings, ice-cores etc.) and climate model simulations. Confidence in such estimates is limited by difficulties in calibrating the proxies and systematic differences between proxy reconstructions and model simulations - notable differences include large differences in multi-decadal variability between proxy reconstructions, and big uncertainties in the effect of volcanic eruptions. Because the difference between the estimates extends into the relatively recent period of the early nineteenth century it is possible to compare them with a reliable instrumental estimate of the temperature change over that period, provided that enough early thermometer observations, covering a wide enough expanse of the world, can be collected. By constraining key aspects of the reconstructions and simulations, instrumental observations, inevitably from a limited period, can reduce reconstruction uncertainty throughout the millennium. A considerable quantity of early instrumental observations are preserved in the world's archives. One organisation which systematically made observations and collected the results was the English East-India Company (EEIC), and 900 log-books of EEIC ships containing daily instrumental measurements of temperature and pressure have been preserved in the British Library. Similar records from voyages of exploration and scientific investigation are preserved in published literature and the records in National Archives. Some of these records have been extracted and digitised, providing hundreds of thousands of new weather records offering an unprecedentedly detailed view of the weather and climate of the late eighteenth and early nineteenth centuries. The new thermometer observations demonstrate that the large-scale temperature response to the Tambora eruption and the 1809 eruption was modest (perhaps 0.5C). This provides a powerful out-of-sample validation for the proxy reconstructions --- supporting their use for longer-term climate reconstructions. However, some of the climate model simulations in the CMIP5 ensemble show much larger volcanic effects than this --- such simulations are unlikely to be accurate in this respect.

Defining the external implementation context: an integrative systematic literature review.

PubMed

Watson, Dennis P; Adams, Erin L; Shue, Sarah; Coates, Heather; McGuire, Alan; Chesher, Jeremy; Jackson, Joanna; Omenka, Ogbonnaya I

2018-03-27

Proper implementation of evidence-based interventions is necessary for their full impact to be realized. However, the majority of research to date has overlooked facilitators and barriers existing outside the boundaries of the implementing organization(s). Better understanding and measurement of the external implementation context would be particularly beneficial in light of complex health interventions that extend into and interact with the larger environment they are embedded within. We conducted a integrative systematic literature review to identify external context constructs likely to impact implementation of complex evidence-based interventions. The review process was iterative due to our goal to inductively develop the identified constructs. Data collection occurred in four primary stages: (1) an initial set of key literature across disciplines was identified and used to inform (2) journal and (3) author searches that, in turn, informed the design of the final (4) database search. Additionally, (5) we conducted citation searches of relevant literature reviews identified in each stage. We carried out an inductive thematic content analysis with the goal of developing homogenous, well-defined, and mutually exclusive categories. We identified eight external context constructs: (1) professional influences, (2) political support, (3) social climate, (4) local infrastructure, (5) policy and legal climate, (6) relational climate, (7) target population, and (8) funding and economic climate. This is the first study to our knowledge to use a systematic review process to identify empirically observed external context factors documented to impact implementation. Comparison with four widely-utilized implementation frameworks supports the exhaustiveness of our review process. Future work should focus on the development of more stringent operationalization and measurement of these external constructs.

Monitoring and projecting snow on Hawaii Island

NASA Astrophysics Data System (ADS)

Zhang, Chunxi; Hamilton, Kevin; Wang, Yuqing

2017-05-01

The highest mountain peaks on Hawaii Island are snow covered for part of almost every year. This snow has aesthetic and recreational value as well as cultural significance for residents and visitors. Thus far there have been almost no systematic observations of snowfall, snow cover, or snow depth in Hawaii. Here we use satellite observations to construct a daily index of Hawaii Island snow cover starting from 2000. The seasonal mean of our index displays large interannual variations that are correlated with the seasonal mean freezing level and frequency of trade wind inversions as determined from nearby balloon soundings. Our snow cover index provides a diagnostic for monitoring climate variability and trends within the extensive area of the globe dominated by the North Pacific trade wind meteorological regime. We have also conducted simulations of the Hawaii climate with a regional atmospheric model. Retrospective simulations for 1990-2015 were run with boundary conditions prescribed from gridded observational analyses. Simulations for the end of 21st century employed boundary conditions based on global climate model projections that included standard scenarios for anticipated anthropogenic climate forcing. The future projections indicate that snowfall will nearly disappear by the end of the current century.

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations

NASA Astrophysics Data System (ADS)

Schneider, Tapio; Lan, Shiwei; Stuart, Andrew; Teixeira, João.

2017-12-01

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.

Teaching the relationship between health and climate change: a systematic scoping review protocol.

PubMed

Osama, Tasnime; Brindley, David; Majeed, Azeem; Murray, Kris A; Shah, Hiral; Toumazos, Mel; Van Velthoven, Michelle; Car, Josip; Wells, Glenn; Meinert, Edward

2018-05-20

The observed and projected impacts of climate change on human health are significant. While climate change has gathered global momentum and is taught frequently, the extent to which the relationships between climate change and health are taught remains uncertain. Education provides an opportunity to create public engagement on these issues, but the extent to which historical implementation of climate health education could be leveraged is not well understood. To address this gap, we propose to conduct a scoping review of all forms of teaching that have been used to illustrate the health effects of climate change between 2005 and 2017, coinciding with a turning point in the public health and climate change agendas following the 2005 Group of 7/8 (G7/8) Summit. Using Arksey/O'Malley's and Levac's methodological framework, MEDLINE/PubMed, Embase, Scopus, Education Resource Information Centre, Web of Science, Global Health, Health Management Information Consortium, Georef, Ebsco and PROSPERO will be systematically searched. Predetermined inclusion and exclusion criteria will be applied by two independent reviewers to determine study eligibility. Studies published in English and after 2005 only will be examined. Following selection of studies, data will be extracted and analysed. No ethical approval is required as exclusively secondary data will be used. Our findings will be communicated to the European Institute of Innovation & Technology Health-Knowledge and Innovation Communities to assist in the development of a FutureLearn Massive Open Online Course on the health effects of climate change. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Structural uncertainty of downscaled climate model output in a difficult-to-resolve environment: data sparseness and parameterization error contribution to statistical and dynamical downscaling output in the U.S. Caribbean region

NASA Astrophysics Data System (ADS)

Terando, A. J.; Grade, S.; Bowden, J.; Henareh Khalyani, A.; Wootten, A.; Misra, V.; Collazo, J.; Gould, W. A.; Boyles, R.

2016-12-01

Sub-tropical island nations may be particularly vulnerable to anthropogenic climate change because of predicted changes in the hydrologic cycle that would lead to significant drying in the future. However, decision makers in these regions have seen their adaptation planning efforts frustrated by the lack of island-resolving climate model information. Recently, two investigations have used statistical and dynamical downscaling techniques to develop climate change projections for the U.S. Caribbean region (Puerto Rico and U.S. Virgin Islands). We compare the results from these two studies with respect to three commonly downscaled CMIP5 global climate models (GCMs). The GCMs were dynamically downscaled at a convective-permitting scale using two different regional climate models. The statistical downscaling approach was conducted at locations with long-term climate observations and then further post-processed using climatologically aided interpolation (yielding two sets of projections). Overall, both approaches face unique challenges. The statistical approach suffers from a lack of observations necessary to constrain the model, particularly at the land-ocean boundary and in complex terrain. The dynamically downscaled model output has a systematic dry bias over the island despite ample availability of moisture in the atmospheric column. Notwithstanding these differences, both approaches are consistent in projecting a drier climate that is driven by the strong global-scale anthropogenic forcing.

A global database with parallel measurements to study non-climatic changes

NASA Astrophysics Data System (ADS)

Venema, Victor; Auchman, Renate; Aguilar, Enric

2017-04-01

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.

NOAA's Scientific Data Stewardship Program

NASA Astrophysics Data System (ADS)

Bates, J. J.

2004-12-01

The NOAA mission is to understand and predict changes in the Earth's environment and conserve and manage coastal and marine resources to meet the Nation's economic, social and environmental needs. NOAA has responsibility for long-term archiving of the United States environmental data and has recently integrated several data management functions into a concept called Scientific Data Stewardship. Scientific Data Stewardship a new paradigm in data management consisting of an integrated suite of functions to preserve and exploit the full scientific value of NOAA's, and the world's, environmental data These functions include careful monitoring of observing system performance for long-term applications, the generation of authoritative long-term climate records from multiple observing platforms, and the proper archival of and timely access to data and metadata. NOAA has developed a conceptual framework to implement the functions of scientific data stewardship. This framework has five objectives: 1) develop real-time monitoring of all satellite observing systems for climate applications, 2) process large volumes of satellite data extending up to decades in length to account for systematic errors and to eliminate artifacts in the raw data (referred to as fundamental climate data records, FCDRs), 3) generate retrieved geophysical parameters from the FCDRs (referred to as thematic climate data records TCDRs) including combining observations from all sources, 4) conduct monitoring and research by analyzing data sets to uncover climate trends and to provide evaluation and feedback for steps 2) and 3), and 5) provide archives of metadata, FCDRs, and TCDRs, and facilitate distribution of these data to the user community. The term `climate data record' and related terms, such as climate data set, have been used for some time, but the climate community has yet to settle on a concensus definition. A recent United States National Academy of Sciences report recommends using the following definition: a climate data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change.

Links between media communication and local perceptions of climate change in an indigenous society

PubMed Central

Fernández-Llamazares, Álvaro; Méndez-López, María Elena; Díaz-Reviriego, Isabel; McBride, Marissa F.; Pyhälä, Aili; Rosell-Melé, Antoni; Reyes-García, Victoria

2015-01-01

Indigenous societies hold a great deal of ethnoclimatological knowledge that could potentially be of key importance for both climate change science and local adaptation; yet, we lack studies examining how such knowledge might be shaped by media communication. This study systematically investigates the interplay between local observations of climate change and the reception of media information amongst the Tsimane’, an indigenous society of Bolivian Amazonia where the scientific discourse of anthropogenic climate change has barely reached. Specifically, we conducted a Randomized Evaluation with a sample of 424 household heads in 12 villages to test to what degree local accounts of climate change are influenced by externally influenced awareness. We randomly assigned villages to a treatment and control group, conducted workshops on climate change with villages in the treatment group, and evaluated the effects of information dissemination on individual climate change perceptions. Results of this work suggest that providing climate change information through participatory workshops does not noticeably influence individual perceptions of climate change. Such findings stress the challenges involved in translating between local and scientific framings of climate change, and gives cause for concern about how to integrate indigenous peoples and local knowledge with global climate change policy debates. PMID:26166919

Links between media communication and local perceptions of climate change in an indigenous society.

PubMed

Fernández-Llamazares, Álvaro; Méndez-López, María Elena; Díaz-Reviriego, Isabel; McBride, Marissa F; Pyhälä, Aili; Rosell-Melé, Antoni; Reyes-García, Victoria

2015-07-01

Indigenous societies hold a great deal of ethnoclimatological knowledge that could potentially be of key importance for both climate change science and local adaptation; yet, we lack studies examining how such knowledge might be shaped by media communication. This study systematically investigates the interplay between local observations of climate change and the reception of media information amongst the Tsimane', an indigenous society of Bolivian Amazonia where the scientific discourse of anthropogenic climate change has barely reached. Specifically, we conducted a Randomized Evaluation with a sample of 424 household heads in 12 villages to test to what degree local accounts of climate change are influenced by externally influenced awareness. We randomly assigned villages to a treatment and control group, conducted workshops on climate change with villages in the treatment group, and evaluated the effects of information dissemination on individual climate change perceptions. Results of this work suggest that providing climate change information through participatory workshops does not noticeably influence individual perceptions of climate change. Such findings stress the challenges involved in translating between local and scientific framings of climate change, and gives cause for concern about how to integrate indigenous peoples and local knowledge with global climate change policy debates.

NCLB: Local Implementation and Impact in Southwest Washington State

ERIC Educational Resources Information Center

Mabry, Linda; Margolis, Jason

2006-01-01

The research reported here is from the first two years of an ongoing and largely qualitative study to examine the impact of the No Child Left Behind federal education policy on educational practice and climate in elementary schools in two districts in southwest Washington. Based on systematic drop-in observations in classrooms and interviews with…

Atmospheric Water Balance and Variability in the MERRA-2 Reanalysis

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Robertson, Franklin R.; Takacs, Lawrence; Molod, Andrea; Mocko, David

2017-01-01

Closing and balancing Earths global water cycle remains a challenge for the climate community. Observations are limited in duration, global coverage, and frequency, and not all water cycle terms are adequately observed. Reanalyses aim to fill the gaps through the assimilation of as many atmospheric water vapor observations as possible. Former generations of reanalyses have demonstrated a number of systematic problems that have limited their use in climate studies, especially regarding low-frequency trends. This study characterizes the NASA Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) water cycle relative to contemporary reanalyses and observations. MERRA-2 includes measures intended to minimize the spurious global variations related to in homogeneity in the observational record. The global balance and cycling of water from ocean to land is presented, with special attention given to the water vapor analysis increment and the effects of the changing observing system. While some systematic regional biases can be identified,MERRA-2 produces temporally consistent time series of total column water and transport of water from ocean to land. However, the interannual variability of ocean evaporation is affected by the changing surface-wind-observing system, and precipitation variability is closely related to the evaporation. The surface energy budget is also strongly influenced by the interannual variability of the ocean evaporation. Furthermore, evaluating the relationship of temperature and water vapor indicates that the variations of water vapor with temperature are weaker in satellite data reanalyses, not just MERRA-2, than determined by observations, atmospheric models, or reanalyses without water vapor assimilation.

A new climate dataset for systematic assessments of climate change impacts as a function of global warming

NASA Astrophysics Data System (ADS)

Heinke, J.; Ostberg, S.; Schaphoff, S.; Frieler, K.; Müller, C.; Gerten, D.; Meinshausen, M.; Lucht, W.

2013-10-01

In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere-Ocean General Circulation Models (AOGCMs). The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilise a simplified relationships between ΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

Unraveling multiple changes in complex climate time series using Bayesian inference

NASA Astrophysics Data System (ADS)

Berner, Nadine; Trauth, Martin H.; Holschneider, Matthias

2016-04-01

Change points in time series are perceived as heterogeneities in the statistical or dynamical characteristics of observations. Unraveling such transitions yields essential information for the understanding of the observed system. The precise detection and basic characterization of underlying changes is therefore of particular importance in environmental sciences. We present a kernel-based Bayesian inference approach to investigate direct as well as indirect climate observations for multiple generic transition events. In order to develop a diagnostic approach designed to capture a variety of natural processes, the basic statistical features of central tendency and dispersion are used to locally approximate a complex time series by a generic transition model. A Bayesian inversion approach is developed to robustly infer on the location and the generic patterns of such a transition. To systematically investigate time series for multiple changes occurring at different temporal scales, the Bayesian inversion is extended to a kernel-based inference approach. By introducing basic kernel measures, the kernel inference results are composed into a proxy probability to a posterior distribution of multiple transitions. Thus, based on a generic transition model a probability expression is derived that is capable to indicate multiple changes within a complex time series. We discuss the method's performance by investigating direct and indirect climate observations. The approach is applied to environmental time series (about 100 a), from the weather station in Tuscaloosa, Alabama, and confirms documented instrumentation changes. Moreover, the approach is used to investigate a set of complex terrigenous dust records from the ODP sites 659, 721/722 and 967 interpreted as climate indicators of the African region of the Plio-Pleistocene period (about 5 Ma). The detailed inference unravels multiple transitions underlying the indirect climate observations coinciding with established global climate events.

Quantifying the influence of global warming on unprecedented extreme climate events

PubMed Central

Singh, Deepti; Horton, Daniel E.; Swain, Daniel L.; Touma, Danielle; Charland, Allison; Liu, Yunjie; Haugen, Matz; Tsiang, Michael; Rajaratnam, Bala

2017-01-01

Efforts to understand the influence of historical global warming on individual extreme climate events have increased over the past decade. However, despite substantial progress, events that are unprecedented in the local observational record remain a persistent challenge. Leveraging observations and a large climate model ensemble, we quantify uncertainty in the influence of global warming on the severity and probability of the historically hottest month, hottest day, driest year, and wettest 5-d period for different areas of the globe. We find that historical warming has increased the severity and probability of the hottest month and hottest day of the year at >80% of the available observational area. Our framework also suggests that the historical climate forcing has increased the probability of the driest year and wettest 5-d period at 57% and 41% of the observed area, respectively, although we note important caveats. For the most protracted hot and dry events, the strongest and most widespread contributions of anthropogenic climate forcing occur in the tropics, including increases in probability of at least a factor of 4 for the hottest month and at least a factor of 2 for the driest year. We also demonstrate the ability of our framework to systematically evaluate the role of dynamic and thermodynamic factors such as atmospheric circulation patterns and atmospheric water vapor, and find extremely high statistical confidence that anthropogenic forcing increased the probability of record-low Arctic sea ice extent. PMID:28439005

Quantifying the influence of global warming on unprecedented extreme climate events.

PubMed

Diffenbaugh, Noah S; Singh, Deepti; Mankin, Justin S; Horton, Daniel E; Swain, Daniel L; Touma, Danielle; Charland, Allison; Liu, Yunjie; Haugen, Matz; Tsiang, Michael; Rajaratnam, Bala

2017-05-09

Efforts to understand the influence of historical global warming on individual extreme climate events have increased over the past decade. However, despite substantial progress, events that are unprecedented in the local observational record remain a persistent challenge. Leveraging observations and a large climate model ensemble, we quantify uncertainty in the influence of global warming on the severity and probability of the historically hottest month, hottest day, driest year, and wettest 5-d period for different areas of the globe. We find that historical warming has increased the severity and probability of the hottest month and hottest day of the year at >80% of the available observational area. Our framework also suggests that the historical climate forcing has increased the probability of the driest year and wettest 5-d period at 57% and 41% of the observed area, respectively, although we note important caveats. For the most protracted hot and dry events, the strongest and most widespread contributions of anthropogenic climate forcing occur in the tropics, including increases in probability of at least a factor of 4 for the hottest month and at least a factor of 2 for the driest year. We also demonstrate the ability of our framework to systematically evaluate the role of dynamic and thermodynamic factors such as atmospheric circulation patterns and atmospheric water vapor, and find extremely high statistical confidence that anthropogenic forcing increased the probability of record-low Arctic sea ice extent.

Quantifying the Influence of Global Warming on Unprecedented Extreme Climate Events

NASA Technical Reports Server (NTRS)

Diffenbaugh, Noah S.; Singh, Deepti; Mankin, Justin S.; Horton, Daniel E.; Swain, Daniel L.; Touma, Danielle; Charland, Allison; Liu, Yunjie; Haugen, Matz; Tsiang, Michael;

Incorporating climate change into systematic conservation planning

USGS Publications Warehouse

Groves, Craig R.; Game, Edward T.; Anderson, Mark G.; Cross, Molly; Enquist, Carolyn; Ferdana, Zach; Girvetz, Evan; Gondor, Anne; Hall, Kimberly R.; Higgins, Jonathan; Marshall, Rob; Popper, Ken; Schill, Steve; Shafer, Sarah L.

2012-01-01

The principles of systematic conservation planning are now widely used by governments and non-government organizations alike to develop biodiversity conservation plans for countries, states, regions, and ecoregions. Many of the species and ecosystems these plans were designed to conserve are now being affected by climate change, and there is a critical need to incorporate new and complementary approaches into these plans that will aid species and ecosystems in adjusting to potential climate change impacts. We propose five approaches to climate change adaptation that can be integrated into existing or new biodiversity conservation plans: (1) conserving the geophysical stage, (2) protecting climatic refugia, (3) enhancing regional connectivity, (4) sustaining ecosystem process and function, and (5) capitalizing on opportunities emerging in response to climate change. We discuss both key assumptions behind each approach and the trade-offs involved in using the approach for conservation planning. We also summarize additional data beyond those typically used in systematic conservation plans required to implement these approaches. A major strength of these approaches is that they are largely robust to the uncertainty in how climate impacts may manifest in any given region.

A new dataset for systematic assessments of climate change impacts as a function of global warming

NASA Astrophysics Data System (ADS)

Heinke, J.; Ostberg, S.; Schaphoff, S.; Frieler, K.; M{ü}ller, C.; Gerten, D.; Meinshausen, M.; Lucht, W.

2012-11-01

In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a~narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalized patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 AOGCMs. The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilize a simplified relationships betweenΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections.

PubMed

Junk, J; Ulber, B; Vidal, S; Eickermann, M

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections

NASA Astrophysics Data System (ADS)

Junk, J.; Ulber, B.; Vidal, S.; Eickermann, M.

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

Cloud Forcing and the Earth's Radiation Budget: New Ideas and New Observations

NASA Technical Reports Server (NTRS)

Barkstrom, Bruce R.

1997-01-01

1. NEW PERSPECTIVES ON CLOUD-RADIATIVE FORCING. When the Earth Radiation Budget Experiment (ERBE) produced the first measurements of cloud-radiative forcing, the climate community interpreted the results from a context in which the atmosphere was a single column, strongly coupled to the Earth's surface. 2. NEW PERSPECTIVES ON CLOUD-RADIATION OBSERVATIONS. The climate community is also on the verge of adding a new dimension to its observational capability. In classic thinking about atmospheric circulation and climate, surface pressure was a readily available quantity. As meteorology developed, it was possible to develop quantitative predictions of future weather by bringing together a network of surface pressure observations and then of profiles of temperature and humidity obtained from balloons. 3. ON COMBINING OBSERVATIONS AND THE - ORY. With this new capability, it is natural to seek recognizable features in the observations we make of the Earth. There are techniques we can use to group the remotely sensed data in the individual footprints into objects that we can track. We will present one such image-processing application to radiation budget data, showing how we can interpret the radiation budget data in terms of cloud systems that are organized into systematic patterns of behavior - an ecosystem-like view of cloud behavior.

Constraints on Oceanic Meridional Transport of Heat and Carbon from Combined Oceanic and Atmospheric Measurements.

NASA Astrophysics Data System (ADS)

Resplandy, L.; Keeling, R. F.; Stephens, B. B.; Bent, J. D.; Jacobson, A. R.; Rödenbeck, C.; Khatiwala, S.

2016-02-01

The global ocean transports heat northward. The magnitude of this asymmetry between the two hemispheres is a key factor of the climate system through the displacement of tropical precipitation north of the equator and its influence on Arctic temperature and sea-ice extent. These asymmetric influences on heat are however not well constrained by observations or models. We identify a robust link between the ocean heat asymmetry and the large-scale distribution in atmospheric oxygen, using both atmospheric and oceanic observations and a suite of models (oceanic, climate and inverse). Novel aircraft observations from the pole-to-pole HIPPO campaign reveal that the ocean northward heat transport necessary to explain the atmospheric oxygen distribution is in the upper range of previous estimates from hydrographic sections and atmospheric reanalyses. Finally, we evidence a strong link between the oceanic transports of heat and natural carbon. This supports the existence of a strong southward transport of natural carbon at the global scale, a feature present at pre-industrial times and still underlying the anthropogenic signal today. We find that current climate models systematically underestimate these natural large-scale ocean meridional transports of heat and carbon, which bears on future climate projections, in particular concerning Arctic climate, possible shifts in rainfall and carbon sinks partition between the land and the ocean.

Assessment of radiative feedback in climate models using satellite observations of annual flux variation.

PubMed

Tsushima, Yoko; Manabe, Syukuro

2013-05-07

In the climate system, two types of radiative feedback are in operation. The feedback of the first kind involves the radiative damping of the vertically uniform temperature perturbation of the troposphere and Earth's surface that approximately follows the Stefan-Boltzmann law of blackbody radiation. The second kind involves the change in the vertical lapse rate of temperature, water vapor, and clouds in the troposphere and albedo of the Earth's surface. Using satellite observations of the annual variation of the outgoing flux of longwave radiation and that of reflected solar radiation at the top of the atmosphere, this study estimates the so-called "gain factor," which characterizes the strength of radiative feedback of the second kind that operates on the annually varying, global-scale perturbation of temperature at the Earth's surface. The gain factor is computed not only for all sky but also for clear sky. The gain factor of so-called "cloud radiative forcing" is then computed as the difference between the two. The gain factors thus obtained are compared with those obtained from 35 models that were used for the fourth and fifth Intergovernmental Panel on Climate Change assessment. Here, we show that the gain factors obtained from satellite observations of cloud radiative forcing are effective for identifying systematic biases of the feedback processes that control the sensitivity of simulated climate, providing useful information for validating and improving a climate model.

Human Plague Risk: Spatial-Temporal Models

NASA Technical Reports Server (NTRS)

Pinzon, Jorge E.

2010-01-01

This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).

Exploring multiple sources of climatic information within personal and medical diaries, Bombay 1799-1828

NASA Astrophysics Data System (ADS)

Adamson, George

2016-04-01

Private diaries are being recognised as an important source of information on past climatic conditions, providing place-specific, often daily records of meteorological information. As many were not intended for publication, or indeed to be read by anyone other than the author, issues of observer bias are lower than some other types of documentary sources. This paper comprises an exploration of the variety of types of climatic information can be mined from a single document or set of documents. The focus of the analysis is three private and one medical diary kept by British colonists in Bombay, western India, during the first decades of the nineteenth century. The paper discusses the potential of the diaries for reconstruction of precipitation, temperature and extreme events. Ad-hoc temperature observations collected by the four observers prove to be particularly fruitful for reconstructing monthly extreme temperatures, with values comparable to more systematic observations collected during the period. This leads to a tentative conclusion that extreme temperatures in Bombay were around 5°C lower during the period than today, a difference likely predominantly attributable to the urban heat island effect.

A method for screening climate change-sensitive infectious diseases.

PubMed

Wang, Yunjing; Rao, Yuhan; Wu, Xiaoxu; Zhao, Hainan; Chen, Jin

2015-01-14

Climate change is a significant and emerging threat to human health, especially where infectious diseases are involved. Because of the complex interactions between climate variables and infectious disease components (i.e., pathogen, host and transmission environment), systematically and quantitatively screening for infectious diseases that are sensitive to climate change is still a challenge. To address this challenge, we propose a new statistical indicator, Relative Sensitivity, to identify the difference between the sensitivity of the infectious disease to climate variables for two different climate statuses (i.e., historical climate and present climate) in non-exposure and exposure groups. The case study in Anhui Province, China has demonstrated the effectiveness of this Relative Sensitivity indicator. The application results indicate significant sensitivity of many epidemic infectious diseases to climate change in the form of changing climatic variables, such as temperature, precipitation and absolute humidity. As novel evidence, this research shows that absolute humidity has a critical influence on many observed infectious diseases in Anhui Province, including dysentery, hand, foot and mouth disease, hepatitis A, hemorrhagic fever, typhoid fever, malaria, meningitis, influenza and schistosomiasis. Moreover, some infectious diseases are more sensitive to climate change in rural areas than in urban areas. This insight provides guidance for future health inputs that consider spatial variability in response to climate change.

A Method for Screening Climate Change-Sensitive Infectious Diseases

PubMed Central

Wang, Yunjing; Rao, Yuhan; Wu, Xiaoxu; Zhao, Hainan; Chen, Jin

2015-01-01

Climate change is a significant and emerging threat to human health, especially where infectious diseases are involved. Because of the complex interactions between climate variables and infectious disease components (i.e., pathogen, host and transmission environment), systematically and quantitatively screening for infectious diseases that are sensitive to climate change is still a challenge. To address this challenge, we propose a new statistical indicator, Relative Sensitivity, to identify the difference between the sensitivity of the infectious disease to climate variables for two different climate statuses (i.e., historical climate and present climate) in non-exposure and exposure groups. The case study in Anhui Province, China has demonstrated the effectiveness of this Relative Sensitivity indicator. The application results indicate significant sensitivity of many epidemic infectious diseases to climate change in the form of changing climatic variables, such as temperature, precipitation and absolute humidity. As novel evidence, this research shows that absolute humidity has a critical influence on many observed infectious diseases in Anhui Province, including dysentery, hand, foot and mouth disease, hepatitis A, hemorrhagic fever, typhoid fever, malaria, meningitis, influenza and schistosomiasis. Moreover, some infectious diseases are more sensitive to climate change in rural areas than in urban areas. This insight provides guidance for future health inputs that consider spatial variability in response to climate change. PMID:25594780

Detecting Climate Variability in Tropical Rainfall

NASA Astrophysics Data System (ADS)

Berg, W.

2004-05-01

A number of satellite and merged satellite/in-situ rainfall products have been developed extending as far back as 1979. While the availability of global rainfall data covering over two decades and encompassing two major El Niño events is a valuable resource for a variety of climate studies, significant differences exist between many of these products. Unfortunately, issues such as availability often determine the use of a product for a given application instead of an understanding of the strengths and weaknesses of the various products. Significant efforts have been made to address the impact of sparse sampling by satellite sensors of variable rainfall processes by merging various satellite and in-situ rainfall products. These combine high spatial and temporal frequency satellite infrared data with higher quality passive microwave observations and rain gauge observations. Combining such an approach with spatial and temporal averaging of the data can reduce the large random errors inherent in satellite rainfall estimates to very small levels. Unfortunately, systematic biases can and do result in artificial climate signals due to the underconstrained nature of the rainfall retrieval problem. Because all satellite retrieval algorithms make assumptions regarding the cloud structure and microphysical properties, systematic changes in these assumed parameters between regions and/or times results in regional and/or temporal biases in the rainfall estimates. These biases tend to be relatively small compared to random errors in the retrieval, however, when random errors are reduced through spatial and temporal averaging for climate applications, they become the dominant source of error. Whether or not such biases impact the results for climate studies is very much dependent on the application. For example, all of the existing satellite rainfall products capture the increased rainfall in the east Pacific associated with El Niño, however, the resulting tropical response to El Niño is substantially smaller due to decreased rainfall in the west Pacific partially canceling increases in the central and east Pacific. These differences are not limited to the long-term merged rainfall products using infrared data, but are also exist in state-of-the-art rainfall retrievals from the active and passive microwave sensors on board the Tropical Rainfall Measuring Mission (TRMM). For example, large differences exist in the response of tropical mean rainfall retrieved from the TRMM microwave imager (TMI) 2A12 algorithm and the precipitation radar (PR) 2A25 algorithm to the 1997/98 El Niño. To assist scientists attempting to wade through the vast array of climate rainfall products currently available, and to help them determine whether systematic biases in these rainfall products impact the conclusions of a given study, we have developed a Climate Rainfall Data Center (CRDC). The CRDC web site (rain.atmos.colostate.edu/CRDC) provides climate researchers information on the various rainfall datasets available as well as access to experts in the field of satellite rainfall retrievals to assist them in the appropriate selection and use of climate rainfall products.

Maximum rates of climate change are systematically underestimated in the geological record.

PubMed

Kemp, David B; Eichenseer, Kilian; Kiessling, Wolfgang

2015-11-10

Recently observed rates of environmental change are typically much higher than those inferred for the geological past. At the same time, the magnitudes of ancient changes were often substantially greater than those established in recent history. The most pertinent disparity, however, between recent and geological rates is the timespan over which the rates are measured, which typically differ by several orders of magnitude. Here we show that rates of marked temperature changes inferred from proxy data in Earth history scale with measurement timespan as an approximate power law across nearly six orders of magnitude (10(2) to >10(7) years). This scaling reveals how climate signals measured in the geological record alias transient variability, even during the most pronounced climatic perturbations of the Phanerozoic. Our findings indicate that the true attainable pace of climate change on timescales of greatest societal relevance is underestimated in geological archives.

Effect of year-to-year variability of leaf area index on variable infiltration capacity model performance and simulation of streamflow during drought

NASA Astrophysics Data System (ADS)

Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.

2014-09-01

This study assessed the effect of using observed monthly leaf area index (LAI) on hydrologic model performance and the simulation of streamflow during drought using the variable infiltration capacity (VIC) hydrological model in the Goulburn-Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) observed monthly LAI dataset covering the period from 1982 to 2012. The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash-Sutcliffe efficiency, the logarithm transformed flow Nash-Sutcliffe efficiency and the percentage bias. Finally, the percentage deviation of the simulated monthly streamflow using the observed monthly LAI from simulated streamflow using long-term mean monthly LAI was computed. The VIC model predicted monthly streamflow in the selected sub-catchments with model efficiencies ranging from 61.5 to 95.9% during calibration (1982-1997) and 59 to 92.4% during validation (1998-2012). Our results suggest systematic improvements from 4 to 25% in the Nash-Sutcliffe efficiency in pasture dominated catchments when the VIC model was calibrated with the observed monthly LAI instead of the long-term mean monthly LAI. There was limited systematic improvement in tree dominated catchments. The results also suggest that the model overestimation or underestimation of streamflow during wet and dry periods can be reduced to some extent by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

Interactive Ice Sheet Flowline Model for High School and College Students

NASA Astrophysics Data System (ADS)

Stearns, L. A.; Rezvanbehbahani, S.; Shankar, S.

2017-12-01

Teaching about climate and climate change is conceptually challenging. While teaching tools and lesson plans are rapidly evolving to help teachers and students improve their understanding of climate processes, there are very few tools targeting ice sheet and glacier dynamics. We have built an interactive ice sheet model that allows students to explore how Antarctic glaciers respond to different climate perturbations. Interactive models offer advantages that are hard to obtain in traditional classroom settings; users can systematically investigate hypothetical situations, explore the effects of modifying systems, and repeatedly observe how systems interrelate. As a result, this project provides a much-needed bridge between the data and models used by the scientific community and students in high school and college. We target our instructional and assessment activities to three high school and college students with the overall aim of increasing understanding of ice sheet dynamics and the different ways that ice sheets are impacted by climate change, while also improving their fundamental math skills.

The Current Status and Future of GNSS-Meteorology in Europe

NASA Astrophysics Data System (ADS)

Jones, J.; Guerova, G.; Dousa, J.; Dick, G.; Haan, de, S.; Pottiaux, E.; Bock, O.; Pacione, R.

2017-12-01

GNSS is a well established atmospheric observing system which can accurately sense water vapour, the most abundant greenhouse gas, accounting for 60-70% of atmospheric warming. Water vapour observations are currently under-sampled in operational meteorology and obtaining and exploiting additional high-quality humidity observations is essential to improve severe weather forecasting and climate monitoring. Inconsistencies introduced into long-term time series from improved GNSS processing algorithms make climate trend analysis challenging. Ongoing re-processing efforts using state-of-the-art models are underway which will provide consistent time series' of tropospheric data, using 15+ years of GNSS observations and from over 600 stations worldwide. These datasets will enable validation of systematic biases from a range of instrumentation, improve the knowledge of climatic trends of atmospheric water vapour, and will potentially be of great benefit to global and regional NWP reanalyses and climate model simulations (e.g. IPCC AR5) COST Action ES1206 is a 4-year project, running from 2013 to 2017, which has coordinated new and improved capabilities from concurrent developments in GNSS, meteorological and climate communities. For the first time, the synergy of multi-GNSS constellations has been used to develop new, more advanced tropospheric products, exploiting the full potential of multi-GNSS on a wide range of temporal and spatial scales - from real-time products monitoring and forecasting severe weather, to the highest quality post-processed products suitable for climate research. The Action has also promoted the use of meteorological data as an input to real-time GNSS positioning, navigation, and timing services and has stimulated knowledge and data transfer throughout Europe and beyond. This presentation will give an overview of COST Action ES1206 plus an overview of ground-based GNSS-meteorology in Europe in general, including current status and future opportunities.

VALUE - Validating and Integrating Downscaling Methods for Climate Change Research

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Benestad, Rasmus; Kotlarski, Sven; Huth, Radan; Hertig, Elke; Wibig, Joanna; Gutierrez, Jose

2013-04-01

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.

Thermal Tides in the Martian Middle Atmosphere as Seen by the Mars Climate Sounder

PubMed Central

Lee, C.; Lawson, W. G.; Richardson, M. I.; Heavens, N. G.; Kleinböhl, A.; Banfield, D.; McCleese, D. J.; Zurek, R.; Kass, D.; Schofield, J. T.; Leovy, C. B.; Taylor, F. W.; Toigo, A. D.

2016-01-01

The first systematic observations of the middle atmosphere of Mars (35km–80km) with the Mars Climate Sounder (MCS) show dramatic patterns of diurnal thermal variation, evident in retrievals of temperature and water ice opacity. At the time of writing, the dataset of MCS limb retrievals is sufficient for spectral analysis within a limited range of latitudes and seasons. This analysis shows that these thermal variations are almost exclusively associated with a diurnal thermal tide. Using a Martian General Circulation Model to extend our analysis we show that the diurnal thermal tide dominates these patterns for all latitudes and all seasons. PMID:27630378

Why Hasn't Earth Warmed as Much as Expected?

NASA Technical Reports Server (NTRS)

Schwartz, Stephen E.; Charlson, Robert J.; Kahn, Ralph A.; Ogren, John A.; Rodhe, Henning

2010-01-01

The observed increase in global mean surface temperature (GMST) over the industrial era is less than 40% of that expected from observed increases in long-lived greenhouse gases together with the best-estimate equilibrium climate sensitivity given by the 2007 Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Possible reasons for this warming discrepancy are systematically examined here. The warming discrepancy is found to be due mainly to some combination of two factors: the IPCC best estimate of climate sensitivity being too high and/or the greenhouse gas forcing being partially offset by forcing by increased concentrations of atmospheric aerosols; the increase in global heat content due to thermal disequilibrium accounts for less than 25% of the discrepancy, and cooling by natural temperature variation can account for only about 15 %. Current uncertainty in climate sensitivity is shown to preclude determining the amount of future fossil fuel CO2 emissions that would be compatible with any chosen maximum allowable increase in GMST; even the sign of such allowable future emissions is unconstrained. Resolving this situation, by empirical determination of the earth's climate sensitivity from the historical record over the industrial period or through use of climate models whose accuracy is evaluated by their performance over this period, is shown to require substantial reduction in the uncertainty of aerosol forcing over this period.

Mapping human dimensions of climate change research in the Canadian Arctic.

PubMed

Ford, James D; Bolton, Kenyon; Shirley, Jamal; Pearce, Tristan; Tremblay, Martin; Westlake, Michael

2012-12-01

This study maps current understanding and research trends on the human dimensions of climate change (HDCC) in the eastern and central Canadian Arctic. Developing a systematic literature review methodology, 117 peer reviewed articles are identified and examined using quantitative and qualitative methods. The research highlights the rapid expansion of HDCC studies over the last decade. Early scholarship was dominated by work documenting Inuit observations of climate change, with research employing vulnerability concepts and terminology now common. Adaptation studies which seek to identify and evaluate opportunities to reduce vulnerability to climate change and take advantage of new opportunities remain in their infancy. Over the last 5 years there has been an increase social science-led research, with many studies employing key principles of community-based research. We currently have baseline understanding of climate change impacts, adaptation, and vulnerability in the region, but key gaps are evident. Future research needs to target significant geographic disparities in understanding, consider risks and opportunities posed by climate change outside of the subsistence hunting sector, complement case study research with regional analyses, and focus on identifying and characterizing sustainable and feasible adaptation interventions.

Land surface models systematically overestimate the intensity, duration and magnitude of seasonal-scale evaporative droughts

DOE PAGES

Ukkola, A. M.; De Kauwe, M. G.; Pitman, A. J.; ...

2016-10-13

Land surface models (LSMs) must accurately simulate observed energy and water fluxes during droughts in order to provide reliable estimates of future water resources. We evaluated 8 different LSMs (14 model versions) for simulating evapotranspiration (ET) during periods of evaporative drought (Edrought) across six flux tower sites. Using an empirically defined Edrought threshold (a decline in ET below the observed 15th percentile), we show that LSMs simulated 58 Edrought days per year, on average, across the six sites, ~3 times as many as the observed 20 d. The simulated Edrought magnitude was ~8 times greater than observed and twice asmore » intense. Our findings point to systematic biases across LSMs when simulating water and energy fluxes under water-stressed conditions. The overestimation of key Edrought characteristics undermines our confidence in the models' capability in simulating realistic drought responses to climate change and has wider implications for phenomena sensitive to soil moisture, including heat waves.« less

Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability.

PubMed

Booth, Ben B B; Dunstone, Nick J; Halloran, Paul R; Andrews, Timothy; Bellouin, Nicolas

2012-04-04

Systematic climate shifts have been linked to multidecadal variability in observed sea surface temperatures in the North Atlantic Ocean. These links are extensive, influencing a range of climate processes such as hurricane activity and African Sahel and Amazonian droughts. The variability is distinct from historical global-mean temperature changes and is commonly attributed to natural ocean oscillations. A number of studies have provided evidence that aerosols can influence long-term changes in sea surface temperatures, but climate models have so far failed to reproduce these interactions and the role of aerosols in decadal variability remains unclear. Here we use a state-of-the-art Earth system climate model to show that aerosol emissions and periods of volcanic activity explain 76 per cent of the simulated multidecadal variance in detrended 1860-2005 North Atlantic sea surface temperatures. After 1950, simulated variability is within observational estimates; our estimates for 1910-1940 capture twice the warming of previous generation models but do not explain the entire observed trend. Other processes, such as ocean circulation, may also have contributed to variability in the early twentieth century. Mechanistically, we find that inclusion of aerosol-cloud microphysical effects, which were included in few previous multimodel ensembles, dominates the magnitude (80 per cent) and the spatial pattern of the total surface aerosol forcing in the North Atlantic. Our findings suggest that anthropogenic aerosol emissions influenced a range of societally important historical climate events such as peaks in hurricane activity and Sahel drought. Decadal-scale model predictions of regional Atlantic climate will probably be improved by incorporating aerosol-cloud microphysical interactions and estimates of future concentrations of aerosols, emissions of which are directly addressable by policy actions.

Can we trust climate models to realistically represent severe European windstorms?

NASA Astrophysics Data System (ADS)

Trzeciak, Tomasz M.; Knippertz, Peter; Owen, Jennifer S. R.

2014-05-01

Despite the enormous advances made in climate change research, robust projections of the position and the strength of the North Atlantic stormtrack are not yet possible. In particular with respect to damaging windstorms, this incertitude bears enormous risks to European societies and the (re)insurance industry. Previous studies have addressed the problem of climate model uncertainty through statistical comparisons of simulations of the current climate with (re-)analysis data and found that there is large disagreement between different climate models, different ensemble members of the same model and observed climatologies of intense cyclones. One weakness of such statistical evaluations lies in the difficulty to separate influences of the climate model's basic state from the influence of fast processes on the development of the most intense storms. Compensating effects between the two might conceal errors and suggest higher reliability than there really is. A possible way to separate influences of fast and slow processes in climate projections is through a "seamless" approach of hindcasting historical, severe storms with climate models started from predefined initial conditions and run in a numerical weather prediction mode on the time scale of several days. Such a cost-effective case-study approach, which draws from and expands on the concepts from the Transpose-AMIP initiative, has recently been undertaken in the SEAMSEW project at the University of Leeds funded by the AXA Research Fund. Key results from this work focusing on 20 historical storms and using different lead times and horizontal and vertical resolutions include: (a) Tracks are represented reasonably well by most hindcasts. (b) Sensitivity to vertical resolution is low. (c) There is a systematic underprediction of cyclone depth for a coarse resolution of T63, but surprisingly no systematic bias is found for higher-resolution runs using T127, showing that climate models are in fact able to represent the storm dynamics well, if given the correct initial conditions. Combined with a too low number of deep cyclones in many climate models, this points too an insufficient number of storm-prone initial conditions in free-running climate runs. This question will be addressed in future work.

Systematic impact of institutional pressures on safety climate in the construction industry.

PubMed

He, Qinghua; Dong, Shuang; Rose, Timothy; Li, Heng; Yin, Qin; Cao, Dongping

2016-08-01

This paper explores how three types of institutional pressure (i.e., coercive, mimetic and normative pressures) systematically impact on the safety climate of construction projects. These impacts are empirically tested by survey data collected from 186 questionnaires of construction companies operating in Shanghai, China. The results, obtained by partial least squares analysis, show that organizational management commitment to safety and employee involvement is positively related to all three institutional pressures, while the perception of responsibility for safety and health is significantly influenced by coercive and mimetic pressure. However, coercive and normative pressures have no significant effect on the applicability of safety rules and work practices, revealing the importance of external organizational pressures in improving project safety climate from a systematic view. The findings also provide insights into the use of institutional forces to facilitate the improvement of safety climate in the construction industry. Copyright © 2015 Elsevier Ltd. All rights reserved.

A new space-time characterization of Northern Hemisphere drought in model simulations of the past and future as compared to the paleoclimate record

NASA Astrophysics Data System (ADS)

Coats, S.; Smerdon, J. E.; Stevenson, S.; Fasullo, J.; Otto-Bliesner, B. L.

2017-12-01

The observational record, which provides only limited sampling of past climate variability, has made it difficult to quantitatively analyze the complex spatio-temporal character of drought. To provide a more complete characterization of drought, machine learning based methods that identify drought in three-dimensional space-time are applied to climate model simulations of the last millennium and future, as well as tree-ring based reconstructions of hydroclimate over the Northern Hemisphere extratropics. A focus is given to the most persistent and severe droughts of the past 1000 years. Analyzing reconstructions and simulations in this context allows for a validation of the spatio-temporal character of persistent and severe drought in climate model simulations. Furthermore, the long records provided by the reconstructions and simulations, allows for sufficient sampling to constrain projected changes to the spatio-temporal character of these features using the reconstructions. Along these lines, climate models suggest that there will be large increases in the persistence and severity of droughts over the coming century, but little change in their spatial extent. These models, however, exhibit biases in the spatio-temporal character of persistent and severe drought over parts of the Northern Hemisphere, which may undermine their usefulness for future projections. Despite these limitations, and in contrast to previous claims, there are no systematic changes in the character of persistent and severe droughts in simulations of the historical interval. This suggests that climate models are not systematically overestimating the hydroclimate response to anthropogenic forcing over this period, with critical implications for confidence in hydroclimate projections.

Impacts of climate change on prioritizing conservation areas of hydrological ecosystem services

NASA Astrophysics Data System (ADS)

Lien, Wan Yu; Lin, Yu Pin

2015-04-01

Ecosystem services (ESs) including hydrological services play important roles in our daily life and provide a lot of benefits for human beings from ecological systems. The systems and their services may be threatened by climate change from global to local scales. We herein developed a systematic approach to assess the impacts of climate change on the hydrological ecosystem services, such as water yield, nutrient (nitrogen and phosphorous) retention, and soil retention in a watershed in Northern Taiwan. We first used an ecosystem service evaluation model, InVEST, to estimate the amount and spatial patterns of annual and monthly hydrological ecosystem services under historical weather data, and different climate change scenarios based on five GMSs. The monthly and annual spatiotemporal variations of the ESs were analyzed in this study. Finally, the multiple estimated ESs were considered as the protection conservation targets and regarded as the input data of the systematic conservation planning software, Zonation, to systematically prioritize reserve areas of the ESs under the climate change scenarios. The ES estimation results indicated that the increasing rainfall in wet season leads to the higher water yield and results in the higher sediment and nutrient export indirectly. The Zonation successfully fielded conservation priorities of the ESs. The conservation priorities of the ESs significantly varied spatially and monthly under the climate change scenarios. The ESs results also indicated that the areas where ESs values and conservation priorities with low resilience under climate change should be considered as high priority protected area to ensure the hydrological services in future. Our proposed approach is a novel systematic approach which can be applied to assess impacts of climate change on spatiotemporal variations of ESs as well as prioritize protected area of the ESs under various climate change scenarios. Keyword: climate change, ecosystem service, conservation planning, spatial analysis.

A global database with parallel measurements to study non-climatic changes

NASA Astrophysics Data System (ADS)

Venema, Victor; Auchmann, Renate; Aguilar, Enric; Auer, Ingeborg; Azorin-Molina, Cesar; Brandsma, Theo; Brunetti, Michele; Dienst, Manuel; Domonkos, Peter; Gilabert, Alba; Lindén, Jenny; Milewska, Ewa; Nordli, Øyvind; Prohom, Marc; Rennie, Jared; Stepanek, Petr; Trewin, Blair; Vincent, Lucie; Willett, Kate; Wolff, Mareile

2016-04-01

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 relocations, (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. Metadata that describe the parallel measurements is as important as the data itself and will be collected as well. For example, the types of the instruments, their siting, height, maintenance, etc. Because they are widely used to study moderate extremes, we will compute the indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). In case the daily data cannot be shared, we would appreciate contributions containing these indices from parallel measurements. For more information: http://tinyurl.com/ISTI-Parallel

The effectiveness of public health interventions to reduce the health impact of climate change: a systematic review of systematic reviews.

PubMed

Bouzid, Maha; Hooper, Lee; Hunter, Paul R

2013-01-01

Climate change is likely to be one of the most important threats to public health in the coming years. Yet despite the large number of papers considering the health impact of climate change, few have considered what public health interventions may be of most value in reducing the disease burden. We aimed to evaluate the effectiveness of public health interventions to reduce the disease burden of high priority climate sensitive diseases. For each disease, we performed a systematic search with no restriction on date or language of publication on Medline, Web of Knowledge, Cochrane CENTRAL and SCOPUS up to December 2010 to identify systematic reviews of public health interventions. We retrieved some 3176 records of which 85 full papers were assessed and 33 included in the review. The included papers investigated the effect of public health interventions on various outcome measures. All interventions were GRADE assessed to determine the strength of evidence. In addition we developed a systematic review quality score. The interventions included environmental interventions to control vectors, chemoprophylaxis, immunization, household and community water treatment, greening cities and community advice. For most reviews, GRADE showed low quality of evidence because of poor study design and high heterogeneity. Also for some key areas such as floods, droughts and other weather extremes, there are no adequate systematic reviews of potential public health interventions. In conclusion, we found the evidence base to be mostly weak for environmental interventions that could have the most value in a warmer world. Nevertheless, such interventions should not be dismissed. Future research on public health interventions for climate change adaptation needs to be concerned about quality in study design and should address the gap for floods, droughts and other extreme weather events that pose a risk to health.

Directionality of recent bird distribution shifts and climate change in Great Britain.

PubMed

Gillings, Simon; Balmer, Dawn E; Fuller, Robert J

2015-06-01

There is good evidence that species' distributions are shifting poleward in response to climate change and wide interest in the magnitude of such responses for scientific and conservation purposes. It has been suggested from the directions of climatic changes that species' distribution shifts may not be simply poleward, but this has been rarely tested with observed data. Here, we apply a novel approach to measuring range shifts on axes ranging through 360°, to recent data on the distributions of 122 species of British breeding birds during 1988-1991 and 2008-2011. Although previously documented poleward range shifts have continued, with an average 13.5 km shift northward, our analysis indicates this is an underestimate because it ignores common and larger shifts that occurred along axes oriented to the north-west and north-east. Trailing edges contracted from a broad range of southerly directions. Importantly, these results are derived from systematically collected data so confounding observer-effort biases can be discounted. Analyses of climate for the same period show that whilst temperature trends should drive species along a north-north-westerly trajectory, directional responses to precipitation will depend on both the time of year that is important for determining a species' distribution, and the location of the range margin. Directions of species' range centroid shift were not correlated with spatial trends in any single climate variable. We conclude that range shifts of British birds are multidirectional, individualistic and probably determined by species-specific interactions of multiple climate factors. Climate change is predicted to lead to changes in community composition through variation in the rates that species' ranges shift; our results suggest communities could change further owing to constituent species shifting along different trajectories. We recommend more studies consider directionality in climate and range dynamics to produce more appropriate measures of observed and expected responses to climate change. © 2014 John Wiley & Sons Ltd.

Polar Processes in a 50-year Simulation of Stratospheric Chemistry and Transport

NASA Technical Reports Server (NTRS)

Kawa, S.R.; Douglass, A. R.; Patrick, L. C.; Allen, D. R.; Randall, C. E.

2004-01-01

The unique chemical, dynamical, and microphysical processes that occur in the winter polar lower stratosphere are expected to interact strongly with changing climate and trace gas abundances. Significant changes in ozone have been observed and prediction of future ozone and climate interactions depends on modeling these processes successfully. We have conducted an off-line model simulation of the stratosphere for trace gas conditions representative of 1975-2025 using meteorology from the NASA finite-volume general circulation model. The objective of this simulation is to examine the sensitivity of stratospheric ozone and chemical change to varying meteorology and trace gas inputs. This presentation will examine the dependence of ozone and related processes in polar regions on the climatological and trace gas changes in the model. The model past performance is base-lined against available observations, and a future ozone recovery scenario is forecast. Overall the model ozone simulation is quite realistic, but initial analysis of the detailed evolution of some observable processes suggests systematic shortcomings in our description of the polar chemical rates and/or mechanisms. Model sensitivities, strengths, and weaknesses will be discussed with implications for uncertainty and confidence in coupled climate chemistry predictions.

The effect of year-to-year variability of leaf area index on Variable Infiltration Capacity model performance and simulation of runoff

NASA Astrophysics Data System (ADS)

Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.

2015-09-01

This study assessed the effect of using observed monthly leaf area index (LAI) on hydrological model performance and the simulation of runoff using the Variable Infiltration Capacity (VIC) hydrological model in the Goulburn-Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) leaf area index dataset covering the period from 1982 to 2012. The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash-Sutcliffe efficiency, the logarithm transformed flow Nash-Sutcliffe efficiency and the percentage bias. Finally, the deviation of the simulated monthly runoff using the observed monthly LAI from simulated runoff using long-term mean monthly LAI was computed. The VIC model predicted monthly runoff in the selected sub-catchments with model efficiencies ranging from 61.5% to 95.9% during calibration (1982-1997) and 59% to 92.4% during validation (1998-2012). Our results suggest systematic improvements, from 4% to 25% in Nash-Sutcliffe efficiency, in sparsely forested sub-catchments when the VIC model was calibrated with observed monthly LAI instead of long-term mean monthly LAI. There was limited systematic improvement in tree dominated sub-catchments. The results also suggest that the model overestimation or underestimation of runoff during wet and dry periods can be reduced to 25 mm and 35 mm respectively by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

Can we trust climate models to realistically represent severe European windstorms?

NASA Astrophysics Data System (ADS)

Trzeciak, Tomasz M.; Knippertz, Peter; Pirret, Jennifer S. R.; Williams, Keith D.

2016-06-01

Cyclonic windstorms are one of the most important natural hazards for Europe, but robust climate projections of the position and the strength of the North Atlantic storm track are not yet possible, bearing significant risks to European societies and the (re)insurance industry. Previous studies addressing the problem of climate model uncertainty through statistical comparisons of simulations of the current climate with (re-)analysis data show large disagreement between different climate models, different ensemble members of the same model and observed climatologies of intense cyclones. One weakness of such evaluations lies in the difficulty to separate influences of the climate model's basic state from the influence of fast processes on the development of the most intense storms, which could create compensating effects and therefore suggest higher reliability than there really is. This work aims to shed new light into this problem through a cost-effective "seamless" approach of hindcasting 20 historical severe storms with the two global climate models, ECHAM6 and GA4 configuration of the Met Office Unified Model, run in a numerical weather prediction mode using different lead times, and horizontal and vertical resolutions. These runs are then compared to re-analysis data. The main conclusions from this work are: (a) objectively identified cyclone tracks are represented satisfactorily by most hindcasts; (b) sensitivity to vertical resolution is low; (c) cyclone depth is systematically under-predicted for a coarse resolution of T63 by both climate models; (d) no systematic bias is found for the higher resolution of T127 out to about three days, demonstrating that climate models are in fact able to represent the complex dynamics of explosively deepening cyclones well, if given the correct initial conditions; (e) an analysis using a recently developed diagnostic tool based on the surface pressure tendency equation points to too weak diabatic processes, mainly latent heating, as the main source for the under-prediction in the coarse-resolution runs. Finally, an interesting implication of these results is that the too low number of deep cyclones in many free-running climate simulations may therefore be related to an insufficient number of storm-prone initial conditions. This question will be addressed in future work.

A global database with parallel measurements to study non-climatic changes

NASA Astrophysics Data System (ADS)

Venema, Victor; Auchmann, Renate; Aguilar, Enric

2015-04-01

n this work we introduce the rationale behind the ongoing compilation of a parallel measurements database, under the umbrella 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., relocations and changes in instrumentation, instrument height or data collection and manipulation procedures. These so-called inhomogeneities distort the climate signal and can hamper the assessment of trends and variability. 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). 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 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, 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. In the ISTI Parallel Observations Science Team (POST), we will gather parallel data in their native format (to avoid undetectable conversion errors we will convert it to a standard format ourselves). 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 temperature measurements, the influencing factors are expected to be insolation, wind and clouds cover; in case of parallel precipitation measurements, wind and temperature are potentially important. Metadata that describe the parallel measurements is as important as the data itself and will be collected as well. For example, the types of the instruments, their siting, height, maintenance, etc. Because they are widely used to study moderate extremes, we will compute the indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). In case the daily data cannot be shared, we would appreciate these indices from parallel measurements. For more information: http://tinyurl.com/ISTI-Parallel

Environmental and social-motivational contextual factors related to youth physical activity: systematic observations of summer day camps.

PubMed

Zarrett, Nicole; Sorensen, Carl; Skiles, Brittany

2013-05-20

Youth risk of obesity is high during the summer months. Summer day camps can be ideal settings for preventing obesity through reducing youth summer sedentary behaviors. However, with limited research on camp settings, the mechanisms by which these programs promote children's physical activity (PA) remains largely unknown. The current study was designed to take a first step in addressing this gap in research through systematic observations of 4 summer day camps. Systematic observations of 4 summer day camps was conducted using the System for Observing Play and Leisure Activity in Youth (SOPLAY) and a social-motivational climate supplemental observation tool founded on Self-Determination Theory and previous research developed by the authors. Teams of two coders observed daily activities for four days across two-week periods at each camp. On 15 minute intervals throughout each day, camps were assessed on level of youth PA (e.g., sedentary, moderate, vigorous), five physical features (e.g., equipment), eight staff interactions (e.g., encourage PA), and six social climate components (e.g., inclusive game). Across the sample, highly engaging games [F(1,329) = 17.68, p < .001], positive peer interactions [F(1,329) = 8.43, p < .01], and bullying [F(1,329) = 9.39, p < .01] were significantly related to higher PA participation rates, and clarity of rules [F(1,329) = 11.12, p < .001] was related to fewer youth participating in PA. Separate analyses for males and females indicated some sex differences with highly engaging games [F(1,329) = 23.10, p < .001] and bullying [F(1,329) = 10.00, p < .01] related to males' but not females' PA, and positive peer interactions related to only females' PA [F(1,329) = 9.58, p < .01]. Small, yet significant physical-environmental effects of temperature [F(1,328) = 1.54, p < .05] and equipment [F(1,328) = 4.34, p = .05] for girls also suggests that activities offered indoors (which was most common during high temperatures), and provision of equipment may also be important considerations for promoting girls' PA. Staff behaviors were minimally predictive of youth PA. This is the first study to conduct systematic observations of the physical and social resources of summer day camps and contributes to our understanding of the strengths and needs of camps to effectively promote PA in both boys and girls during the summer months when risks for obesity are high.

The role of observational reference data for climate downscaling: Insights from the VALUE COST Action

NASA Astrophysics Data System (ADS)

Kotlarski, Sven; Gutiérrez, José M.; Boberg, Fredrik; Bosshard, Thomas; Cardoso, Rita M.; Herrera, Sixto; Maraun, Douglas; Mezghani, Abdelkader; Pagé, Christian; Räty, Olle; Stepanek, Petr; Soares, Pedro M. M.; Szabo, Peter

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research (http://www.value-cost.eu). A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of downscaling methods. Such assessments can be expected to crucially depend on the existence of accurate and reliable observational reference data. In dynamical downscaling, observational data can influence model development itself and, later on, model evaluation, parameter calibration and added value assessment. In empirical-statistical downscaling, observations serve as predictand data and directly influence model calibration with corresponding effects on downscaled climate change projections. We here present a comprehensive assessment of the influence of uncertainties in observational reference data and of scale-related issues on several of the above-mentioned aspects. First, temperature and precipitation characteristics as simulated by a set of reanalysis-driven EURO-CORDEX RCM experiments are validated against three different gridded reference data products, namely (1) the EOBS dataset (2) the recently developed EURO4M-MESAN regional re-analysis, and (3) several national high-resolution and quality-controlled gridded datasets that recently became available. The analysis reveals a considerable influence of the choice of the reference data on the evaluation results, especially for precipitation. It is also illustrated how differences between the reference data sets influence the ranking of RCMs according to a comprehensive set of performance measures.

What we know, do not know, and need to know about climate change vulnerability in the western Canadian Arctic: a systematic literature review

NASA Astrophysics Data System (ADS)

Ford, James D.; Pearce, Tristan

2010-01-01

This letter systematically reviews and synthesizes scientific and gray literature publications (n = 420) to identify and characterize the nature of climate change vulnerability in the Inuvialuit Settlement Region of the western Canadian Arctic and identify gaps in understanding. The literature documents widespread evidence of climate change, with implications for human and biophysical systems. Adaptations are being employed to manage changing conditions and are indicative of a high adaptive capacity. However, barriers to adaptation are evident and are expected to constrain adaptive capacity to future climate change. Continued climate change is predicted for the region, with differential exposure sensitivity for communities, groups and sectors: a function of social-economic-biophysical characteristics and projected future climatic conditions. Existing climate risks are expected to increase in magnitude and frequency, although the interaction between projected changes and socio-economic-demographic trends has not been assessed. The capacity for adapting to future climate change has also not been studied. The review identifies the importance of targeted vulnerability research that works closely with community members and other stakeholders to address research needs. Importantly, the fully categorized list of reviewed references accompanying this letter will be a valuable resource for those working or planning to work in the region, capturing climate change research published since 1990. At a broader level, the systematic review methodology offers a promising tool for climate/environmental change studies in general where there is a large and emerging body of research but limited understanding of research gaps and needs.

Assessing Extratropical Influence on Tropical Climatology and Variability with Regional Coupled Data Assimilation

NASA Astrophysics Data System (ADS)

Lu, F.; Liu, Z.; Liu, Y.; Zhang, S.; Jacob, R. L.

2017-12-01

The Regional Coupled Data Assimilation (RCDA) method is introduced as a tool to study coupled climate dynamics and teleconnections. The RCDA method is built on an ensemble-based coupled data assimilation (CDA) system in a coupled general circulation model (CGCM). The RCDA method limits the data assimilation to the desired model components (e.g. atmosphere) and regions (e.g. the extratropics), and studies the ensemble-mean model response (e.g. tropical response to "observed" extratropical atmospheric variability). When applied to the extratropical influence on tropical climate, the RCDA method has shown some unique advantages, namely the combination of a fully coupled model, real-world observations and an ensemble approach. Tropical variability (e.g. El Niño-Southern Oscillation or ENSO) and climatology (e.g. asymmetric Inter-Tropical Convergence Zone or ITCZ) were initially thought to be determined mostly by local forcing and ocean-atmosphere interaction in the tropics. Since late 20th century, numerous studies have showed that extratropical forcing could affect, or even largely determine some aspects of the tropical climate. Due to the coupled nature of the climate system, however, the challenge of determining and further quantifying the causality of extratropical forcing on the tropical climate remains. Using the RCDA method, we have demonstrated significant control of extratropical atmospheric forcing on ENSO variability in a CGCM, both with model-generated and real-world observation datasets. The RCDA method has also shown robust extratropical impact on the tropical double-ITCZ bias in a CGCM. The RCDA method has provided the first systematic and quantitative assessment of extratropical influence on tropical climatology and variability by incorporating real world observations in a CGCM.

How Do You Determine Whether The Earth Is Warming Up?

NASA Astrophysics Data System (ADS)

Restrepo, J. M.; Comeau, D.; Flaschka, H.

2012-12-01

How does one determine whether the extreme summer temperatures in the North East of the US, or in Moscow during the summer of 2010, was an extreme weather fluctuation or the result of a systematic global climate warming trend? It is only under exceptional circumstances that one can determine whether an observational climate signal belongs to a particular statistical distribution. In fact, observed climate signals are rarely "statistical" and thus there is usually no way to rigorously obtain enough field data to produce a trend or tendency, based upon data alone. Furthermore, this type of data is often multi-scale. We propose a trend or tendency methodology that does not make use of a parametric or a statistical assumption. The most important feature of this trend strategy is that it is defined in very precise mathematical terms. The tendency is easily understood and practical, and its algorithmic realization is fairly robust. In addition to proposing a trend, the methodology can be adopted to generate surrogate statistical models, useful in reduced filtering schemes of time dependent processes.

Could geoengineering research help answer one of the biggest questions in climate science?

NASA Astrophysics Data System (ADS)

Wood, Robert; Ackerman, Thomas; Rasch, Philip; Wanser, Kelly

2017-07-01

Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in quantifying the radiative forcing of climate, and hinders our ability to determine Earth's climate sensitivity to greenhouse gas increases. Representation of aerosol-cloud interactions in global models is particularly challenging because these interactions occur on typically unresolved scales. Observational studies show influences of aerosol on clouds, but correlations between aerosol and clouds are insufficient to constrain aerosol forcing because of the difficulty in separating aerosol and meteorological impacts. In this commentary, we argue that this current impasse may be overcome with the development of approaches to conduct control experiments whereby aerosol particle perturbations can be introduced into patches of marine low clouds in a systematic manner. Such cloud perturbation experiments constitute a fresh approach to climate science and would provide unprecedented data to untangle the effects of aerosol particles on cloud microphysics and the resulting reflection of solar radiation by clouds. The control experiments would provide a critical test of high-resolution models that are used to develop an improved representation aerosol-cloud interactions needed to better constrain aerosol forcing in global climate models.

A virtual climate library of surface temperature over North America for 1979-2015

NASA Astrophysics Data System (ADS)

Kravtsov, Sergey; Roebber, Paul; Brazauskas, Vytaras

2017-10-01

The most comprehensive continuous-coverage modern climatic data sets, known as reanalyses, come from combining state-of-the-art numerical weather prediction (NWP) models with diverse available observations. These reanalysis products estimate the path of climate evolution that actually happened, and their use in a probabilistic context—for example, to document trends in extreme events in response to climate change—is, therefore, limited. Free runs of NWP models without data assimilation can in principle be used for the latter purpose, but such simulations are computationally expensive and are prone to systematic biases. Here we produce a high-resolution, 100-member ensemble simulation of surface atmospheric temperature over North America for the 1979-2015 period using a comprehensive spatially extended non-stationary statistical model derived from the data based on the North American Regional Reanalysis. The surrogate climate realizations generated by this model are independent from, yet nearly statistically congruent with reality. This data set provides unique opportunities for the analysis of weather-related risk, with applications in agriculture, energy development, and protection of human life.

A virtual climate library of surface temperature over North America for 1979–2015

PubMed Central

Kravtsov, Sergey; Roebber, Paul; Brazauskas, Vytaras

2017-01-01

The most comprehensive continuous-coverage modern climatic data sets, known as reanalyses, come from combining state-of-the-art numerical weather prediction (NWP) models with diverse available observations. These reanalysis products estimate the path of climate evolution that actually happened, and their use in a probabilistic context—for example, to document trends in extreme events in response to climate change—is, therefore, limited. Free runs of NWP models without data assimilation can in principle be used for the latter purpose, but such simulations are computationally expensive and are prone to systematic biases. Here we produce a high-resolution, 100-member ensemble simulation of surface atmospheric temperature over North America for the 1979–2015 period using a comprehensive spatially extended non-stationary statistical model derived from the data based on the North American Regional Reanalysis. The surrogate climate realizations generated by this model are independent from, yet nearly statistically congruent with reality. This data set provides unique opportunities for the analysis of weather-related risk, with applications in agriculture, energy development, and protection of human life. PMID:29039842

A virtual climate library of surface temperature over North America for 1979-2015.

PubMed

Kravtsov, Sergey; Roebber, Paul; Brazauskas, Vytaras

2017-10-17

The most comprehensive continuous-coverage modern climatic data sets, known as reanalyses, come from combining state-of-the-art numerical weather prediction (NWP) models with diverse available observations. These reanalysis products estimate the path of climate evolution that actually happened, and their use in a probabilistic context-for example, to document trends in extreme events in response to climate change-is, therefore, limited. Free runs of NWP models without data assimilation can in principle be used for the latter purpose, but such simulations are computationally expensive and are prone to systematic biases. Here we produce a high-resolution, 100-member ensemble simulation of surface atmospheric temperature over North America for the 1979-2015 period using a comprehensive spatially extended non-stationary statistical model derived from the data based on the North American Regional Reanalysis. The surrogate climate realizations generated by this model are independent from, yet nearly statistically congruent with reality. This data set provides unique opportunities for the analysis of weather-related risk, with applications in agriculture, energy development, and protection of human life.

Abrupt cooling over the North Atlantic in modern climate models

PubMed Central

Sgubin, Giovanni; Swingedouw, Didier; Drijfhout, Sybren; Mary, Yannick; Bennabi, Amine

2017-01-01

Observations over the 20th century evidence no long-term warming in the subpolar North Atlantic (SPG). This region even experienced a rapid cooling around 1970, raising a debate over its potential reoccurrence. Here we assess the risk of future abrupt SPG cooling in 40 climate models from the fifth Coupled Model Intercomparison Project (CMIP5). Contrary to the long-term SPG warming trend evidenced by most of the models, 17.5% of the models (7/40) project a rapid SPG cooling, consistent with a collapse of the local deep-ocean convection. Uncertainty in projections is associated with the models' varying capability in simulating the present-day SPG stratification, whose realistic reproduction appears a necessary condition for the onset of a convection collapse. This event occurs in 45.5% of the 11 models best able to simulate the observed SPG stratification. Thus, due to systematic model biases, the CMIP5 ensemble as a whole underestimates the chance of future abrupt SPG cooling, entailing crucial implications for observation and adaptation policy. PMID:28198383

Climate change tendencies observable in the rainfall measurements since 1950 in the federal land of North Rhine-Westphalia and their consequences for urban hydrology.

PubMed

Einfalt, T; Quirmbach, M; Langstädtler, G; Mehlig, B

2011-01-01

Climate change is present in climatological models - but did we already observe changes in the past measurement data? For the state of North Rhine Westphalia, the rainfall measurements since 1950 have been systematically analysed in order to find out whether there have already been trends and whether the behaviour of rainfall has changed in time. More than 600 station series have been screened for use in the project and quality controlled. Implausible data were discarded. For the analysis, standard values such as yearly sums, half-yearly sums, monthly sums, number of dry days, number of days with precipitation above a threshold, partial time series and extreme values statistics have been calculated and evaluated. Results show that also in the past 50 years, changes in precipitation regime could be observed. These changes have been regionally different. Consequences for urban hydrology include a development of more flexible design approaches.

Impact of a statistical bias correction on the projected simulated hydrological changes obtained from three GCMs and two hydrology models

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Chen, Cui; Haerter, Jan O.; Gerten, Dieter; Heinke, Jens; Piani, Claudio

2010-05-01

Future climate model scenarios depend crucially on their adequate representation of the hydrological cycle. Within the European project "Water and Global Change" (WATCH) special care is taken to couple state-of-the-art climate model output to a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, due to the systematic model errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed, which can be used for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. As observations, global re-analysed daily data of precipitation and temperature are used that are obtained in the WATCH project. We will apply the bias correction to global climate model data of precipitation and temperature from the GCMs ECHAM5/MPIOM, CNRM-CM3 and LMDZ-4, and intercompare the bias corrected data to the original GCM data and the observations. Then, the orginal and the bias corrected GCM data will be used to force two global hydrology models: (1) the hydrological model of the Max Planck Institute for Meteorology (MPI-HM) consisting of the Simplified Land surface (SL) scheme and the Hydrological Discharge (HD) model, and (2) the dynamic vegetation model LPJmL operated by the Potsdam Institute for Climate Impact Research. The impact of the bias correction on the projected simulated hydrological changes will be analysed, and the resulting behaviour of the two hydrology models will be compared.

Projected changes to growth and mortality of Hawaiian corals over the next 100 years.

PubMed

Hoeke, Ron K; Jokiel, Paul L; Buddemeier, Robert W; Brainard, Russell E

2011-03-29

Recent reviews suggest that the warming and acidification of ocean surface waters predicated by most accepted climate projections will lead to mass mortality and declining calcification rates of reef-building corals. This study investigates the use of modeling techniques to quantitatively examine rates of coral cover change due to these effects. Broad-scale probabilities of change in shallow-water scleractinian coral cover in the Hawaiian Archipelago for years 2000-2099 A.D. were calculated assuming a single middle-of-the-road greenhouse gas emissions scenario. These projections were based on ensemble calculations of a growth and mortality model that used sea surface temperature (SST), atmospheric carbon dioxide (CO(2)), observed coral growth (calcification) rates, and observed mortality linked to mass coral bleaching episodes as inputs. SST and CO(2) predictions were derived from the World Climate Research Programme (WCRP) multi-model dataset, statistically downscaled with historical data. The model calculations illustrate a practical approach to systematic evaluation of climate change effects on corals, and also show the effect of uncertainties in current climate predictions and in coral adaptation capabilities on estimated changes in coral cover. Despite these large uncertainties, this analysis quantitatively illustrates that a large decline in coral cover is highly likely in the 21(st) Century, but that there are significant spatial and temporal variances in outcomes, even under a single climate change scenario.

Projected changes to growth and mortality of Hawaiian corals over the next 100 years

USGS Publications Warehouse

Hoeke, R.K.; Jokiel, P.L.; Buddemeier, R.W.; Brainard, R.E.

2011-01-01

Background: Recent reviews suggest that the warming and acidification of ocean surface waters predicated by most accepted climate projections will lead to mass mortality and declining calcification rates of reef-building corals. This study investigates the use of modeling techniques to quantitatively examine rates of coral cover change due to these effects. Methodology/Principal Findings: Broad-scale probabilities of change in shallow-water scleractinian coral cover in the Hawaiian Archipelago for years 2000-2099 A.D. were calculated assuming a single middle-of-the-road greenhouse gas emissions scenario. These projections were based on ensemble calculations of a growth and mortality model that used sea surface temperature (SST), atmospheric carbon dioxide (CO2), observed coral growth (calcification) rates, and observed mortality linked to mass coral bleaching episodes as inputs. SST and CO2 predictions were derived from the World Climate Research Programme (WCRP) multi-model dataset, statistically downscaled with historical data. Conclusions/Significance: The model calculations illustrate a practical approach to systematic evaluation of climate change effects on corals, and also show the effect of uncertainties in current climate predictions and in coral adaptation capabilities on estimated changes in coral cover. Despite these large uncertainties, this analysis quantitatively illustrates that a large decline in coral cover is highly likely in the 21st Century, but that there are significant spatial and temporal variances in outcomes, even under a single climate change scenario.

Integrating Enhanced Grace Terrestrial Water Storage Data Into the U.S. and North American Drought Monitors

NASA Technical Reports Server (NTRS)

Housborg, Rasmus; Rodell, Matthew

2010-01-01

NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations nf the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including ground water. The U.S. and North American Drought Monitors are two of the premier drought monitoring products available to decision-makers for assessing and minimizing drought impacts, but they rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors hy filling this observational gap. Horizontal, vertical and temporal disaggregation of the coarse-resolution GRACE TWS data has been accomplished by assimilating GRACE TWS anomalies into the Catchment Land Surface Model using ensemble Kalman smoother. The Drought Monitors combine several short-term and long-term drought indices and indicators expressed in percentiles as a reference to their historical frequency of occurrence for the location and time of year in question. To be consistent, we are in the process of generating a climatology of estimated soil moisture and ground water based on m 60-year Catchment model simulation which will subsequently be used to convert seven years of GRACE assimilated fields into soil moisture and groundwater percentiles. for systematic incorporation into the objective blends that constitute Drought Monitor baselines. At this stage we provide a preliminary evaluation of GRACE assimilated Catchment model output against independent datasets including soil moisture observations from Aqua AMSR-E and groundwater level observations from the U.S. Geological Survey's Groundwater Climate Response Network.

External forcing as a metronome for Atlantic multidecadal variability

NASA Astrophysics Data System (ADS)

Otterå, Odd Helge; Bentsen, Mats; Drange, Helge; Suo, Lingling

2010-10-01

Instrumental records, proxy data and climate modelling show that multidecadal variability is a dominant feature of North Atlantic sea-surface temperature variations, with potential impacts on regional climate. To understand the observed variability and to gauge any potential for climate predictions it is essential to identify the physical mechanisms that lead to this variability, and to explore the spatial and temporal characteristics of multidecadal variability modes. Here we use a coupled ocean-atmosphere general circulation model to show that the phasing of the multidecadal fluctuations in the North Atlantic during the past 600 years is, to a large degree, governed by changes in the external solar and volcanic forcings. We find that volcanoes play a particularly important part in the phasing of the multidecadal variability through their direct influence on tropical sea-surface temperatures, on the leading mode of northern-hemisphere atmosphere circulation and on the Atlantic thermohaline circulation. We suggest that the implications of our findings for decadal climate prediction are twofold: because volcanic eruptions cannot be predicted a decade in advance, longer-term climate predictability may prove challenging, whereas the systematic post-eruption changes in ocean and atmosphere may hold promise for shorter-term climate prediction.

(abstract) A Geomagnetic Contribution to Climate Change in this Century

NASA Technical Reports Server (NTRS)

Feynman, J.; Ruzmaikin, A.; Lawrence, J.

1996-01-01

There is a myth that all solar effects can be parameterized by the sun spot number. This is not true. For example, the level of geomagnetic activity during this century was not proportional to the sunspot number. Instead there is a large systematic increase in geomagnetic activity, not reflected in the sunspot number. This increase occurred gradually over at least 60 years. The 11 year solar cycle variation was superimposed on this systematic increase. Here we show that this systematic increase in activity is well correlated to the simultaneous increase in terrestrial temperature that occurred during the first half of this century. We discuss these findings in terms of mechanisms by which geomagnetics can be coupled to climate. These mechanisms include possible changes in weather patterns and cloud cover due to increased cosmic ray fluxes, or to increased fluxes of high energy electrons. We suggest that this systematic increase in geomagnetic activity contributed (along with anthropogenic effects and possible changes in solar irradiance) to the changes in climate recorded during this period.

Thirty Years of Improving the NCEP Global Forecast System

NASA Astrophysics Data System (ADS)

White, G. H.; Manikin, G.; Yang, F.

2014-12-01

Current eight day forecasts by the NCEP Global Forecast System are as accurate as five day forecasts 30 years ago. This revolution in weather forecasting reflects increases in computer power, improvements in the assimilation of observations, especially satellite data, improvements in model physics, improvements in observations and international cooperation and competition. One important component has been and is the diagnosis, evaluation and reduction of systematic errors. The effect of proposed improvements in the GFS on systematic errors is one component of the thorough testing of such improvements by the Global Climate and Weather Modeling Branch. Examples of reductions in systematic errors in zonal mean temperatures and winds and other fields will be presented. One challenge in evaluating systematic errors is uncertainty in what reality is. Model initial states can be regarded as the best overall depiction of the atmosphere, but can be misleading in areas of few observations or for fields not well observed such as humidity or precipitation over the oceans. Verification of model physics is particularly difficult. The Environmental Modeling Center emphasizes the evaluation of systematic biases against observations. Recently EMC has placed greater emphasis on synoptic evaluation and on precipitation, 2-meter temperatures and dew points and 10 meter winds. A weekly EMC map discussion reviews the performance of many models over the United States and has helped diagnose and alleviate significant systematic errors in the GFS, including a near surface summertime evening cold wet bias over the eastern US and a multi-week period when the GFS persistently developed bogus tropical storms off Central America. The GFS exhibits a wet bias for light rain and a dry bias for moderate to heavy rain over the continental United States. Significant changes to the GFS are scheduled to be implemented in the fall of 2014. These include higher resolution, improved physics and improvements to the assimilation. These changes significantly improve the tropospheric flow and reduce a tropical upper tropospheric warm bias. One important error remaining is the failure of the GFS to maintain deep convection over Indonesia and in the tropical west Pacific. This and other current systematic errors will be presented.

A Systematic Review and Meta-Analysis of the Partitioning of Precipitation over Land

NASA Astrophysics Data System (ADS)

Padrón, Ryan S.; Gudmundsson, Lukas; Greve, Peter; Seneviratne, Sonia I.

2017-04-01

Long-term mean Precipitation (P) over land is partitioned into runoff (R) and evapotranspiration (ET). The aridity index, defined as the ratio between potential ET and P, constitutes the first order control of this partitioning (i.e. ET/P) within Budyko's framework. However, second order controls of ET/P can be significant, and their understanding remains a fundamental challenge. This study therefore introduces a new global observation-based dataset for the long-term mean partitioning of P into ET and R in approximately 2000 catchments, which is obtained from a systematic examination of 170 peer-reviewed studies. The new dataset serves as a basis to improve our understanding of these second order controls around the world. A list of 22 indicators of second order controls of ET/P are identified from the literature, and tested for significance using the new dataset. Results reveal that (i) climate type is a dominant control of ET/P, and additional controls vary with climatic region; (ii) climate characteristics and catchment slope dominate over other catchment controls—the phase shift between the seasonal cycle of P and potential ET appears as an important index across all climate types; (iii) despite the high attention that vegetation-related indices receive as controls of ET/P, they were found to be less important and not always significant; and (iv) the fraction of precipitation falling as snow is the most important second order control in regions with snow climate. The process-related insights from this study about the partitioning of P are a valuable asset for model development, watershed management, and the understanding of future water availability around the globe.

Controls on stream network branching angles, tested using landscape evolution models

NASA Astrophysics Data System (ADS)

Theodoratos, Nikolaos; Seybold, Hansjörg; Kirchner, James W.

2016-04-01

Stream networks are striking landscape features. The topology of stream networks has been extensively studied, but their geometry has received limited attention. Analyses of nearly 1 million stream junctions across the contiguous United States [1] have revealed that stream branching angles vary systematically with climate and topographic gradients at continental scale. Stream networks in areas with wet climates and gentle slopes tend to have wider branching angles than in areas with dry climates or steep slopes, but the mechanistic linkages underlying these empirical correlations remain unclear. Under different climatic and topographic conditions different runoff generation mechanisms and, consequently, transport processes are dominant. Models [2] and experiments [3] have shown that the relative strength of channel incision versus diffusive hillslope transport controls the spacing between valleys, an important geometric property of stream networks. We used landscape evolution models (LEMs) to test whether similar factors control network branching angles as well. We simulated stream networks using a wide range of hillslope diffusion and channel incision parameters. The resulting branching angles vary systematically with the parameters, but by much less than the regional variability in real-world stream networks. Our results suggest that the competition between hillslope and channeling processes influences branching angles, but that other mechanisms may also be needed to account for the variability in branching angles observed in the field. References: [1] H. Seybold, D. H. Rothman, and J. W. Kirchner, 2015, Climate's watermark in the geometry of river networks, Submitted manuscript. [2] J. T. Perron, W. E. Dietrich, and J. W. Kirchner, 2008, Controls on the spacing of first-order valleys, Journal of Geophysical Research, 113, F04016. [3] K. E. Sweeney, J. J. Roering, and C. Ellis, 2015, Experimental evidence for hillslope control of landscape scale, Science, 349(6243), 51-53.

Shifts in tree functional composition amplify the response of forest biomass to climate

NASA Astrophysics Data System (ADS)

Zhang, Tao; Niinemets, Ülo; Sheffield, Justin; Lichstein, Jeremy W.

2018-04-01

Forests have a key role in global ecosystems, hosting much of the world’s terrestrial biodiversity and acting as a net sink for atmospheric carbon. These and other ecosystem services that are provided by forests may be sensitive to climate change as well as climate variability on shorter time scales (for example, annual to decadal). Previous studies have documented responses of forest ecosystems to climate change and climate variability, including drought-induced increases in tree mortality rates. However, relationships between forest biomass, tree species composition and climate variability have not been quantified across a large region using systematically sampled data. Here we use systematic forest inventories from the 1980s and 2000s across the eastern USA to show that forest biomass responds to decadal-scale changes in water deficit, and that this biomass response is amplified by concurrent changes in community-mean drought tolerance, a functionally important aspect of tree species composition. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards species that are more tolerant to drought but are slower growing. These results demonstrate concurrent changes in forest species composition and biomass carbon storage across a large, systematically sampled region, and highlight the potential for climate-induced changes in forest ecosystems across the world, resulting from both direct effects of climate on forest biomass and indirect effects mediated by shifts in species composition.

Shifts in tree functional composition amplify the response of forest biomass to climate.

PubMed

Zhang, Tao; Niinemets, Ülo; Sheffield, Justin; Lichstein, Jeremy W

2018-04-05

Forests have a key role in global ecosystems, hosting much of the world's terrestrial biodiversity and acting as a net sink for atmospheric carbon. These and other ecosystem services that are provided by forests may be sensitive to climate change as well as climate variability on shorter time scales (for example, annual to decadal). Previous studies have documented responses of forest ecosystems to climate change and climate variability, including drought-induced increases in tree mortality rates. However, relationships between forest biomass, tree species composition and climate variability have not been quantified across a large region using systematically sampled data. Here we use systematic forest inventories from the 1980s and 2000s across the eastern USA to show that forest biomass responds to decadal-scale changes in water deficit, and that this biomass response is amplified by concurrent changes in community-mean drought tolerance, a functionally important aspect of tree species composition. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards species that are more tolerant to drought but are slower growing. These results demonstrate concurrent changes in forest species composition and biomass carbon storage across a large, systematically sampled region, and highlight the potential for climate-induced changes in forest ecosystems across the world, resulting from both direct effects of climate on forest biomass and indirect effects mediated by shifts in species composition.

Atmosphere and climate studies of Mars using the Mars Observer pressure modulator infrared radiometer

NASA Technical Reports Server (NTRS)

Mccleese, D. J.; Haskins, R. D.; Schofield, J. T.; Zurek, R. W.; Leovy, C. B.; Paige, D. A.; Taylor, F. W.

1992-01-01

Studies of the climate and atmosphere of Mars are limited at present by a lack of meteorological data having systematic global coverage with good horizontal and vertical resolution. The Mars Observer spacecraft in a low, nearly circular, polar orbit will provide an excellent platform for acquiring the data needed to advance significantly our understanding of the Martian atmosphere and its remarkable variability. The Mars Observer pressure modulator infrared radiometer (PMIRR) is a nine-channel limb and nadir scanning atmospheric sounder which will observe the atmosphere of Mars globally from 0 to 80 km for a full Martian year. PMIRR employs narrow-band radiometric channels and two pressure modulation cells to measure atmospheric and surface emission in the thermal infrared. PMIRR infrared and visible measurements will be combined to determine the radiative balance of the polar regions, where a sizeable fraction of the global atmospheric mass annually condenses onto and sublimes from the surface. Derived meteorological fields, including diabatic heating and cooling and the vertical variation of horizontal winds, are computed from the globally mapped fields retrieved from PMIRR data.

Mechanical Description of the Mars Climate Sounder Instrument

NASA Technical Reports Server (NTRS)

Jau, Bruno M.

2008-01-01

This paper introduces the Mars Climate Sounder (MCS) Instrument of the Mars Reconnaissance Orbiter (MRO) spacecraft. The instrument scans the Martian atmosphere almost continuously to systematically acquire weather and climate observations over time. Its primary components are an optical bench that houses dual telescopes with a total of nine channels for visible and infrared sensing, and a two axis gimbal that provides pointing capabilities. Both rotating joints consist of an integrated actuator with a hybrid planetary/harmonic transmission and a twist cap section that enables the electrical wiring to pass through the rotating joint. Micro stepping is used to reduce spacecraft disturbance torques to acceptable levels while driving the stepper motors. To ensure survivability over its four year life span, suitable mechanical components, lubrication, and an active temperature control system were incorporated. Some life test results and lessons learned are provided to serve as design guidelines for actuator parts and flex cables.

Implications of freshwater flux data from the CMIP5 multimodel output across a set of Northern Hemisphere drainage basins

NASA Astrophysics Data System (ADS)

Bring, Arvid; Asokan, Shilpa M.; Jaramillo, Fernando; Jarsjö, Jerker; Levi, Lea; Pietroń, Jan; Prieto, Carmen; Rogberg, Peter; Destouni, Georgia

2015-06-01

The multimodel ensemble of the Coupled Model Intercomparison Project, Phase 5 (CMIP5) synthesizes the latest research in global climate modeling. The freshwater system on land, particularly runoff, has so far been of relatively low priority in global climate models, despite the societal and ecosystem importance of freshwater changes, and the science and policy needs for such model output on drainage basin scales. Here we investigate the implications of CMIP5 multimodel ensemble output data for the freshwater system across a set of drainage basins in the Northern Hemisphere. Results of individual models vary widely, with even ensemble mean results differing greatly from observations and implying unrealistic long-term systematic changes in water storage and level within entire basins. The CMIP5 projections of basin-scale freshwater fluxes differ considerably more from observations and among models for the warm temperate study basins than for the Arctic and cold temperate study basins. In general, the results call for concerted research efforts and model developments for improving the understanding and modeling of the freshwater system and its change drivers. Specifically, more attention to basin-scale water flux analyses should be a priority for climate model development, and an important focus for relevant model-based advice for adaptation to climate change.

INVENTORY AND ASSESSMENT OF CLIMATE SENSITIVE DECISIONS

EPA Science Inventory

The project will create a pilot inventory of climate-sensitive resource managment decision. The project will develop and demonstrate a new approach to collecting systematic information about the context and characteristics of climate-sensitive decisions and using this informatio...

The Effectiveness of Public Health Interventions to Reduce the Health Impact of Climate Change: A Systematic Review of Systematic Reviews

PubMed Central

Bouzid, Maha; Hooper, Lee; Hunter, Paul R.

2013-01-01

Background Climate change is likely to be one of the most important threats to public health in the coming years. Yet despite the large number of papers considering the health impact of climate change, few have considered what public health interventions may be of most value in reducing the disease burden. We aimed to evaluate the effectiveness of public health interventions to reduce the disease burden of high priority climate sensitive diseases. Methods and Findings For each disease, we performed a systematic search with no restriction on date or language of publication on Medline, Web of Knowledge, Cochrane CENTRAL and SCOPUS up to December 2010 to identify systematic reviews of public health interventions. We retrieved some 3176 records of which 85 full papers were assessed and 33 included in the review. The included papers investigated the effect of public health interventions on various outcome measures. All interventions were GRADE assessed to determine the strength of evidence. In addition we developed a systematic review quality score. The interventions included environmental interventions to control vectors, chemoprophylaxis, immunization, household and community water treatment, greening cities and community advice. For most reviews, GRADE showed low quality of evidence because of poor study design and high heterogeneity. Also for some key areas such as floods, droughts and other weather extremes, there are no adequate systematic reviews of potential public health interventions. Conclusion In conclusion, we found the evidence base to be mostly weak for environmental interventions that could have the most value in a warmer world. Nevertheless, such interventions should not be dismissed. Future research on public health interventions for climate change adaptation needs to be concerned about quality in study design and should address the gap for floods, droughts and other extreme weather events that pose a risk to health. PMID:23634220

The Importance of the Spatial Density of Satellite Measurements for the Retrieval of Spatial Flux Patterns

NASA Astrophysics Data System (ADS)

Marshall, J.; Nuñez Ramirez, T. G.; Kiemle, C.; Butz, A.; Hasekamp, O. P.; Ehret, G.; Heimann, M.

2014-12-01

Black carbon is one of the key short-lived climate pollutants, which is a topic of growing interest for near-term mitigation of climate change and air quality improvement. In this presentation we will examine the emissions and impact of black carbon and co-pollutants on the South American glacial region and describe some recent measurements associated with the PISAC (Pollution and its Impacts on the South American Cryosphere) Initiative. The Andes is the longest continental mountain range in the world, extending about 7000 km along western South America through seven countries with complex topography and covering several climate zones, diversity of ecosystems and communities. Air pollution associated with biomass burning and urban emissions affects extensive areas in the region and is a serious public health concern. Scientific evidence indicates that the Andean cryosphere is changing rapidly as snow fields and glaciers generally recede, leading to changes in stream flow and water quality along the Andes. The challenge is to identify the principal causes of the observed changes so that action can be taken to mitigate this negative trend. Despite the paucity of systematic observations along the Andes, a few modeling and observational studies have indicated the presence of black carbon in the high Andes, with potentially significant impact on the Andean cryosphere.

Black Carbon Emissions and Impacts on the South American Glacial Region

NASA Astrophysics Data System (ADS)

Molina, L. T.; Gallardo, L.; Schmitt, C. G.

2015-12-01

Black carbon is one of the key short-lived climate pollutants, which is a topic of growing interest for near-term mitigation of climate change and air quality improvement. In this presentation we will examine the emissions and impact of black carbon and co-pollutants on the South American glacial region and describe some recent measurements associated with the PISAC (Pollution and its Impacts on the South American Cryosphere) Initiative. The Andes is the longest continental mountain range in the world, extending about 7000 km along western South America through seven countries with complex topography and covering several climate zones, diversity of ecosystems and communities. Air pollution associated with biomass burning and urban emissions affects extensive areas in the region and is a serious public health concern. Scientific evidence indicates that the Andean cryosphere is changing rapidly as snow fields and glaciers generally recede, leading to changes in stream flow and water quality along the Andes. The challenge is to identify the principal causes of the observed changes so that action can be taken to mitigate this negative trend. Despite the paucity of systematic observations along the Andes, a few modeling and observational studies have indicated the presence of black carbon in the high Andes, with potentially significant impact on the Andean cryosphere.

Climate Change and the Canadian Higher Education System: An Institutional Policy Analysis

ERIC Educational Resources Information Center

Henderson, Joseph; Bieler, Andrew; McKenzie, Marcia

2017-01-01

Climate change is a pressing concern. Higher education can address the challenge, but systematic analyses of climate change in education policy are sparse. This paper addresses this gap in the literature by reporting on how Canadian postsecondary educational institutions have engaged with climate change through policy actions. We used descriptive…

Process-level improvements in CMIP5 models and their impact on tropical variability, the Southern Ocean, and monsoons

NASA Astrophysics Data System (ADS)

Lauer, Axel; Jones, Colin; Eyring, Veronika; Evaldsson, Martin; Hagemann, Stefan; Mäkelä, Jarmo; Martin, Gill; Roehrig, Romain; Wang, Shiyu

2018-01-01

The performance of updated versions of the four earth system models (ESMs) CNRM, EC-Earth, HadGEM, and MPI-ESM is assessed in comparison to their predecessor versions used in Phase 5 of the Coupled Model Intercomparison Project. The Earth System Model Evaluation Tool (ESMValTool) is applied to evaluate selected climate phenomena in the models against observations. This is the first systematic application of the ESMValTool to assess and document the progress made during an extensive model development and improvement project. This study focuses on the South Asian monsoon (SAM) and the West African monsoon (WAM), the coupled equatorial climate, and Southern Ocean clouds and radiation, which are known to exhibit systematic biases in present-day ESMs. The analysis shows that the tropical precipitation in three out of four models is clearly improved. Two of three updated coupled models show an improved representation of tropical sea surface temperatures with one coupled model not exhibiting a double Intertropical Convergence Zone (ITCZ). Simulated cloud amounts and cloud-radiation interactions are improved over the Southern Ocean. Improvements are also seen in the simulation of the SAM and WAM, although systematic biases remain in regional details and the timing of monsoon rainfall. Analysis of simulations with EC-Earth at different horizontal resolutions from T159 up to T1279 shows that the synoptic-scale variability in precipitation over the SAM and WAM regions improves with higher model resolution. The results suggest that the reasonably good agreement of modeled and observed mean WAM and SAM rainfall in lower-resolution models may be a result of unrealistic intensity distributions.

The permafrost carbon inventory on the Tibetan Plateau: a new evaluation using deep sediment cores

NASA Astrophysics Data System (ADS)

Yang, Y.; Ding, J.; Li, F.; Yang, G.; Chen, L.

2016-12-01

The permafrost organic carbon (OC) stock is of global significance because of its large pool size and potential positive feedback to climate warming. However, due to the lack of systematic field observations and appropriate upscaling methodologies, substantial uncertainties exist in the permafrost OC budget, which limits our understanding on the fate of frozen carbon in a warming world. In particular, the lack of comprehensive estimation of OC stock across alpine permafrost means that the current knowledge on this issue remains incomplete. Here we evaluated the pool size and spatial variations of permafrost OC stock to 3 meters depth on the Tibetan Plateau by combining systematic measurements from a substantial number of pedons (i.e., 342 three-meter-deep cores and 177 50-cm-deep pits) with a machine learning technique (i.e., support vector machine, SVM). We also quantified uncertainties in permafrost carbon budget by conducting Monte Carlo simulation. Our results revealed that the combination of systematic measurements with the SVM model allowed spatially explicit estimates. The OC density (OC amount per unit area, OCD) exhibited a decreasing trend from the southeastern to the northwestern plateau, with the exception that OCD in the swamp meadow was substantially higher than that in surrounding regions. Our results also demonstrated that Tibetan permafrost stored a large amount of OC in the top 3 meters, with the median OC pool size being 15.31 Pg C (interquartile range: 13.03-17.77 Pg C). Of them, 44% occurred in deep layers (i.e., 100-300 cm), close to the proportion observed across the northern circumpolar permafrost region. The large carbon pool size, together with significant permafrost thawing implies a risk of carbon emissions and positive climate feedback across the Tibetan alpine permafrost region.

Towards improved and more routine Earth system model evaluation in CMIP

DOE PAGES

Eyring, Veronika; Gleckler, Peter J.; Heinze, Christoph; ...

2016-11-01

The Coupled Model Intercomparison Project (CMIP) has successfully provided the climate community with a rich collection of simulation output from Earth system models (ESMs) that can be used to understand past climate changes and make projections and uncertainty estimates of the future. Confidence in ESMs can be gained because the models are based on physical principles and reproduce many important aspects of observed climate. More research is required to identify the processes that are most responsible for systematic biases and the magnitude and uncertainty of future projections so that more relevant performance tests can be developed. At the same time,more » there are many aspects of ESM evaluation that are well established and considered an essential part of systematic evaluation but have been implemented ad hoc with little community coordination. Given the diversity and complexity of ESM analysis, we argue that the CMIP community has reached a critical juncture at which many baseline aspects of model evaluation need to be performed much more efficiently and consistently. We provide a perspective and viewpoint on how a more systematic, open, and rapid performance assessment of the large and diverse number of models that will participate in current and future phases of CMIP can be achieved, and announce our intention to implement such a system for CMIP6. Accomplishing this could also free up valuable resources as many scientists are frequently "re-inventing the wheel" by re-writing analysis routines for well-established analysis methods. A more systematic approach for the community would be to develop and apply evaluation tools that are based on the latest scientific knowledge and observational reference, are well suited for routine use, and provide a wide range of diagnostics and performance metrics that comprehensively characterize model behaviour as soon as the output is published to the Earth System Grid Federation (ESGF). The CMIP infrastructure enforces data standards and conventions for model output and documentation accessible via the ESGF, additionally publishing observations (obs4MIPs) and reanalyses (ana4MIPs) for model intercomparison projects using the same data structure and organization as the ESM output. This largely facilitates routine evaluation of the ESMs, but to be able to process the data automatically alongside the ESGF, the infrastructure needs to be extended with processing capabilities at the ESGF data nodes where the evaluation tools can be executed on a routine basis. Efforts are already underway to develop community-based evaluation tools, and we encourage experts to provide additional diagnostic codes that would enhance this capability for CMIP. And, at the same time, we encourage the community to contribute observations and reanalyses for model evaluation to the obs4MIPs and ana4MIPs archives. The intention is to produce through the ESGF a widely accepted quasi-operational evaluation framework for CMIP6 that would routinely execute a series of standardized evaluation tasks. Over time, as this capability matures, we expect to produce an increasingly systematic characterization of models which, compared with early phases of CMIP, will more quickly and openly identify the strengths and weaknesses of the simulations. This will also reveal whether long-standing model errors remain evident in newer models and will assist modelling groups in improving their models. Finally, this framework will be designed to readily incorporate updates, including new observations and additional diagnostics and metrics as they become available from the research community.« less

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

Gharbia, Salem S; Smullen, Trevor; Gill, Laurence; Johnston, Paul; Pilla, Francesco

2018-08-15

Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m 2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Climate Downscaling over Nordeste, Brazil, Using the NCEP RSM97.

NASA Astrophysics Data System (ADS)

Sun, Liqiang; Ferran Moncunill, David; Li, Huilan; Divino Moura, Antonio; de Assis de Souza Filho, Francisco

2005-02-01

The NCEP Regional Spectral Model (RSM), with horizontal resolution of 60 km, was used to downscale the ECHAM4.5 AGCM (T42) simulations forced with observed SSTs over northeast Brazil. An ensemble of 10 runs for the period January-June 1971-2000 was used in this study. The RSM can resolve the spatial patterns of observed seasonal precipitation and capture the interannual variability of observed seasonal precipitation as well. The AGCM bias in displacement of the Atlantic ITCZ is partially corrected in the RSM. The RSM probability distribution function of seasonal precipitation anomalies is in better agreement with observations than that of the driving AGCM. Good potential prediction skills are demonstrated by the RSM in predicting the interannual variability of regional seasonal precipitation. The RSM can also capture the interannual variability of observed precipitation at intraseasonal time scales, such as precipitation intensity distribution and dry spells. A drought index and a flooding index were adopted to indicate the severity of drought and flooding conditions, and their interannual variability was reproduced by the RSM. The overall RSM performance in the downscaled climate of the ECHAM4.5 AGCM is satisfactory over Nordeste. The primary deficiency is a systematic dry bias for precipitation simulation.

Advancing Climate Change Education: Student Engagement and Teacher Talk in the Classroom

NASA Astrophysics Data System (ADS)

Holthuis, N.; Saltzman, J.; Lotan, R.; Mastrandrea, M. D.; Diffenbaugh, P.; Gray, S.; Kloser, M.

2011-12-01

Stanford's Global Climate Change: Professional Development for K-12 Teachers is a unique collaboration between the Stanford School of Education and School of Earth Sciences to provide teacher professional development on the science of global climate change, pedagogical strategies, and curriculum materials. Scientists and education specialists developed a curriculum for middle and high school science classrooms. It addresses the fundamental issues of climate science, the impacts of climate change on society and on global resources, mitigation and adaptation strategies. This project documents in detail the full circle of curriculum development, teacher professional development, classroom implementation, analysis of student achievement data, and curriculum revision. Ongoing evaluation has provided understanding of the unique conditions and requirements of climate change education. In a sample of 750 secondary students in 25 Bay Area classrooms, we found statistically significant differences between post- (x=11.56, sd=4.75) and pre- (x=8.64, sd=4.58) test scores on standardized items and short open-ended essay questions. Through systematic classroom observations (300 observations in 25 classrooms), we documented student engagement and interactions, and the nature of teachers' talk in the classroom. We found that on average, 73.4% of the students were engaged, 14.4% were interacting with peers, and about 12.1% were disengaged. We also documented teacher talk (165 observations) and found that on the average, teachers delivered factual content and talked about classroom processes and spent less time on scientific argumentation, reasoning and/ or analysis. We documented significant differences in the quality of implementation among the teachers. Our study suggests that in addition to strengthening content knowledge and pedagogical content knowledge, professional development for teachers needs to include classroom management strategies, explicit modeling of collaborative work, and greater attention to the quality of teachers' questions and interactions with the students to enhance the quality of student talk and understanding. In our final year of the project, we will focus our observations more tightly on the nature of teacher and student talk to explore student understanding of climate change.

Overview of the Special Issue: A Multi-Model Framework to Achieve Consistent Evaluation of Climate Change Impacts in the United States

EPA Science Inventory

The Climate Change Impacts and Risk Analysis (CIRA) project establishes a new multi-model framework to systematically assess the impacts, economic damages, and risks from climate change in the United States. The primary goal of this framework to estimate how climate change impac...

Heat Exposure and Maternal Health in the Face of Climate Change

PubMed Central

Kuehn, Leeann; McCormick, Sabrina

2017-01-01

Climate change will increasingly affect the health of vulnerable populations, including maternal and fetal health. This systematic review aims to identify recent literature that investigates increasing heat and extreme temperatures on pregnancy outcomes globally. We identify common research findings in order to create a comprehensive understanding of how immediate effects will be sustained in the next generation. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guide, we systematically reviewed articles from PubMed and Cochrane Reviews. We included articles that identify climate change-related exposures and adverse health effects for pregnant women. There is evidence that temperature extremes adversely impact birth outcomes, including, but not limited to: changes in length of gestation, birth weight, stillbirth, and neonatal stress in unusually hot temperature exposures. The studies included in this review indicate that not only is there a need for further research on the ways that climate change, and heat in particular, may affect maternal health and neonatal outcomes, but that uniform standards for assessing the effects of heat on maternal fetal health also need to be established. PMID:28758917

Heat Exposure and Maternal Health in the Face of Climate Change.

PubMed

Kuehn, Leeann; McCormick, Sabrina

2017-07-29

Climate change will increasingly affect the health of vulnerable populations, including maternal and fetal health. This systematic review aims to identify recent literature that investigates increasing heat and extreme temperatures on pregnancy outcomes globally. We identify common research findings in order to create a comprehensive understanding of how immediate effects will be sustained in the next generation. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guide, we systematically reviewed articles from PubMed and Cochrane Reviews. We included articles that identify climate change-related exposures and adverse health effects for pregnant women. There is evidence that temperature extremes adversely impact birth outcomes, including, but not limited to: changes in length of gestation, birth weight, stillbirth, and neonatal stress in unusually hot temperature exposures. The studies included in this review indicate that not only is there a need for further research on the ways that climate change, and heat in particular, may affect maternal health and neonatal outcomes, but that uniform standards for assessing the effects of heat on maternal fetal health also need to be established.

Does climate have heavy tails?

NASA Astrophysics Data System (ADS)

Bermejo, Miguel; Mudelsee, Manfred

2013-04-01

When we speak about a distribution with heavy tails, we are referring to the probability of the existence of extreme values will be relatively large. Several heavy-tail models are constructed from Poisson processes, which are the most tractable models. Among such processes, one of the most important are the Lévy processes, which are those process with independent, stationary increments and stochastic continuity. If the random component of a climate process that generates the data exhibits a heavy-tail distribution, and if that fact is ignored by assuming a finite-variance distribution, then there would be serious consequences (in the form, e.g., of bias) for the analysis of extreme values. Yet, it appears that it is an open question to what extent and degree climate data exhibit heavy-tail phenomena. We present a study about the statistical inference in the presence of heavy-tail distribution. In particular, we explore (1) the estimation of tail index of the marginal distribution using several estimation techniques (e.g., Hill estimator, Pickands estimator) and (2) the power of hypothesis tests. The performance of the different methods are compared using artificial time-series by means of Monte Carlo experiments. We systematically apply the heavy tail inference to observed climate data, in particular we focus on time series data. We study several proxy and directly observed climate variables from the instrumental period, the Holocene and the Pleistocene. This work receives financial support from the European Commission (Marie Curie Initial Training Network LINC, No. 289447, within the 7th Framework Programme).

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

DOE PAGES

Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.; ...

2017-01-31

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

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

Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less

Could geoengineering research help answer one of the biggest questions in climate science?: GEOENGINEERING RESEARCH

DOE PAGES

Wood, Robert; Ackerman, Thomas; Rasch, Philip J.; ...

2017-06-22

Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in quantifying the radiative forcing of climate, and hinders our ability to determine Earth's climate sensitivity to greenhouse gas increases. Representation of aerosol–cloud interactions in global models is particularly challenging because these interactions occur on typically unresolved scales. Observational studies show influences of aerosol on clouds, but correlations between aerosol and clouds are insufficient to constrain aerosol forcing because of the difficulty in separating aerosol and meteorological impacts. In this commentary, we argue that this current impasse may be overcome with the development of approaches to conduct control experimentsmore » whereby aerosol particle perturbations can be introduced into patches of marine low clouds in a systematic manner. Such cloud perturbation experiments constitute a fresh approach to climate science and would provide unprecedented data to untangle the effects of aerosol particles on cloud microphysics and the resulting reflection of solar radiation by clouds. Here, the control experiments would provide a critical test of high-resolution models that are used to develop an improved representation aerosol–cloud interactions needed to better constrain aerosol forcing in global climate models.« less

Could geoengineering research help answer one of the biggest questions in climate science?: GEOENGINEERING RESEARCH

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

Wood, Robert; Ackerman, Thomas; Rasch, Philip J.

Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in quantifying the radiative forcing of climate, and hinders our ability to determine Earth's climate sensitivity to greenhouse gas increases. Representation of aerosol–cloud interactions in global models is particularly challenging because these interactions occur on typically unresolved scales. Observational studies show influences of aerosol on clouds, but correlations between aerosol and clouds are insufficient to constrain aerosol forcing because of the difficulty in separating aerosol and meteorological impacts. In this commentary, we argue that this current impasse may be overcome with the development of approaches to conduct control experimentsmore » whereby aerosol particle perturbations can be introduced into patches of marine low clouds in a systematic manner. Such cloud perturbation experiments constitute a fresh approach to climate science and would provide unprecedented data to untangle the effects of aerosol particles on cloud microphysics and the resulting reflection of solar radiation by clouds. Here, the control experiments would provide a critical test of high-resolution models that are used to develop an improved representation aerosol–cloud interactions needed to better constrain aerosol forcing in global climate models.« less

Assessing Flood Risk at Nuclear Power Plants with an Uncertain Climate

NASA Astrophysics Data System (ADS)

Wigmosta, M. S.; Vail, L. W.

2011-12-01

In 2010 a tsunami severely damaged the Fukushima Dai-ichi Nuclear Power Plant in Japan. As a result, the U.S. Nuclear Regulatory Commission directed that a systematic and methodical review of Commission processes and regulations be performed to determine whether the agency should make additional improvements to its regulatory system and to make recommendations to the Commission. Two of the recommendations of the Task Force created to inform the Commission were: establish a logical, systematic, and coherent regulatory framework for adequate protection that appropriately balances defense-in-depth and risk considerations and that the NRC require licensees to reevaluate and upgrade as necessary the design-basis flooding protection of structures, systems, and components for each operating reactor. These recommendations came at the same time as technical discussions about updating approaches to evaluate flood hazard were underway. These discussions included: consideration of climate nonstationarity in flood assessments; transitioning from PMP/PMF assessments to probabilistic flood analyses to better align with risk-informed decision making; and systematic consideration of combined events in flood risk analysis. There is no scientific basis to assume that shifts in long-term mean precipitation and temperature (such as is commonly derived from climate models) relate to flood probability. Flood mechanisms are often more complex and reflect climate pattern anomalies more than mean annual shifts. Instead of discounting historical data due to climatic nonstationarity, it is important to better understand the climate patterns that have triggered floods in the past and to look to climate forecasts to understand the likely changes in the frequency of those historical climate patterns with climate change. It is equally important to have a better understanding of whether climate change will result in flood-generating climate systems heretofore unknown in the particular locale. This presentation will provide a roadmap to ensuring that the flood hazards of existing and future nuclear power plants are well defined.

New early instrumental series since the beginning of the 19th century in eastern Iberia (Valencia, Spain)

NASA Astrophysics Data System (ADS)

Sanchez-Lorenzo, Arturo; Barriendos, Mariano; Guinaldo, Elena; Lopez-Bustins, Joan A.

2010-05-01

Early instrumental series are the main source for climate information in the 18th and the first part of the 19th century, which is when systematic meteorological observations started in most national meteorological services. The first continuous series in Spain starts in 1780 in Barcelona due to meteorological observations made by the medical doctor Francisco Salvá Campillo. Moreover, only two other series have been recovered at the present in Spain: Madrid and Cádiz/San Fernando. Until present, in Spain the major part of the meteorological observations detected in early instrumental periods were made by medical doctors, who started to pay attention to the environmental factors influencing population health under the Hippocrates oath, although also there are military institutions and academic university staff (e.g. physicists, mathematicians, etc.). Due to the high spatial and temporal climate variability in the Iberian Peninsula, it is important to recover and digitize more climatic series, and this is one of the main goals of the Salvá-Sinobas project (http://salva-sinobas.uvigo.es/) funded by the Spanish Ministry of Environment, and Rural and Marine Affairs for the 2009-2011 period. The first new series with systematic observations was detected in the city of Valencia, in the eastern façade of the Iberian Peninsula. The meteorological observations were daily published in the newspapers Diario de Valencia (1804-1834) and Diario Mercantil de Valencia (1837-1863) until official meteorological observations started in 1858 at the University of Valencia. Each day 3-daily observations (morning, midday, afternoon) were published with five climatic variables: temperature, air pressure, humidity, wind direction and the sky state. Only during the 1804-1808 period daily rainfall data is available. We checked the observer comments published in the newspapers to obtain metadata about the instruments and meteorological station information. Unfortunately, temperature data was recorded indoor and unknown hygrometer was used during the first decades until 1841. One curious detail of the Valencia early instrumental series is that the records were initiated by a local clockmaker, a new profession interested in meteorological observations in Spain during this period. A great effort has been made to detect original manuscripts, but the archive revision did not provide encouraging results. We started to digitalize daily air pressure records, to improve atmospheric circulation reconstruction in the Mediterranean region, and the sky observations (defined as cloud free, cloudy or overcast conditions), since we are interested into reconstruct cloud cover variability since early 19th century in Valencia. Finally, due to the lack of metadata about wind direction, we tried to assess the reliability of these measurements using the daily Western Mediterranean Oscillation index (WeMOi), a regional circulation pattern in the western Mediterranean basin. Wind direction records in Valencia were registered in 32 class intervals. The negative phase of the WeMOi is linked to those intervals associated to easterly humid flows.

Ocean heat content and ocean energy budget: make better use of historical global subsurface temperature dataset

NASA Astrophysics Data System (ADS)

Cheng, L.; Zhu, J.

2016-02-01

Ocean heat content (OHC) change contributes substantially to global sea level rise, also is a key metric of the ocean/global energy budget, so it is a vital task for the climate research community to estimate historical OHC. While there are large uncertainties regarding its value, here we review the OHC calculation by using the historical global subsurface temperature dataset, and discuss the sources of its uncertainty. The presentation briefly introduces how to correct to the systematic biases in expendable bathythermograph (XBT) data, a alternative way of filling data gaps (which is main focus of this talk), and how to choose a proper climatology. A new reconstruction of historical upper (0-700 m) OHC change will be presented, which is the Institute of Atmospheric Physics (IAP) version of historical upper OHC assessment. The authors also want to highlight the impact of observation system change on OHC calculation, which could lead to bias in OHC estimates. Furthermore, we will compare the updated observational-based estimates on ocean heat content change since 1970s with CMIP5 results. This comparison shows good agreement, increasing the confidence of the climate models in representing the climate history.

Using Co-production to Enhance Co-production: Cultivating institutional capacity through exchange between climate science, social science, and practice

NASA Astrophysics Data System (ADS)

Kalafatis, S.

2015-12-01

Many climate scientists and boundary organizations have accumulated years of experience providing decision support for climate adaptation related to landscape change. The Great Lakes Integrated Sciences + Assessments (GLISA) is one such organization that has developed a reputation for providing stakeholders with climate change decision support throughout the Great Lakes region of North America. After five years of applied outreach, GLISA climate scientists working with practitioners identified three common limitations across projects that were slowing down the use of information, describing them as mismatched terminology, unrealistic expectations, and disordered integration. Discussions with GLISA-affiliated social scientists revealed compelling parallels between these observations and the existing social science literature on the persistent "usability gap" in information use as well as opportunities to preemptively overcome these barriers. The discovery of these overlaps between the climate scientists' experience of barriers and the social science literature as well as strategies to systematically address them demonstrate the potential for boundary organizations to act as incubators of more and more efficient co-production over time. To help illustrate these findings, this presentation also provides an example of decision-making for adaptation in the face of landscape change in which GLISA scientists assisted Isle Royale National Park with assessing the implications of future ecological transitions for current wildlife management efforts.

Global Framework for Climate Services (GFCS): status of implementation

NASA Astrophysics Data System (ADS)

Lucio, Filipe

2014-05-01

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.

Using MERRA Gridded Innovations for Quantifying Uncertainties in Analysis Fields and Diagnosing Observing System Inhomogeneities

NASA Technical Reports Server (NTRS)

da Silva, Arlindo; Redder, Christopher

2010-01-01

MERRA is a NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5). The project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales and places the NASA EOS suite of observations in a climate context. The characterization of uncertainty in reanalysis fields is a commonly requested feature by users of such data. While intercomparison with reference data sets is common practice for ascertaining the realism of the datasets, such studies typically are restricted to long term climatological statistics and seldom provide state dependent measures of the uncertainties involved. In principle, variational data assimilation algorithms have the ability of producing error estimates for the analysis variables (typically surface pressure, winds, temperature, moisture and ozone) consistent with the assumed background and observation error statistics. However, these "perceived error estimates" are expensive to obtain and are limited by the somewhat simplistic errors assumed in the algorithm. The observation minus forecast residuals (innovations) by-product of any assimilation system constitutes a powerful tool for estimating the systematic and random errors in the analysis fields. Unfortunately, such data is usually not readily available with reanalysis products, often requiring the tedious decoding of large datasets and not so-user friendly file formats. With MERRA we have introduced a gridded version of the observations/innovations used in the assimilation process, using the same grid and data formats as the regular datasets. Such dataset empowers the user with the ability of conveniently performing observing system related analysis and error estimates. The scope of this dataset will be briefly described. We will present a systematic analysis of MERRA innovation time series for the conventional observing system, including maximum-likelihood estimates of background and observation errors, as well as global bias estimates. Starting with the joint PDF of innovations and analysis increments at observation locations we propose a technique for diagnosing bias among the observing systems, and document how these contextual biases have evolved during the satellite era covered by MERRA.

Using MERRA Gridded Innovation for Quantifying Uncertainties in Analysis Fields and Diagnosing Observing System Inhomogeneities

NASA Astrophysics Data System (ADS)

da Silva, A.; Redder, C. R.

2010-12-01

MERRA is a NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5). The Project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales and places the NASA EOS suite of observations in a climate context. The characterization of uncertainty in reanalysis fields is a commonly requested feature by users of such data. While intercomparison with reference data sets is common practice for ascertaining the realism of the datasets, such studies typically are restricted to long term climatological statistics and seldom provide state dependent measures of the uncertainties involved. In principle, variational data assimilation algorithms have the ability of producing error estimates for the analysis variables (typically surface pressure, winds, temperature, moisture and ozone) consistent with the assumed background and observation error statistics. However, these "perceived error estimates" are expensive to obtain and are limited by the somewhat simplistic errors assumed in the algorithm. The observation minus forecast residuals (innovations) by-product of any assimilation system constitutes a powerful tool for estimating the systematic and random errors in the analysis fields. Unfortunately, such data is usually not readily available with reanalysis products, often requiring the tedious decoding of large datasets and not so-user friendly file formats. With MERRA we have introduced a gridded version of the observations/innovations used in the assimilation process, using the same grid and data formats as the regular datasets. Such dataset empowers the user with the ability of conveniently performing observing system related analysis and error estimates. The scope of this dataset will be briefly described. We will present a systematic analysis of MERRA innovation time series for the conventional observing system, including maximum-likelihood estimates of background and observation errors, as well as global bias estimates. Starting with the joint PDF of innovations and analysis increments at observation locations we propose a technique for diagnosing bias among the observing systems, and document how these contextual biases have evolved during the satellite era covered by MERRA.

Quantitative study of long-term solar and climatic changes

NASA Technical Reports Server (NTRS)

Eddy, J. A.

1982-01-01

Long term variations in the diameter and the shape of the Sun were studied. Daily observations of the Sun's diameter made at the Greenwich Observatory between 1836 and 1953 were analysed and interpreted. The data was converted into digital form and then screened and processed. It was found that the horizontal diameter of the Sun measured at Greenwich appears to have decreased systematically between 1880 and 1953 at a rate of 1.2 plus or minus 0.6 minutes of arc per century.

Improving Global Modeling and Data Analysis Using Remotely-Sensed Rainfall Data: Lessons From TRMM and Plans for GPM

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Einaudi, Franco (Technical Monitor)

2001-01-01

I will discuss the need for accurate rainfall observations to improve our ability to model the earth's climate and improve short-range weather forecasts. I will give an overview of the recent progress in using of rainfall data provided by TRMM and other microwave instruments in data assimilation to improve global analyses and diagnose state-dependent systematic errors in physical parameterizations. I will outline the current and future research strategies in preparation for the Global Precipitation Mission.

Impacts of snow on soil temperature observed across the circumpolar north

NASA Astrophysics Data System (ADS)

Zhang, Yu; Sherstiukov, Artem B.; Qian, Budong; Kokelj, Steven V.; Lantz, Trevor C.

2018-04-01

Climate warming has significant impacts on permafrost, infrastructure and soil organic carbon at the northern high latitudes. These impacts are mainly driven by changes in soil temperature (TS). Snow insulation can cause significant differences between TS and air temperature (TA), and our understanding about this effect through space and time is currently limited. In this study, we compiled soil and air temperature observations (measured at about 0.2 m depth and 2 m height, respectively) at 588 sites from climate stations and boreholes across the northern high latitudes. Analysis of this circumpolar dataset demonstrates the large offset between mean TS and TA in the low arctic and northern boreal regions. The offset decreases both northward and southward due to changes in snow conditions. Correlation analysis shows that the coupling between annual TS and TA is weaker, and the response of annual TS to changes in TA is smaller in boreal regions than in the arctic and the northern temperate regions. Consequently, the inter-annual variation and the increasing trends of annual TS are smaller than that of TA in boreal regions. The systematic and significant differences in the relationship between TS and TA across the circumpolar north is important for understanding and assessing the impacts of climate change and for reconstruction of historical climate based on ground temperature profiles for the northern high latitudes.

Mitigation strategies and unforseen consequences: A systematic assessment of the adaption of upper midwest agriculture to future climate change

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

Doering, O.; Lowenberg-DeBoer, J.; Habeck, M.

1997-12-31

Our starting point is the assumption of global climate change that doubles CO{sub 2} in the Upper Midwest by 2050. This work then concentrates on determining agriculture in the Upper Midwest successfully adapts to such a climate change.

Trends in Extreme Rainfall Frequency in the Contiguous United States: Attribution to Climate Change and Climate Variability Modes

NASA Astrophysics Data System (ADS)

Armal, S.; Devineni, N.; Khanbilvardi, R.

2017-12-01

This study presents a systematic analysis for identifying and attributing trends in the annual frequency of extreme rainfall events across the contiguous United States to climate change and climate variability modes. A Bayesian multilevel model is developed for 1,244 stations simultaneously to test the null hypothesis of no trend and verify two alternate hypotheses: Trend can be attributed to changes in global surface temperature anomalies, or to a combination of cyclical climate modes with varying quasi-periodicities and global surface temperature anomalies. The Bayesian multilevel model provides the opportunity to pool information across stations and reduce the parameter estimation uncertainty, hence identifying the trends better. The choice of the best alternate hypotheses is made based on Watanabe-Akaike Information Criterion, a Bayesian pointwise predictive accuracy measure. Statistically significant time trends are observed in 742 of the 1,244 stations. Trends in 409 of these stations can be attributed to changes in global surface temperature anomalies. These stations are predominantly found in the Southeast and Northeast climate regions. The trends in 274 of these stations can be attributed to the El Nino Southern Oscillations, North Atlantic Oscillation, Pacific Decadal Oscillation and Atlantic Multi-Decadal Oscillation along with changes in global surface temperature anomalies. These stations are mainly found in the Northwest, West and Southwest climate regions.

Sensitivity of the Tropical Atmosphere Energy Balance to ENSO-Related SST Changes: How Well Can We Quantify Hydrologic and Radiative Responses?

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Fitzjarrald, Dan; Sohn, Byung-Ju; Arnold, James E. (Technical Monitor)

2001-01-01

The continuing debate over feedback mechanisms governing tropical sea surface temperatures (SSTs) and tropical climate in general has highlighted the diversity of potential checks and balances within the climate system. Competing feedbacks due to changes in surface evaporation, water vapor, and cloud long- and shortwave radiative properties each may serve critical roles in stabilizing or destabilizing the climate system. It is also intriguing that even those climate variations having origins internal to the climate system-- changes in ocean heat transport for example, apparently require complementary equilibrating effects by changes in atmospheric energy fluxes. Perhaps the best observational evidence of this is the relatively invariant nature of tropically averaged net radiation exiting the top-of-atmosphere (TOA) as measured by broadband satellite sensors over the past two decades. Thus, analyzing how these feedback mechanisms are operating within the context of current interannual variability may offer considerable insight for anticipating future climate change. In this paper we focus on how fresh water and radiative fluxes over the tropical oceans change during ENSO warm and cold events and how these changes affect the tropical energy balance. At present, ENSO remains the most prominent known mode of natural variability at interannual time scales. Although great advances have been made in understanding this phenomenon and realizing prediction skill over the past decade, our ability to document the coupled water and energy changes observationally and to represent them in climate models seems far from settled (Soden, 2000 J Climate). Our analysis makes use a number of data bases, principally those derived from space-based measurements, to explore systematic changes in rainfall, evaporation, and surface and top-of-atmosphere (TOA) radiative fluxes, A reexamination of the Langley 8-Year Surface Radiation Budget data set reveals errors in the surface longwave emission due to use of biased SSTs. Subsequent correction allows subsequent use of this data set along with ERBE TOA fluxes to infer net atmospheric radiative beating. Further analysis of recent rainfall algorithms provides new estimates for precipitation variability in line with interannual evaporation changes inferred from the da Silva, Young, Levitus COADS analysis. The overall results from our analysis suggest an increase (decrease) of the hydrologic cycle during ENSO warm (cold) events at the rate of about 5 Wm-2 per K of SST change. This rate is slightly less than that which would be expected for constant relative humidity over the tropical oceans. Corresponding radiative fluxes seem systematically smaller resulting in a enhanced (suppressed) export of energy from the tropical ocean regions during warm (cold) SST events. Discussion of likely errors due to sampling and measurement strategies are discussed along with their impacts on our conclusions.

Monitoring the change of coastal zones from space

NASA Astrophysics Data System (ADS)

Cazenave, A. A.; Le Cozannet, G.; Benveniste, J.; Woodworth, P. L.

2017-12-01

The world's coastal zones, where an important fraction of the world population is currently living, are under serious threat because of coastal erosion, cyclones, storms, and salinization of estuaries and coastal aquifers. In the future, these hazards are expected to increase due to the combined effects of sea level rise, climate change, human activities and population increase. The response of coastal environments to natural and anthropogenic forcing factors (including climate change) depends on the characteristics of the forcing agents, as well as on the internal properties of the coastal systems, that remain poorly known and mostly un-surveyed at global scale. To better understand changes affecting coastal zones and to provide useful information to decision makers, various types of observations with global coverage need to be collected and analysed. Observations from space appear as an important complement to existing in situ observing systems (e.g., regional tide gauge networks). In this presentation, we discuss the benefit of systematic coastal monitoring from space, addressing both observations of forcing agents and of the coastal response. We highlight the need for a global coastal sea level data set based on retracked nadir altimetry missions and new SAR technology.

Multi-year GNSS monitoring of atmospheric IWV over Central and South America for climate studies

NASA Astrophysics Data System (ADS)

Mendoza, Luciano; Bianchi, Clara; Fernández, Laura; Natali, María Paula; Meza, Amalia; Moirano, Juan

2017-04-01

Atmospheric water vapour has been acknowledged as an essential climate variable. Weather prediction and hazard assessment systems benefit from real-time observations, whereas long-term records contribute to climate studies. Nowadays, ground-based GNSS products have become widely employed, complementing satellite observations over the oceans. Although the past decade has seen a significant development of the GNSS infrastructure in Central and South America, its potential for atmospheric water vapour monitoring has not been fully exploited. With this in mind, we have performed a regional, seven-year long and homogeneous analysis, comprising 136 GNSS tracking stations, obtaining high-rate and continuous observations of column integrated water vapour and troposphere zenith total delay (Bianchi et al. 2016). As preliminary application for this data set, we have estimated local water vapour trends, their significance, and their relation with specific climate regimes. We have found evidence of drying at temperate regions in South America, at a rate of about 2% per decade, while a slow moistening of the troposphere over tropical regions is also weakly suggested by our results. Furthermore, we have assessed the regional performance of the empirical model GPT2w to blindly estimate troposphere delays. The model fairly reproduces the observed mean delays, including their annual and semi-annual variations. Nevertheless, a long-term evaluation has shown systematical biases, up to 20 mm, probably inherited form the underling atmospheric reanalysis. Additionally, the complete data set has been made openly available at a scientific repository (doi:10.1594/PANGAEA.858234). References: C. Bianchi, L. Mendoza, L. Fernandez, M. P. Natali, A. Meza, J. F. Moirano, Multi-year GNSS monitoring of atmospheric IWV over Central and South America for climate studies, Ann. Geophys., ISSN 0992-7689, eISSN 1432-0576, 34 (7), 623-639 (doi:10.5194/angeo-34-623-2016).

Positive tropical marine low-cloud cover feedback inferred from cloud-controlling factors

DOE PAGES

Qu, Xin; Hall, Alex; Klein, Stephen A.; ...

2015-09-28

Differences in simulations of tropical marine low-cloud cover (LCC) feedback are sources of significant spread in temperature responses of climate models to anthropogenic forcing. Here we show that in models the feedback is mainly driven by three large-scale changes—a strengthening tropical inversion, increasing surface latent heat flux, and an increasing vertical moisture gradient. Variations in the LCC response to these changes alone account for most of the spread in model-projected 21st century LCC changes. A methodology is devised to constrain the LCC response observationally using sea surface temperature (SST) as a surrogate for the latent heat flux and moisture gradient.more » In models where the current climate's LCC sensitivities to inversion strength and SST variations are consistent with observed, LCC decreases systematically, which would increase absorption of solar radiation. These results support a positive LCC feedback. Finally, correcting biases in the sensitivities will be an important step toward more credible simulation of cloud feedbacks.« less

Vertical profiles of aerosol mass concentration derived by unmanned airborne in situ and remote sensing instruments during dust events

NASA Astrophysics Data System (ADS)

Mamali, Dimitra; Marinou, Eleni; Sciare, Jean; Pikridas, Michael; Kokkalis, Panagiotis; Kottas, Michael; Binietoglou, Ioannis; Tsekeri, Alexandra; Keleshis, Christos; Engelmann, Ronny; Baars, Holger; Ansmann, Albert; Amiridis, Vassilis; Russchenberg, Herman; Biskos, George

2018-05-01

In situ measurements using unmanned aerial vehicles (UAVs) and remote sensing observations can independently provide dense vertically resolved measurements of atmospheric aerosols, information which is strongly required in climate models. In both cases, inverting the recorded signals to useful information requires assumptions and constraints, and this can make the comparison of the results difficult. Here we compare, for the first time, vertical profiles of the aerosol mass concentration derived from light detection and ranging (lidar) observations and in situ measurements using an optical particle counter on board a UAV during moderate and weak Saharan dust episodes. Agreement between the two measurement methods was within experimental uncertainty for the coarse mode (i.e. particles having radii > 0.5 µm), where the properties of dust particles can be assumed with good accuracy. This result proves that the two techniques can be used interchangeably for determining the vertical profiles of aerosol concentrations, bringing them a step closer towards their systematic exploitation in climate models.

A user-targeted synthesis of the VALUE perfect predictor experiment

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutierrez, Jose; Kotlarski, Sven; Hertig, Elke; Wibig, Joanna; Rössler, Ole; Huth, Radan

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. VALUE's main approach to validation is user-focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. We consider different aspects: (1) marginal aspects such as mean, variance and extremes; (2) temporal aspects such as spell length characteristics; (3) spatial aspects such as the de-correlation length of precipitation extremes; and multi-variate aspects such as the interplay of temperature and precipitation or scale-interactions. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur. Experiment 1 (perfect predictors): what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Experiment 2 (Global climate model predictors): how is the overall representation of regional climate, including errors inherited from global climate models? Experiment 3 (pseudo reality): do methods fail in representing regional climate change? Here, we present a user-targeted synthesis of the results of the first VALUE experiment. In this experiment, downscaling methods are driven with ERA-Interim reanalysis data to eliminate global climate model errors, over the period 1979-2008. As reference data we use, depending on the question addressed, (1) observations from 86 meteorological stations distributed across Europe; (2) gridded observations at the corresponding 86 locations or (3) gridded spatially extended observations for selected European regions. With more than 40 contributing methods, this study is the most comprehensive downscaling inter-comparison project so far. The results clearly indicate that for several aspects, the downscaling skill varies considerably between different methods. For specific purposes, some methods can therefore clearly be excluded.

PARAGON: A Systematic, Integrated Approach to Aerosol Observation and Modeling

NASA Technical Reports Server (NTRS)

Diner, David J.; Kahn, Ralph A.; Braverman, Amy J.; Davies, Roger; Martonchik, John V.; Menzies, Robert T.; Ackerman, Thomas P.; Seinfeld, John H.; Anderson, Theodore L.; Charlson, Robert J.;

Understanding observed and simulated historical temperature trends in California

NASA Astrophysics Data System (ADS)

Bonfils, C. J.; Duffy, P. B.; Santer, B. D.; Lobell, D. B.; Wigley, T. M.

2006-12-01

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.

Multi-objective optimization for evaluation of simulation fidelity for precipitation, cloudiness and insolation in regional climate models

NASA Astrophysics Data System (ADS)

Lee, H.

2016-12-01

Precipitation is one of the most important climate variables that are taken into account in studying regional climate. Nevertheless, how precipitation will respond to a changing climate and even its mean state in the current climate are not well represented in regional climate models (RCMs). Hence, comprehensive and mathematically rigorous methodologies to evaluate precipitation and related variables in multiple RCMs are required. The main objective of the current study is to evaluate the joint variability of climate variables related to model performance in simulating precipitation and condense multiple evaluation metrics into a single summary score. We use multi-objective optimization, a mathematical process that provides a set of optimal tradeoff solutions based on a range of evaluation metrics, to characterize the joint representation of precipitation, cloudiness and insolation in RCMs participating in the North American Regional Climate Change Assessment Program (NARCCAP) and Coordinated Regional Climate Downscaling Experiment-North America (CORDEX-NA). We also leverage ground observations, NASA satellite data and the Regional Climate Model Evaluation System (RCMES). Overall, the quantitative comparison of joint probability density functions between the three variables indicates that performance of each model differs markedly between sub-regions and also shows strong seasonal dependence. Because of the large variability across the models, it is important to evaluate models systematically and make future projections using only models showing relatively good performance. Our results indicate that the optimized multi-model ensemble always shows better performance than the arithmetic ensemble mean and may guide reliable future projections.

An effective drift correction for dynamical downscaling of decadal global climate predictions

NASA Astrophysics Data System (ADS)

Paeth, Heiko; Li, Jingmin; Pollinger, Felix; Müller, Wolfgang A.; Pohlmann, Holger; Feldmann, Hendrik; Panitz, Hans-Jürgen

2018-04-01

Initialized decadal climate predictions with coupled climate models are often marked by substantial climate drifts that emanate from a mismatch between the climatology of the coupled model system and the data set used for initialization. While such drifts may be easily removed from the prediction system when analyzing individual variables, a major problem prevails for multivariate issues and, especially, when the output of the global prediction system shall be used for dynamical downscaling. In this study, we present a statistical approach to remove climate drifts in a multivariate context and demonstrate the effect of this drift correction on regional climate model simulations over the Euro-Atlantic sector. The statistical approach is based on an empirical orthogonal function (EOF) analysis adapted to a very large data matrix. The climate drift emerges as a dramatic cooling trend in North Atlantic sea surface temperatures (SSTs) and is captured by the leading EOF of the multivariate output from the global prediction system, accounting for 7.7% of total variability. The SST cooling pattern also imposes drifts in various atmospheric variables and levels. The removal of the first EOF effectuates the drift correction while retaining other components of intra-annual, inter-annual and decadal variability. In the regional climate model, the multivariate drift correction of the input data removes the cooling trends in most western European land regions and systematically reduces the discrepancy between the output of the regional climate model and observational data. In contrast, removing the drift only in the SST field from the global model has hardly any positive effect on the regional climate model.

Using Perturbed Physics Ensembles and Machine Learning to Select Parameters for Reducing Regional Biases in a Global Climate Model

NASA Astrophysics Data System (ADS)

Li, S.; Rupp, D. E.; Hawkins, L.; Mote, P.; McNeall, D. J.; Sarah, S.; Wallom, D.; Betts, R. A.

2017-12-01

This study investigates the potential to reduce known summer hot/dry biases over Pacific Northwest in the UK Met Office's atmospheric model (HadAM3P) by simultaneously varying multiple model parameters. The bias-reduction process is done through a series of steps: 1) Generation of perturbed physics ensemble (PPE) through the volunteer computing network weather@home; 2) Using machine learning to train "cheap" and fast statistical emulators of climate model, to rule out regions of parameter spaces that lead to model variants that do not satisfy observational constraints, where the observational constraints (e.g., top-of-atmosphere energy flux, magnitude of annual temperature cycle, summer/winter temperature and precipitation) are introduced sequentially; 3) Designing a new PPE by "pre-filtering" using the emulator results. Steps 1) through 3) are repeated until results are considered to be satisfactory (3 times in our case). The process includes a sensitivity analysis to find dominant parameters for various model output metrics, which reduces the number of parameters to be perturbed with each new PPE. Relative to observational uncertainty, we achieve regional improvements without introducing large biases in other parts of the globe. Our results illustrate the potential of using machine learning to train cheap and fast statistical emulators of climate model, in combination with PPEs in systematic model improvement.

Detecting regional patterns of changing CO2 flux in Alaska

PubMed Central

Parazoo, Nicholas C.; Wofsy, Steven C.; Koven, Charles D.; Sweeney, Colm; Lawrence, David M.; Lindaas, Jakob; Chang, Rachel Y.-W.; Miller, Charles E.

2016-01-01

With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO2 with climatically forced CO2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage and near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO2 observing network is unlikely to detect potentially large CO2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. Although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost. PMID:27354511

Detecting regional patterns of changing CO 2 flux in Alaska

DOE PAGES

Parazoo, Nicholas C.; Commane, Roisin; Wofsy, Steven C.; ...

2016-06-27

With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO 2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO 2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO 2 with climatically forced CO 2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage andmore » near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO 2 observing network is unlikely to detect potentially large CO 2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. In conclusion, although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost.« less

Health Effects of Environmental Exposures, Occupational Hazards and Climate Change in Ethiopia: Synthesis of Situational Analysis, Needs Assessment and the Way Forward.

PubMed

Berhane, Kiros; Kumie, Abera; Samet, Jonathan

2016-01-01

The burden of diseases caused by environmental and occupational health hazards and the effects of global climate change are of growing concerns in Ethiopia. However, no adequate information seems to be available on the current situation. This means there is a critical gap in research, policy framework and implementation in the country. The purpose of this paper was to synthesize evidence from a systematic situational analysis and needs assessment to help establish a hub for research and training on three major themes and their related policy frameworks: air pollution and health, occupational health and safety and climate change and health. The methods used in this work include a systematic review of secondary data from peer-reviewed literature, thesis reports from academia, government and national statistical reports. Limited primary data based on key informant interviews held with major stakeholders were also used as sources of data. Exposures to high levels of indoor and outdoor air pollutants were found to be major sources of public health challenges. Lack of occupational safety and health due to agricultural activities and exposure to industries was found to be substantial. Worse is the growing fear that climate change will pose increasingly significant multidimensional challenges to the environment and public health. Across all three areas of focus, there was a paucity of information on local scientific evidence. There is also very limited trained skilled manpower and physical infrastructure to monitor the environment and enforce regulatory guidelines. Research, policy frameworks and regulatory mechanisms were among the cross-cutting issues that needed urgent attention. Critical gaps were observed in research and training across the three themes. Also, there is a limitation in implementing the link between policy and related regulations in the environment and health.

Systematization of climate data in the virtual research environment on the basis of ontology approach

NASA Astrophysics Data System (ADS)

Alipova, K. A.; Bart, A. A.; Fazliev, A. Z.; Gordov, E. P.; Okladnikov, I. G.; Privezentsev, A. I.; Titov, A. G.

2017-11-01

The first version of a primitive OWL-ontology of collections climate and meteorological data of Institute of Monitoring of Climatic and Ecological Systems SB RAS is presented. The ontology is a component of expert and decision support systems intended for quick search for climate and meteorological data required for solution of a certain class of applied problems.

The MedCLIVAR program and the climate of the Mediterranean region

NASA Astrophysics Data System (ADS)

Lionello, P.; Gacic, M.; Gomis, G.; Garcia-Herrera, R.; Giorgi, F.; Planton, S.; Trigo, R.; Theocharis, A.; Tsimplis, M. N.; Ulbrich, U.; Xoplaki, E.

2012-04-01

MedCLIVAR has become an independent platform for scientific discussion, the exchange of information and the coordination of activities across scientific groups around the Mediterranean. The scientific objects of the programme include past climate variability, connections between the Mediterranean and global climate, the Mediterranean Sea circulation and sea level, feedbacks on the global climate system, and the regional responses to greenhouse gas, air pollution, and aerosols. A strength of the MedCLIVAR programme is the development of a multidisciplinary vision of the evolution of Mediterranean climate, which includes atmospheric, marine and terrestrial components at multiple time scales, covering the range from paleo-reconstructions to future climate scenarios. MedCLIVAR has promoted scientific dissemination with many publication and by producing two books, which review the climate-related knowledge of the Mediterranean basin, one published at the beginning of the project and the second just recently finalized. Over these years, MedCLIVAR (www.medclivar.eu) has held 6 workshops and 2 schools, assigned 31 young scientist exchange grants and 7 senior scientist short visits, sponsored or co-sponsored 11 scientific meetings and organized annual sessions during the European Geophysical Union general assembly. A systematic archive of observations and model data simulations on the Mediterranean Climate, in order to both share data across the scientific community and ensure the data availability for 10 years, is presently being organized at the WDCC (http://cera-www.dkrz.de/CERA/MedCLIVAR.html)

Total column water vapor estimation over land using radiometer data from SAC-D/Aquarius

NASA Astrophysics Data System (ADS)

Epeloa, Javier; Meza, Amalia

2018-02-01

The aim of this study is retrieving atmospheric total column water vapor (CWV) over land surfaces using a microwave radiometer (MWR) onboard the Scientific Argentine Satellite (SAC-D/Aquarius). To research this goal, a statistical algorithm is used for the purpose of filtering the study region according to the climate type. A log-linear relationship between the brightness temperatures of the MWR and CWV obtained from Global Navigation Satellite System (GNSS) measurements was used. In this statistical algorithm, the retrieved CWV is derived from the Argentinian radiometer's brightness temperature which works at 23.8 GHz and 36.5 GHz, and taking into account CWVs observed from GNSS stations belonging to a region sharing the same climate type. We support this idea, having found a systematic effect when applying the algorithm; it was generated for one region using the previously mentioned criteria, however, it should be applied to additional regions, especially those with other climate types. The region we analyzed is in the Southeastern United States of America, where the climate type is Cfa (Köppen - Geiger classification); this climate type includes moist subtropical mid-latitude climates, with hot, muggy summers and frequent thunderstorms. However, MWR only contains measurements taken from over ocean surfaces; therefore the determination of water vapor over land is an important contribution to extend the use of the SAC-D/Aquarius radiometer measurements beyond the ocean surface. The CWVs computed by our algorithm are compared against radiosonde CWV observations and show a bias of about -0.6 mm, a root mean square (rms) of about 6 mm and a correlation of 0.89.

Dissemination of Climate Model Output to the Public and Commercial Sector

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

Robert Stockwell, PhD

2010-09-23

Climate is defined by the Glossary of Meteorology as the mean of atmospheric variables over a period of time ranging from as short as a few months to multiple years and longer. Although the term climate is often used to refer to long-term weather statistics, the broader definition of climate is the time evolution of a system consisting of the atmosphere, hydrosphere, lithosphere, and biosphere. Physical, chemical, and biological processes are involved in interactions among the components of the climate system. Vegetation, soil moisture, and glaciers are part of the climate system in addition to the usually considered temperature andmore » precipitation (Pielke, 2008). Climate change refers to any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer. Climate change can be initiated by external forces, such as cyclical variations in the Earth's solar orbit that are thought to have caused glacial and interglacial periods within the last 2 million years (Milankovitch, 1941). However, a linear response to astronomical forcing does not explain many other observed glacial and interglacial cycles (Petit et al., 1999). It is now understood that climate is influenced by the interaction of solar radiation with atmospheric greenhouse gasses (e.g., carbon dioxide, chlorofluorocarbons, methane, nitrous oxide, etc.), aerosols (airborne particles), and Earth's surface. A significant aspect of climate are the interannual cycles, such as the El Nino La Nina cycle which profoundly affects the weather in North America but is outside the scope of weather forecasts. Some of the most significant advances in understanding climate change have evolved from the recognition of the influence of ocean circulations upon the atmosphere (IPCC, 2007). Human activity can affect the climate system through increasing concentrations of atmospheric greenhouse gases, air pollution, increasing concentrations of aerosol, and land alteration. A particular concern is that atmospheric levels of CO{sub 2} may be rising faster than at any time in Earth's history, except possibly following rare events like impacts from large extraterrestrial objects (AMS, 2007). Atmospheric CO{sub 2} concentrations have increased since the mid-1700s through fossil fuel burning and changes in land use, with more than 80% of this increase occurring since 1900. The increased levels of CO{sub 2} will remain in the atmosphere for hundreds to thousands of years. The complexity of the climate system makes it difficult to predict specific aspects of human-induced climate change, such as exactly how and where changes will occur, and their magnitude. The Intergovernmental Panel for Climate Change (IPCC) was established by World Meteorological Organization (WMO) and the United Nations in 1988. The IPCC was tasked with assessing the scientific, technical and socioeconomic information needed to understand the risk of human-induced climate change, its observed and projected impacts, and options for adaptation and mitigation. The IPCC concluded in its Fourth Assessment Report (AR4) that warming of the climate system is unequivocal, and that most of the observed increase in globally averaged temperatures since the mid-20th century is very likely due to the observed increased in anthropogenic greenhouse gas concentrations (IPCC, 2007).« less

Vegetation coupling to global climate: Trajectories of vegetation change and phenology modeling from satellite observations

NASA Astrophysics Data System (ADS)

Fisher, Jeremy Isaac

Important systematic shifts in ecosystem function are often masked by natural variability. The rich legacy of over two decades of continuous satellite observations provides an important database for distinguishing climatological and anthropogenic ecosystem changes. Examples from semi-arid Sudanian West Africa and New England (USA) illustrate the response of vegetation to climate and land-use. In Burkina Faso, West Africa, pastoral and agricultural practices compete for land area, while degradation may follow intensification. The Nouhao Valley is a natural experiment in which pastoral and agricultural land uses were allocated separate, coherent reserves. Trajectories of annual net primary productivity were derived from 18 years of coarse-grain (AVHRR) satellite data. Trends suggested that pastoral lands had responded rigorously to increasing rainfall after the 1980's droughts. A detailed analysis at Landsat resolution (30m) indicated that the increased vegetative cover was concentrated in the river basins of the pastoral region, implying a riparian wood expansion. In comparison, riparian cover was reduced in agricultural regions. We suggest that broad-scale patterns of increasing semi-arid West African greenness may be indicative of climate variability, whereas local losses may be anthropogenic in nature. The contiguous deciduous forests, ocean proximity, topography, and dense urban developments of New England provide an ideal landscape to examine influences of climate variability and the impact of urban development vegetation response. Spatial and temporal patterns of interannual climate variability were examined via green leaf phenology. Phenology, or seasonal growth and senescence, is driven by deficits of light, temperature, and water. In temperate environments, phenology variability is driven by interannual temperature and precipitation shifts. Average and interannual phenology analyses across southern New England were conducted at resolutions of 30m (Landsat) and 500m Moderate Resolution Imaging Spectrometer (MODIS). A robust logistic-growth model of canopy cover was employed to determine phenological characteristics at each forest stand. The duel analyses revealed important findings: (a) local phenological gradients from microclimatic structures are highly influential in broad-scale phenological observations; (b) satellite observed phenology reflects observations of canopy growth from field studies; (c) phenological anomalies in urban areas which were previously attributed to urban heat may be a function of urban-specific land cover (i.e. green lawns); and (d) patterns of interannual variability in phenology at the regional scale have high spatial coherency and appear to be driven by broad-scale climatic change. Satellite-observed phenology may reflect temperatures during spring and provides a proxy of climate variability.

Mapping topographic plant location properties using a dense matching approach

NASA Astrophysics Data System (ADS)

Niederheiser, Robert; Rutzinger, Martin; Lamprecht, Andrea; Bardy-Durchhalter, Manfred; Pauli, Harald; Winkler, Manuela

2017-04-01

Within the project MEDIALPS (Disentangling anthropogenic drivers of climate change impacts on alpine plant species: Alps vs. Mediterranean mountains) six regions in Alpine and in Mediterranean mountain regions are investigated to assess how plant species respond to climate change. The project is embedded in the Global Observation Research Initiative in Alpine Environments (GLORIA), which is a well-established global monitoring initiative for systematic observation of changes in the plant species composition and soil temperature on mountain summits worldwide to discern accelerating climate change pressures on these fragile alpine ecosystems. Close-range sensing techniques such as terrestrial photogrammetry are well suited for mapping terrain topography of small areas with high resolution. Lightweight equipment, flexible positioning for image acquisition in the field, and independence on weather conditions (i.e. wind) make this a feasible method for in-situ data collection. New developments of dense matching approaches allow high quality 3D terrain mapping with less requirements for field set-up. However, challenges occur in post-processing and required data storage if many sites have to be mapped. Within MEDIALPS dense matching is used for mapping high resolution topography for 284 3x3 meter plots deriving information on vegetation coverage, roughness, slope, aspect and modelled solar radiation. This information helps identifying types of topography-dependent ecological growing conditions and evaluating the potential for existing refugial locations for specific plant species under climate change. This research is conducted within the project MEDIALPS - Disentangling anthropogenic drivers of climate change impacts on alpine plant species: Alps vs. Mediterranean mountains funded by the Earth System Sciences Programme of the Austrian Academy of Sciences.

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

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

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

New directions in hydro-climatic histories: observational data recovery, proxy records and the atmospheric circulation reconstructions over the earth (ACRE) initiative in Southeast Asia

NASA Astrophysics Data System (ADS)

Williamson, Fiona; Allan, Rob; Switzer, Adam D.; Chan, Johnny C. L.; Wasson, Robert James; D'Arrigo, Rosanne; Gartner, Richard

2015-12-01

The value of historic observational weather data for reconstructing long-term climate patterns and the detailed analysis of extreme weather events has long been recognized (Le Roy Ladurie, 1972; Lamb, 1977). In some regions however, observational data has not been kept regularly over time, or its preservation and archiving has not been considered a priority by governmental agencies. This has been a particular problem in Southeast Asia where there has been no systematic country-by-country method of keeping or preserving such data, the keeping of data only reaches back a few decades, or where instability has threatened the survival of historic records. As a result, past observational data are fragmentary, scattered, or even absent altogether. The further we go back in time, the more obvious the gaps. Observational data can be complimented however by historical documentary or proxy records of extreme events such as floods, droughts and other climatic anomalies. This review article highlights recent initiatives in sourcing, recovering, and preserving historical weather data and the potential for integrating the same with proxy (and other) records. In so doing, it focuses on regional initiatives for data research and recovery - particularly the work of the international Atmospheric Circulation Reconstructions over the Earth's (ACRE) Southeast Asian regional arm (ACRE SEA) - and the latter's role in bringing together disparate, but interrelated, projects working within this region. The overarching goal of the ACRE SEA initiative is to connect regional efforts and to build capacity within Southeast Asian institutions, agencies and National Meteorological and Hydrological Services (NMHS) to improve and extend historical instrumental, documentary and proxy databases of Southeast Asian hydroclimate, in order to contribute to the generation of high-quality, high-resolution historical hydroclimatic reconstructions (reanalyses) and, to build linkages with humanities researchers working on issues in environmental and climatic history in the region. Thus, this article also highlights the inherent value of multi/cross/inter-disciplinary projects in providing better syntheses and understanding of human and environmental/climatic variability and change.

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

DOE PAGES

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai; ...

2016-07-14

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Earths Climate Sensitivity: Apparent Inconsistencies in Recent Assessments

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

Schwartz, Stephen E.; Charlson, Robert J.; Kahn, Ralph

Earth's equilibrium climate sensitivity (ECS) and forcing of Earth's climate system over the industrial era have been re-examined in two new assessments: the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and a study by Otto et al. (2013). The ranges of these quantities given in these assessments and also in the Fourth (2007) IPCC Assessment are analyzed here within the framework of a planetary energy balance model, taking into account the observed increase in global mean surface temperature over the instrumental record together with best estimates of the rate of increase of planetary heat content.more » This analysis shows systematic differences among the several assessments and apparent inconsistencies within individual assessments. Importantly, the likely range of ECS to doubled CO₂ given in AR5, 1.5–4.5 K/(3.7 W m⁻²) exceeds the range inferred from the assessed likely range of forcing, 1.2–2.9 K/(3.7 W m⁻²), where 3.7 W ⁻² denotes the forcing for doubled CO₂. Such differences underscore the need to identify their causes and reduce the underlying uncertainties. Explanations might involve underestimated negative aerosol forcing, overestimated total forcing, overestimated climate sensitivity, poorly constrained ocean heating, limitations of the energy balance model, or a combination of effects.« less

Earths Climate Sensitivity: Apparent Inconsistencies in Recent Assessments

DOE PAGES

Schwartz, Stephen E.; Charlson, Robert J.; Kahn, Ralph; ...

2014-12-08

Earth's equilibrium climate sensitivity (ECS) and forcing of Earth's climate system over the industrial era have been re-examined in two new assessments: the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and a study by Otto et al. (2013). The ranges of these quantities given in these assessments and also in the Fourth (2007) IPCC Assessment are analyzed here within the framework of a planetary energy balance model, taking into account the observed increase in global mean surface temperature over the instrumental record together with best estimates of the rate of increase of planetary heat content.more » This analysis shows systematic differences among the several assessments and apparent inconsistencies within individual assessments. Importantly, the likely range of ECS to doubled CO₂ given in AR5, 1.5–4.5 K/(3.7 W m⁻²) exceeds the range inferred from the assessed likely range of forcing, 1.2–2.9 K/(3.7 W m⁻²), where 3.7 W ⁻² denotes the forcing for doubled CO₂. Such differences underscore the need to identify their causes and reduce the underlying uncertainties. Explanations might involve underestimated negative aerosol forcing, overestimated total forcing, overestimated climate sensitivity, poorly constrained ocean heating, limitations of the energy balance model, or a combination of effects.« less

Who trusts scientists for information about climate change? Nuclear power? Vaccines?

NASA Astrophysics Data System (ADS)

Hamilton, L.

2015-12-01

US public acceptance/rejection of science on the topic of climate change has become highly polarized, with a demographic profile well established through survey research. Trust in scientists for information about climate change tends to increase with education, decrease with age, and is higher among self-identified liberals and moderates than among conservatives. Demographic profiles of people who do or do not trust scientists regarding other disputed topics are less well established. Some observers have argued that certain domains such as vaccines, nuclear power or genetically modified organisms (GMOs) could present a mirror image of climate change, with liberals instead of conservatives disproportionately rejecting science on that topic. Evidence for this mirror-image hypothesis has been mainly anecdotal, however. Here we test it systematically using statewide survey data on more than 1200 interviews, comparing five similarly worded questions that ask respondents whether they trust, don't trust, or are unsure about scientists as a source of information about ... climate change, vaccines, evolution, nuclear power safety, or GMOs. Climate change proves to be the most polarized of these topics, but all five exhibit roughly similar age, education and ideological effects -- contrary to the mirror-image hypothesis. The common patterns across five science domains, chosen for their hypothetical contrasts, map out an unexpectedly cohesive picture of who trusts scientists for information, and who does not. Implications of these survey results for public outreach and science communication are explored.

Mars Operational Environmental Satellite (MOES): A post-Mars Observer discovery mission

NASA Technical Reports Server (NTRS)

Limaye, Sanjay S.

1993-01-01

Mars Operational Environmental Satellite (MOES) is a Discovery concept mission that is designed to observe the global short-term weather phenomena on Mars in a systematic fashion. Even after the Mariner, Viking, and, soon, Mars Observer missions, crucial aspects of the martian atmosphere will remain unobserved systematically. Achieving a better understanding of the cycles of dust, water vapor, and ices on Mars requires detailed information about atmospheric transports of those quantities associated with the weather systems, particularly those arising in mid latitudes during fall and winter. It also requires a quantitive understanding of the processes responsible for the onset and evolution of dust storms on all scales. Whereas on Earth the system of geosynchronous and polar orbiting satellites provides continuous coverage of the weather systems, on Mars the time history of important events such as regional and global dust storms remains unobserved. To understand the transport of tracers in the martian atmosphere and particularly to identify their sources and sinks, it is necessary to have systematic global, synoptic observations that have yet to be attained. Clearly these requirements are not easy to achieve from a single spacecraft in orbit, but if we focus on specific regions of the planet, e.g., polar vs. low and mid latitudes, then it is possible to attain a nearly ideal coverage at a reasonable spatial and temporal resolution with a system of just two satellites. Mars Observer is about to yield good coverage of the polar latitudes, so we focus initially on the region not covered well in terms of diurnal coverage, and in terms of desired observations will provide the initial data for the numerical models of the martian weather and climate that can be verified only with better temporal and spatial data.

National Centers for Environmental Prediction

Science.gov Websites

: Influence of convective parameterization on the systematic errors of Climate Forecast System (CFS) model ; Climate Dynamics, 41, 45-61, 2013. Saha, S., S. Pokhrel and H. S. Chaudhari : Influence of Eurasian snow Organization Search Enter text Search Navigation Bar End Cap Search EMC Go Branches Global Climate and Weather

Toward a Global Map of Raindrop Size Distributions. Part 1; Rain-Type Classification and Its Implications for Validating Global Rainfall Products

NASA Technical Reports Server (NTRS)

L'Ecuyer, Tristan S.; Kummerow, Christian; Berg,Wesley

2004-01-01

Variability in the global distribution of precipitation is recognized as a key element in assessing the impact of climate change for life on earth. The response of precipitation to climate forcings is, however, poorly understood because of discrepancies in the magnitude and sign of climatic trends in satellite-based rainfall estimates. Quantifying and ultimately removing these biases is critical for studying the response of the hydrologic cycle to climate change. In addition, estimates of random errors owing to variability in algorithm assumptions on local spatial and temporal scales are critical for establishing how strongly their products should be weighted in data assimilation or model validation applications and for assigning a level of confidence to climate trends diagnosed from the data. This paper explores the potential for refining assumed drop size distributions (DSDs) in global radar rainfall algorithms by establishing a link between satellite observables and information gleaned from regional validation experiments where polarimetric radar, Doppler radar, and disdrometer measurements can be used to infer raindrop size distributions. By virtue of the limited information available in the satellite retrieval framework, the current method deviates from approaches adopted in the ground-based radar community that attempt to relate microphysical processes and resultant DSDs to local meteorological conditions. Instead, the technique exploits the fact that different microphysical pathways for rainfall production are likely to lead to differences in both the DSD of the resulting raindrops and the three-dimensional structure of associated radar reflectivity profiles. Objective rain-type classification based on the complete three-dimensional structure of observed reflectivity profiles is found to partially mitigate random and systematic errors in DSDs implied by differential reflectivity measurements. In particular, it is shown that vertical and horizontal reflectivity structure obtained from spaceborne radar can be used to reproduce significant differences in Z(sub dr) between the easterly and westerly climate regimes observed in the Tropical Rainfall Measuring Mission Large-scale Biosphere-Atmosphere (TRMM-LBA) field experiment as well as the even larger differences between Amazonian rainfall and that observed in eastern Colorado. As such, the technique offers a potential methodology for placing locally observed DSD information into a global framework.

Spatial relationship between climatic diversity and biodiversity conservation value.

PubMed

Wang, Junjun; Wu, Ruidong; He, Daming; Yang, Feiling; Hu, Peijun; Lin, Shiwei; Wu, Wei; Diao, Yixin; Guo, Yang

2018-06-04

Capturing the full range of climatic diversity in a reserve network is expected to improve the resilience of biodiversity to climate change. Therefore, a study on systematic conservation planning for climatic diversity that explicitly or implicitly hypothesizes that regions with higher climatic diversity will support greater biodiversity is needed. However, little is known about the extent and generality of this hypothesis. This study utilized the case of Yunnan, southwest China, to quantitatively classify climatic units and modeled 4 climatic diversity indicators, including the variety of climatic units (VCU), rarity of climatic units (RCU), endemism of climatic units (ECU) and a composite index of climatic units (CICD). We used 5 reliable priority conservation area (PCA) schemes to represent the areas with high biodiversity conservation value. We then investigated the spatial relationships between the 4 climatic diversity indicators and the 5 PCA schemes and assessed the representation of climatic diversity within the existing nature reserves. The CICD exhibited the best performance for indicating high conservation value areas, followed by the ECU and RCU. However, contrary to conventional knowledge, VCU did not show a positive association with biodiversity conservation value. The rarer or more endemic climatic units tended to have higher reserve coverage than the more common units. However, only 28 units covering 10.5% of the land in Yunnan had more than 17% of their areas protected. In addition to climatic factors, topography and human disturbances also significantly affected the relationship between climatic diversity and biodiversity conservation value. This analysis suggests that climatic diversity can be an effective surrogate for establishing a more robust reserve network under climate change in Yunnan. Our study improves the understanding of the relationship between climatic diversity and biodiversity and helps build an evidence-based foundation for systematic conservation planning that targets climatic diversity in response to climate change. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

On the Emergent Constraints of Climate Sensitivity [On proposed emergent constraints of climate sensitivity

DOE PAGES

Qu, Xin; Hall, Alex; DeAngelis, Anthony M.; ...

2018-01-11

Differences among climate models in equilibrium climate sensitivity (ECS; the equilibrium surface temperature response to a doubling of atmospheric CO2) remain a significant barrier to the accurate assessment of societally important impacts of climate change. Relationships between ECS and observable metrics of the current climate in model ensembles, so-called emergent constraints, have been used to constrain ECS. Here a statistical method (including a backward selection process) is employed to achieve a better statistical understanding of the connections between four recently proposed emergent constraint metrics and individual feedbacks influencing ECS. The relationship between each metric and ECS is largely attributable tomore » a statistical connection with shortwave low cloud feedback, the leading cause of intermodel ECS spread. This result bolsters confidence in some of the metrics, which had assumed such a connection in the first place. Additional analysis is conducted with a few thousand artificial metrics that are randomly generated but are well correlated with ECS. The relationships between the contrived metrics and ECS can also be linked statistically to shortwave cloud feedback. Thus, any proposed or forthcoming ECS constraint based on the current generation of climate models should be viewed as a potential constraint on shortwave cloud feedback, and physical links with that feedback should be investigated to verify that the constraint is real. Additionally, any proposed ECS constraint should not be taken at face value since other factors influencing ECS besides shortwave cloud feedback could be systematically biased in the models.« less

Diagnosis and Quantification of Climatic Sensitivity of Carbon Fluxes in Ensemble Global Ecosystem Models

NASA Astrophysics Data System (ADS)

Wang, W.; Hashimoto, H.; Milesi, C.; Nemani, R. R.; Myneni, R.

2011-12-01

Terrestrial ecosystem models are primary scientific tools to extrapolate our understanding of ecosystem functioning from point observations to global scales as well as from the past climatic conditions into the future. However, no model is nearly perfect and there are often considerable structural uncertainties existing between different models. Ensemble model experiments thus become a mainstream approach in evaluating the current status of global carbon cycle and predicting its future changes. A key task in such applications is to quantify the sensitivity of the simulated carbon fluxes to climate variations and changes. Here we develop a systematic framework to address this question solely by analyzing the inputs and the outputs from the models. The principle of our approach is to assume the long-term (~30 years) average of the inputs/outputs as a quasi-equlibrium of the climate-vegetation system while treat the anomalies of carbon fluxes as responses to climatic disturbances. In this way, the corresponding relationships can be largely linearized and analyzed using conventional time-series techniques. This method is used to characterize three major aspects of the vegetation models that are mostly important to global carbon cycle, namely the primary production, the biomass dynamics, and the ecosystem respiration. We apply this analytical framework to quantify the climatic sensitivity of an ensemble of models including CASA, Biome-BGC, LPJ as well as several other DGVMs from previous studies, all driven by the CRU-NCEP climate dataset. The detailed analysis results are reported in this study.

Reconstructing the 20th century high-resolution climate of the southeastern United States

NASA Astrophysics Data System (ADS)

Dinapoli, Steven M.; Misra, Vasubandhu

2012-10-01

We dynamically downscale the 20th Century Reanalysis (20CR) to a 10-km grid resolution from 1901 to 2008 over the southeastern United States and the Gulf of Mexico using the Regional Spectral Model. The downscaled data set, which we call theFlorida Climate Institute-Florida State University Land-Atmosphere Reanalysis for theSoutheastern United States at 10-km resolution (FLAReS1.0), will facilitate the study of the effects of low-frequency climate variability and major historical climate events on local hydrology and agriculture. To determine the suitability of the FLAReS1.0 downscaled data set for any subsequent applied climate studies, we compare the annual, seasonal, and diurnal variability of temperature and precipitation in the model to various observation data sets. In addition, we examine the model's depiction of several meteorological phenomena that affect the climate of the region, including extreme cold waves, summer sea breezes and associated convective activity, tropical cyclone landfalls, and midlatitude frontal systems. Our results show that temperature and precipitation variability are well-represented by FLAReS1.0 on most time scales, although systematic biases do exist in the data. FLAReS1.0 accurately portrays some of the major weather phenomena in the region, but the severity of extreme weather events is generally underestimated. The high resolution of FLAReS1.0 makes it more suitable for local climate studies than the coarser 20CR.

On the Emergent Constraints of Climate Sensitivity [On proposed emergent constraints of climate sensitivity

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

Qu, Xin; Hall, Alex; DeAngelis, Anthony M.

Differences among climate models in equilibrium climate sensitivity (ECS; the equilibrium surface temperature response to a doubling of atmospheric CO2) remain a significant barrier to the accurate assessment of societally important impacts of climate change. Relationships between ECS and observable metrics of the current climate in model ensembles, so-called emergent constraints, have been used to constrain ECS. Here a statistical method (including a backward selection process) is employed to achieve a better statistical understanding of the connections between four recently proposed emergent constraint metrics and individual feedbacks influencing ECS. The relationship between each metric and ECS is largely attributable tomore » a statistical connection with shortwave low cloud feedback, the leading cause of intermodel ECS spread. This result bolsters confidence in some of the metrics, which had assumed such a connection in the first place. Additional analysis is conducted with a few thousand artificial metrics that are randomly generated but are well correlated with ECS. The relationships between the contrived metrics and ECS can also be linked statistically to shortwave cloud feedback. Thus, any proposed or forthcoming ECS constraint based on the current generation of climate models should be viewed as a potential constraint on shortwave cloud feedback, and physical links with that feedback should be investigated to verify that the constraint is real. Additionally, any proposed ECS constraint should not be taken at face value since other factors influencing ECS besides shortwave cloud feedback could be systematically biased in the models.« less

Land Cover Indicators for U.S. National Climate Assessments

NASA Astrophysics Data System (ADS)

Channan, S.; Thomson, A. M.; Collins, K. M.; Sexton, J. O.; Torrens, P.; Emanuel, W. R.

2014-12-01

Land is a critical resource for human habitat and for the vast majority of human activities. Many natural resources are derived from terrestrial ecosystems or otherwise extracted from the landscape. Terrestrial biodiversity depends on land attributes as do people's perceptions of the value of land, including its value for recreation or tourism. Furthermore, land surface properties and processes affect weather and climate, and land cover change and land management affect emissions of greenhouse gases. Thus, land cover with its close association with climate is so pervasive that a land cover indicator is of fundamental importance to U.S. national climate assessments and related research. Moderate resolution remote sensing products (MODIS) were used to provide systematic data on annual distributions of land cover over the period 2001-2012. Selected Landsat observations and data products further characterize land cover at higher resolution. Here we will present the prototype for a suite of land cover indicators including land cover maps as well as charts depicting attributes such as composition by land cover class, statistical indicators of landscape characteristics, and tabular data summaries indispensable for communicating the status and trends of U.S. land cover at national, regional and state levels.

Accelerating Climate and Weather Simulations through Hybrid Computing

NASA Technical Reports Server (NTRS)

Zhou, Shujia; Cruz, Carlos; Duffy, Daniel; Tucker, Robert; Purcell, Mark

2011-01-01

Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

On the stability treatment in WAsP

NASA Astrophysics Data System (ADS)

Giebel, G.; Gryning, S.-E.

2003-04-01

An assessment of the treatment of atmospheric stability in the standard package for wind resource estimation, WAsP (from Risø National Laboratory), is presented. Emphasis is on the vertical wind profiles in WAsP and the treatment of stability therein, under special consideration of the nightly situation. The study starts with an introduction to WAsP and the way it treats the vertical extrapolation, under special consideration of the stability. The two parameters available for changing the stability treatment in WAsP are identified as RMS heat flux and offset heat flux. Four years worth of data from the meteorological mast at Risø, plus data from Egypt and Bermuda, is used for the identification of the parameter settings for stable conditions. To this aim, the measured heat fluxes from the mast were used to extract three data sets with successively higher stability in four different heights. These data sets were then run through the Observed Wind Climate Wizard (part of the WAsP package), resulting in Weibull fits to the data. Using these observed wind climates, a prediction of the highest level wind climate using the lowest level wind climate under all different stable conditions is undertaken and compared with the measured data set. To expand on this study, a systematic variation of the two heat flux parameters in WAsP is done, finding the parameters yielding the lowest overall errors for the predictions. Parts of this study were financed by the Landesumweltamt Brandenburg.

Effects of Planetary Boundary Layer Parameterizations on CWRF Regional Climate Simulation

NASA Astrophysics Data System (ADS)

Liu, S.; Liang, X.

2011-12-01

Planetary Boundary Layer (PBL) parameterizations incorporated in CWRF (Climate extension of the Weather Research and Forecasting model) are first evaluated by comparing simulated PBL heights with observations. Among the 10 evaluated PBL schemes, 2 (CAM, UW) are new in CWRF while the other 8 are original WRF schemes. MYJ, QNSE and UW determine the PBL heights based on turbulent kinetic energy (TKE) profiles, while others (YSU, ACM, GFS, CAM, TEMF) are from bulk Richardson criteria. All TKE-based schemes (MYJ, MYNN, QNSE, UW, Boulac) substantially underestimate convective or residual PBL heights from noon toward evening, while others (ACM, CAM, YSU) well capture the observed diurnal cycle except for the GFS with systematic overestimation. These differences among the schemes are representative over most areas of the simulation domain, suggesting systematic behaviors of the parameterizations. Lower PBL heights simulated by the QNSE and MYJ are consistent with their smaller Bowen ratios and heavier rainfalls, while higher PBL tops by the GFS correspond to warmer surface temperatures. Effects of PBL parameterizations on CWRF regional climate simulation are then compared. The QNSE PBL scheme yields systematically heavier rainfall almost everywhere and throughout the year; this is identified with a much greater surface Bowen ratio (smaller sensible versus larger latent heating) and wetter soil moisture than other PBL schemes. Its predecessor MYJ scheme shares the same deficiency to a lesser degree. For temperature, the performance of the QNSE and MYJ schemes remains poor, having substantially larger rms errors in all seasons. GFS PBL scheme also produces large warm biases. Pronounced sensitivities are also found to the PBL schemes in winter and spring over most areas except the southern U.S. (Southeast, Gulf States, NAM); excluding the outliers (QNSE, MYJ, GFS) that cause extreme biases of -6 to +3°C, the differences among the schemes are still visible (±2°C), where the CAM is generally more realistic. QNSE, MYJ, GFS and BouLac PBL parameterizations are identified as obvious outliers of overall performance in representing precipitation, surface air temperature or PBL height variations. Their poor performance may result from deficiencies in physical formulations, dependences on applicable scales, or trouble numerical implementations, requiring future detailed investigation to isolate the actual cause.

Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe.

PubMed

Elsgaard, L; Børgesen, C D; Olesen, J E; Siebert, S; Ewert, F; Peltonen-Sainio, P; Rötter, R P; Skjelvåg, A O

2012-01-01

Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops.

Linkages Between Terrestrial Carbon Uptake and Interannual Climate Variability over the Texas-northern Mexico High Plains

NASA Astrophysics Data System (ADS)

Parazoo, N.; Barnes, E. A.; Worden, J.; Harper, A. B.; Bowman, K. W.; Frankenberg, C.

2014-12-01

The Texas-northern Mexico high plains experienced record drought conditions in 2011 during strong negative phases of ENSO and the NAO. Given predictions of increased frequency and severity of drought under projected climate change [e.g., Reichstein et al., 2013] and recent findings of CO2 growth rate sensitivity to interannual variability of carbon uptake in semi-arid ecosystems [Poulter et al., 2014], we investigate the response of carbon uptake in the Texas high plains to interannual climate variability with the goal of improved mechanistic understanding of climate-carbon cycle links. Specifically, we examine (1) observed tendencies in regional scale carbon uptake and soil moisture from 2010 to 2011 using satellite observations of gross primary production (GPP) (from plant fluorescence) from GOSAT and soil moisture from SMOS, and (2) the interannual relationship between GPP and ENSO & NAO variability using terrestrial biosphere simulations from 1950-2012. Observations reveal widespread decline of GPP in 2011 (0.42 +/- 0.04 Pg C yr-1) correlated with negative soil moisture tendencies (r = 0.85 +/- 0.21) which leads to corresponding declines in net carbon uptake and transpiration (according to model simulations). Further examination of model results over the period 1950-2012 indicates that negative GPP anomalies are linked systematically to winter and spring precipitation deficits associated with overlapping negative phases of winter NAO and ENSO, with increasing magnitude of negative anomalies in strong La Niña years. Furthermore, the strongest decline of GPP, carbon uptake, and transpiration on record occurred during the 2011 drought and were associated with extreme negative phases of ENSO and NAO, with 2011 being the only year since 1950 that both indices exceeded 1 σ standard deviation.

Evaluation of high intensity precipitation from 16 Regional climate models over a meso-scale catchment in the Midlands Regions of England

NASA Astrophysics Data System (ADS)

Wetterhall, F.; He, Y.; Cloke, H.; Pappenberger, F.; Freer, J.; Wilson, M.; McGregor, G.

2009-04-01

Local flooding events are often triggered by high-intensity rain-fall events, and it is important that these can be correctly modelled by Regional Climate Models (RCMs) if the results are to be used in climate impact assessment. In this study, daily precipitation from 16 RCMs was compared with observations over a meso-scale catchment in the Midlands Region of England. The RCM data was provided from the European research project ENSEMBLES and the precipitation data from the UK MetOffice. The RCMs were all driven by reanalysis data from the ERA40 dataset over the time period 1961-2000. The ENSEMBLES data is on the spatial scale of 25 x 25 km and it was disaggregated onto a 5 x 5 km grid over the catchment and compared with interpolated observational data with the same resolution. The mean precipitation was generally underestimated by the ENSEMBLES data, and the maximum and persistence of high intensity rainfall was even more underestimated. The inter-annual variability was not fully captured by the RCMs, and there was a systematic underestimation of precipitation during the autumn months. The spatial pattern in the modelled precipitation data was too smooth in comparison with the observed data, especially in the high altitudes in the western part of the catchment where the high precipitation usually occurs. The RCM outputs cannot reproduce the current high intensity precipitation events that are needed to sufficiently model extreme flood events. The results point out the discrepancy between climate model output and the high intensity precipitation input needs for hydrological impact modelling.

Sensitivity of summer climate to anthropogenic land-cover change over the Greater Phoenix, AZ, region

USGS Publications Warehouse

Georgescu, M.; Miguez-Macho, G.; Steyaert, L.T.; Weaver, C.P.

2008-01-01

This work evaluates the first-order effect of land-use/land-cover change (LULCC) on the summer climate of one of the nation's most rapidly expanding metropolitan complexes, the Greater Phoenix, AZ, region. High-resolution-2-km grid spacing-Regional Atmospheric Modeling System (RAMS) simulations of three "wet" and three "dry" summers were carried out for two different land-cover reconstructions for the region: a circa 1992 representation based on satellite observations, and a hypothetical land-cover scenario where the anthropogenic landscape of irrigated agriculture and urban pixels was replaced with current semi-natural vegetation. Model output is evaluated with respect to observed air temperature, dew point, and precipitation. Our results suggest that development of extensive irrigated agriculture adjacent to the urban area has dampened any regional-mean warming due to urbanization. Consistent with previous observationally based work, LULCC produces a systematic increase in precipitation to the north and east of the city, though only under dry conditions. This is due to a change in background atmospheric stability resulting from the advection of both warmth from the urban core and moisture from the irrigated area. ?? 2008 Elsevier Ltd. All rights reserved.

Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model

NASA Astrophysics Data System (ADS)

Acevedo, Walter; Fallah, Bijan; Reich, Sebastian; Cubasch, Ulrich

2017-05-01

Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, we investigate the assimilation of tree-ring-width (TRW) chronologies into an atmospheric global climate model using ensemble Kalman filter (EnKF) techniques and a process-based tree-growth forward model as an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in the model. This result might help the dendrochronology community to optimize their sampling efforts.

A new framework for climate sensitivity and prediction: a modelling perspective

NASA Astrophysics Data System (ADS)

Ragone, Francesco; Lucarini, Valerio; Lunkeit, Frank

2016-03-01

The sensitivity of climate models to increasing CO2 concentration and the climate response at decadal time-scales are still major factors of uncertainty for the assessment of the long and short term effects of anthropogenic climate change. While the relative slow progress on these issues is partly due to the inherent inaccuracies of numerical climate models, this also hints at the need for stronger theoretical foundations to the problem of studying climate sensitivity and performing climate change predictions with numerical models. Here we demonstrate that it is possible to use Ruelle's response theory to predict the impact of an arbitrary CO2 forcing scenario on the global surface temperature of a general circulation model. Response theory puts the concept of climate sensitivity on firm theoretical grounds, and addresses rigorously the problem of predictability at different time-scales. Conceptually, these results show that performing climate change experiments with general circulation models is a well defined problem from a physical and mathematical point of view. Practically, these results show that considering one single CO2 forcing scenario is enough to construct operators able to predict the response of climatic observables to any other CO2 forcing scenario, without the need to perform additional numerical simulations. We also introduce a general relationship between climate sensitivity and climate response at different time scales, thus providing an explicit definition of the inertia of the system at different time scales. This technique allows also for studying systematically, for a large variety of forcing scenarios, the time horizon at which the climate change signal (in an ensemble sense) becomes statistically significant. While what we report here refers to the linear response, the general theory allows for treating nonlinear effects as well. These results pave the way for redesigning and interpreting climate change experiments from a radically new perspective.

The permafrost carbon inventory on the Tibetan Plateau: a new evaluation using deep sediment cores.

PubMed

Ding, Jinzhi; Li, Fei; Yang, Guibiao; Chen, Leiyi; Zhang, Beibei; Liu, Li; Fang, Kai; Qin, Shuqi; Chen, Yongliang; Peng, Yunfeng; Ji, Chengjun; He, Honglin; Smith, Pete; Yang, Yuanhe

2016-08-01

The permafrost organic carbon (OC) stock is of global significance because of its large pool size and the potential positive feedback to climate warming. However, due to the lack of systematic field observations and appropriate upscaling methodologies, substantial uncertainties exist in the permafrost OC budget, which limits our understanding of the fate of frozen carbon in a warming world. In particular, the lack of comprehensive estimates of OC stocks across alpine permafrost means that current knowledge on this issue remains incomplete. Here, we evaluated the pool size and spatial variations of permafrost OC stock to 3 m depth on the Tibetan Plateau by combining systematic measurements from a substantial number of pedons (i.e. 342 three-metre-deep cores and 177 50-cm-deep pits) with a machine learning technique (i.e. support vector machine, SVM). We also quantified uncertainties in permafrost carbon budget by conducting Monte Carlo simulations. Our results revealed that the combination of systematic measurements with the SVM model allowed spatially explicit estimates to be made. The OC density (OC amount per unit area, OCD) exhibited a decreasing trend from the south-eastern to the north-western plateau, with the exception that OCD in the swamp meadow was substantially higher than that in surrounding regions. Our results also demonstrated that Tibetan permafrost stored a large amount of OC in the top 3 m, with the median OC pool size being 15.31 Pg C (interquartile range: 13.03-17.77 Pg C). 44% of OC occurred in deep layers (i.e. 100-300 cm), close to the proportion observed across the northern circumpolar permafrost region. The large carbon pool size together with significant permafrost thawing suggests a risk of carbon emissions and positive climate feedback across the Tibetan alpine permafrost region. © 2016 John Wiley & Sons Ltd.

Climate variability controls on unsaturated water and chemical movement, High Plains aquifer, USA

USGS Publications Warehouse

Gurdak, J.J.; Hanson, R.T.; McMahon, P.B.; Bruce, B.W.; McCray, J.E.; Thyne, G.D.; Reedy, R.C.

2007-01-01

Responses in the vadose zone and groundwater to interannual, interdecadal, and multidecadal climate variability have important implications for groundwater resource sustainability, yet they are poorly documented and not well understood in most aquifers of the USA. This investigation systematically examines the role of interannual to multidecadal climate variability on groundwater levels, deep infiltration (3-23 m) events, and downward displacement (>1 m) of chloride and nitrate reservoirs in thick (15-50 m) vadose zones across the regionally extensive High Plains aquifer. Such vadose zone responses are unexpected across much of the aquifer given a priori that unsaturated total-potential profiles indicate upward water movement from the water table toward the root zone, mean annual potential evapotranspiration exceeds mean annual precipitation, and millennia-scale evapoconcentration results in substantial vadose zone chloride and nitrate reservoirs. Using singular spectrum analysis (SSA) to reconstruct precipitation and groundwater level time-series components, variability was identified in all time series as partially coincident with known climate cycles, such as the Pacific Decadal Oscillation (PDO) (10-25 yr) and the El Nin??o/Southern Oscillation (ENSO) (2-6 yr). Using these lag-correlated hydrologic time series, a new method is demonstrated to estimate climate-varying unsaturated water flux. The results suggest the importance of interannual to interdecadal climate variability on water-flux estimation in thick vadose zones and provide better understanding of the climate-induced transients responsible for the observed deep infiltration and chemical-mobilization events. Based on these results, we discuss implications for climate-related sustainability of the High Plains aquifer. ?? Soil Science Society of America.

Elevation Control on Vegetation Organization in a Semiarid Ecosystem in Central New Mexico

NASA Astrophysics Data System (ADS)

Nudurupati, S. S.; Istanbulluoglu, E.; Adams, J. M.; Hobley, D. E. J.; Gasparini, N. M.; Tucker, G. E.; Hutton, E. W. H.

2015-12-01

Many semiarid and desert ecosystems are characterized by patchy and dynamic vegetation. Topography plays a commanding role on vegetation patterns. It is observed that plant biomes and biodiversity vary systematically with slope and aspect, from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations. In this study, we investigate the role of elevation dependent climatology on vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. An ecohydrologic cellular automaton model developed within Landlab (component based modeling framework) is used. The model couples local vegetation dynamics (that simulate biomass production based on local soil moisture and potential evapotranspiration) and plant establishment and mortality based on competition for resources and space. This model is driven by elevation dependent rainfall pulses and solar radiation. The domain is initialized with randomly assigned plant types and the model parameters that couple plant response with soil moisture are systematically changed. Climate perturbation experiments are conducted to examine spatial vegetation organization and associated timescales. Model results reproduce elevation and aspect controls on observed vegetation patterns indicating that this model captures necessary and sufficient conditions that explain these observed ecohydrological patterns.

Projecting Future Heat-Related Mortality under Climate Change Scenarios: A Systematic Review

PubMed Central

Barnett, Adrian Gerard; Wang, Xiaoming; Vaneckova, Pavla; FitzGerald, Gerard; Tong, Shilu

2011-01-01

Background: Heat-related mortality is a matter of great public health concern, especially in the light of climate change. Although many studies have found associations between high temperatures and mortality, more research is needed to project the future impacts of climate change on heat-related mortality. Objectives: We conducted a systematic review of research and methods for projecting future heat-related mortality under climate change scenarios. Data sources and extraction: A literature search was conducted in August 2010, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 through July 2010. Data synthesis: Fourteen studies fulfilled the inclusion criteria. Most projections showed that climate change would result in a substantial increase in heat-related mortality. Projecting heat-related mortality requires understanding historical temperature–mortality relationships and considering the future changes in climate, population, and acclimatization. Further research is needed to provide a stronger theoretical framework for projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution, and mortality displacement. Conclusions: Scenario-based projection research will meaningfully contribute to assessing and managing the potential impacts of climate change on heat-related mortality. PMID:21816703

WRF model forecasts and their use for hydroclimate monitoring over southern South America

NASA Astrophysics Data System (ADS)

Muller, Omar; Lovino, Miguel; Berbery, E. Hugo

2017-04-01

Weather forecasting and monitoring systems based on regional models are becoming increasingly relevant for decision support in agriculture and water management. This work evaluates the predictive and monitoring capabilities of a system based on WRF model simulations at 15 km grid spacing over a domain that encompasses La Plata Basin (LPB) in southern South America, where agriculture and water resources are essential. The model's skill up to a lead-time of 7 days is evaluated with daily precipitation and 2m temperature in-situ observations. Results show high prediction performance with 7 days lead-time throughout the domain and particularly over LPB, where about 70% of rain and no-rain days are correctly predicted. The scores tend to be better over humid climates than over arid-to-semiarid climates. Compared to the arid-semiarid climate, the humid climate has a higher probability of detection and less false alarms. The ranges of the skill scores are similar to those found over the United States, suggesting that proper choice of parameterizations lead to no loss of performance of the model. Daily mean, minimum and maximum forecast temperatures are highly correlated with observations up to 7 day lead time. The best performance is for daily mean temperature, followed by minimum temperature and a slightly weaker performance for maximum temperature over arid regions. The usefulness of WRF products for hydroclimate monitoring was tested for an unprecedented drought in southern Brazil and for a slightly above normal precipitation season in northeastern Argentina. In both cases the model products reproduce the observed precipitation conditions with consistent impacts on soil moisture, evapotranspiration and runoff. This evaluation validates the model's usefulness to fore-cast weather up to one week and to monitor climate conditions in real time. The scores suggest that the forecast lead-time can be extended into week two, while bias correction methods can reduce part of the systematic errors.

Assessment of the performance of CORDEX-SA experiments in simulating seasonal mean temperature over the Himalayan region for the present climate: Part I

NASA Astrophysics Data System (ADS)

Nengker, T.; Choudhary, A.; Dimri, A. P.

2018-04-01

The ability of an ensemble of five regional climate models (hereafter RCMs) under Coordinated Regional Climate Downscaling Experiments-South Asia (hereafter, CORDEX-SA) in simulating the key features of present day near surface mean air temperature (Tmean) climatology (1970-2005) over the Himalayan region is studied. The purpose of this paper is to understand the consistency in the performance of models across the ensemble, space and seasons. For this a number of statistical measures like trend, correlation, variance, probability distribution function etc. are applied to evaluate the performance of models against observation and simultaneously the underlying uncertainties between them for four different seasons. The most evident finding from the study is the presence of a large cold bias (-6 to -8 °C) which is systematically seen across all the models and across space and time over the Himalayan region. However, these RCMs with its fine resolution perform extremely well in capturing the spatial distribution of the temperature features as indicated by a consistently high spatial correlation (greater than 0.9) with the observation in all seasons. In spite of underestimation in simulated temperature and general intensification of cold bias with increasing elevation the models show a greater rate of warming than the observation throughout entire altitudinal stretch of study region. During winter, the simulated rate of warming gets even higher at high altitudes. Moreover, a seasonal response of model performance and its spatial variability to elevation is found.

Scaling and contextualizing climate-conflict nexus in historical agrarian China

NASA Astrophysics Data System (ADS)

Lee, Harry F.

2017-04-01

This study examines climate-conflict nexus in historical agrarian China in multi-scalar and contextualized approach, illustrating what and how socio-political factors could significantly mediate the climate-violent link in pre-industrial society. Previous empirical large-N studies show that violent conflict in historical agrarian society was triggered by climate-induced food scarcity. The relationship was valid in China, Europe, and various geographic regions in the Northern Hemisphere in pre-industrial era. Nevertheless, the observed relationship has only been verified at a macro level (long-term variability of the nexus is emphasized and data over large area are aggregated), and somewhat generalized in nature (only physical environmental factors are controlled). Three inter-related issues remain unresolved: First, the key explanatory variable of violent conflicts may change substantially at different spatio-temporal scales. It is necessary to check whether the climate-conflict nexus is valid at a micro level (about short-term variability of the nexus and data in finer spatial resolution), and explore how the nexus changes along various spatio-temporal dimensions. Second, as the climate-conflict nexus has only been demonstrated in a broad sense, it is necessary to check whether and how the nexus is mediated by local socio-political context. More non-climatic factors pertinent to the cause and distribution of conflicts (e.g., governance, adaptive mechanisms, etc.) should be considered. Third, the methodology applied in the previous studies assumes spatially-independent observations and linear relationship, which may simplify the climate-conflict link. Moreover, the solitary reliance on quantitative methods may neglect those non-quantifiable socio-political dynamics which mediates the climate-conflict nexus. I plan to address the above issues by using disaggregated spatial analysis and in-depth case studies, with close attention to local and temporal differences and non-linear nature of the climate-conflict link. China will be chosen as study area. Study period will be delimited to AD1-1911. This study represents pioneering research which systematically examines the climate-conflict nexus in pre-industrial society over extended period in multi-scalar and contextualized perspective. By comparing and evaluating the climate-conflict link along various spatio-temporal dimensions and in different socio-political context, it may help to deepen the theoretical understanding of, and also resolve the current debate over, the climate-conflict relationship. Given the large potential changes in climatic regimes projected in coming decades, the findings in this study may have important implications for the social impact of climate change in tropical countries that are in some ways similar to pre-industrial society.

Changes in tree functional composition amplify the response of forest biomass to climate variability

NASA Astrophysics Data System (ADS)

Lichstein, Jeremy; Zhang, Tao; Niinemets, Ulo; Sheffield, Justin

2017-04-01

The response of forest carbon storage to climate change is highly uncertain, contributing substantially to the divergence among global climate model projections. Numerous studies have documented responses of forest ecosystems to climate change and variability, including drought-induced increases in tree mortality rates. However, the sensitivity of forests to climate variability - in terms of both biomass carbon storage and functional components of tree species composition - has yet to be quantified across a large region using systematically sampled data. Here, we combine systematic forest inventories across the eastern USA with a species-level drought-tolerance index, derived from a meta-analysis of published literature, to quantify changes in forest biomass and community-mean-drought-tolerance in one-degree grid cells from the 1980s to 2000s. We show that forest biomass responds to decadal-scale changes in water deficit and that this biomass response is amplified by concurrent changes in community-mean-drought-tolerance. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards more drought-tolerant but lower-biomass species. Multiple plant functional traits are correlated with the above species-level drought-tolerance index, and likely contribute to the decrease in biomass with increasing drought-tolerance. These traits include wood density and P50 (the xylem water potential at which a plant loses 50% of its hydraulic conductivity). Simulations with a trait- and competition-based dynamic global vegetation model suggest that species differences in plant carbon allocation to wood, leaves, and fine roots also likely contribute to the observed decrease in biomass with increasing drought-tolerance, because competition drives plants to over-invest in fine roots when water is limiting. Thus, the most competitive species under dry conditions have greater root allocation but lower total biomass than productivity-maximizing plants. Amplification of the biomass-climate response due to shifts in species functional composition (temporal beta diversity) contrasts with evidence that local (alpha) diversity increases ecosystem stability, including increased resistance to climate extremes. These contrasting effects of alpha and beta diversity highlight the need to better understand how different components of biodiversity, including changes in the functional traits of the dominant plant species, affect ecosystem functioning.

SysSon - A Framework for Systematic Sonification Design

NASA Astrophysics Data System (ADS)

Vogt, Katharina; Goudarzi, Visda; Holger Rutz, Hanns

2015-04-01

SysSon is a research approach on introducing sonification systematically to a scientific community where it is not yet commonly used - e.g., in climate science. Thereby, both technical and socio-cultural barriers have to be met. The approach was further developed with climate scientists, who participated in contextual inquiries, usability tests and a workshop of collaborative design. Following from these extensive user tests resulted our final software framework. As frontend, a graphical user interface allows climate scientists to parametrize standard sonifications with their own data sets. Additionally, an interactive shell allows to code new sonifications for users competent in sound design. The framework is a standalone desktop application, available as open source (for details see http://sysson.kug.ac.at/) and works with data in NetCDF format.

The ESA GOME-Evolution "Climate" water vapor product: a homogenized time series of H2O columns from GOME, SCIAMACHY, and GOME-2

NASA Astrophysics Data System (ADS)

Beirle, Steffen; Lampel, Johannes; Wang, Yang; Mies, Kornelia; Dörner, Steffen; Grossi, Margherita; Loyola, Diego; Dehn, Angelika; Danielczok, Anja; Schröder, Marc; Wagner, Thomas

2018-03-01

We present time series of the global distribution of water vapor columns over more than 2 decades based on measurements from the satellite instruments GOME, SCIAMACHY, and GOME-2 in the red spectral range. A particular focus is the consistency amongst the different sensors to avoid jumps from one instrument to another. This is reached by applying robust and simple retrieval settings consistently. Potentially systematic effects due to differences in ground pixel size are avoided by merging SCIAMACHY and GOME-2 observations to GOME spatial resolution, which also allows for a consistent treatment of cloud effects. In addition, the GOME-2 swath is reduced to that of GOME and SCIAMACHY to have consistent viewing geometries.Remaining systematic differences between the different sensors are investigated during overlap periods and are corrected for in the homogenized time series. The resulting Climate product v2.2 (https://doi.org/10.1594/WDCC/GOME-EVL_water_vapor_clim_v2.2) allows the study of the temporal evolution of water vapor over the last 20 years on a global scale.

Assessment of bias correction under transient climate change

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Vannitsem, Stéphane

2015-04-01

Calibration of climate simulations is necessary since large systematic discrepancies are generally found between the model climate and the observed climate. Recent studies have cast doubt upon the common assumption of the bias being stationary when the climate changes. This led to the development of new methods, mostly based on linear sensitivity of the biases as a function of time or forcing (Kharin et al. 2012). However, recent studies uncovered more fundamental problems using both low-order systems (Vannitsem 2011) and climate models, showing that the biases may display complicated non-linear variations under climate change. This last analysis focused on biases derived from the equilibrium climate sensitivity, thereby ignoring the effect of the transient climate sensitivity. Based on the linear response theory, a general method of bias correction is therefore proposed that can be applied on any climate forcing scenario. The validity of the method is addressed using twin experiments with a climate model of intermediate complexity LOVECLIM (Goosse et al., 2010). We evaluate to what extent the bias change is sensitive to the structure (frequency) of the applied forcing (here greenhouse gases) and whether the linear response theory is valid for global and/or local variables. To answer these question we perform large-ensemble simulations using different 300-year scenarios of forced carbon-dioxide concentrations. Reality and simulations are assumed to differ by a model error emulated as a parametric error in the wind drag or in the radiative scheme. References [1] H. Goosse et al., 2010: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603-633. [2] S. Vannitsem, 2011: Bias correction and post-processing under climate change, Nonlin. Processes Geophys., 18, 911-924. [3] V.V. Kharin, G. J. Boer, W. J. Merryfield, J. F. Scinocca, and W.-S. Lee, 2012: Statistical adjustment of decadal predictions in a changing climate, Geophys. Res. Lett., 39, L19705.

Underestimating belief in climate change

NASA Astrophysics Data System (ADS)

Jost, John T.

2018-03-01

People are influenced by second-order beliefs — beliefs about the beliefs of others. New research finds that citizens in the US and China systematically underestimate popular support for taking action to curb climate change. Fortunately, they seem willing and able to correct their misperceptions.

Heat waves and warm periods in Slovakia

NASA Astrophysics Data System (ADS)

Faško, Pavel; Bochníček, Oliver; Markovič, Ladislav; Švec, Marek

2016-04-01

The scenarios of climate change caused by human activity show that frequency of occurrence and extent of heat waves in the interior of Europe is increasing. Among the most exposed regions in this regard should the area of southeastern and eastern Austria and south-western Slovakia. The relatively faster increase in the number of heat waves in this area is related also to potential desertification in this region just east of the Alps, since during summer, weather fronts advancing from the west are consequently losing their original features and moderating influence. Summer weather patterns for this area should in the future more closely remind climate typical for some inland areas of southwestern, southern and southeastern Europe. A certain shift of climate zones from south to north should thus modify future climate and Slovakia. Despite the complex natural conditions the existing trends derived from results of meteorological measurements and observations are clear and they confirm warming of climate in this region. Observations and measurements in the recent years of the 21st century confirm, that heat waves are no longer rare phenomenon during summer, but are systematically appearing even in colder regions of northern Slovakia. What is very remarkable and will be necessary to pay more attention to, is the fact that these heat waves are expanding into previously unaffected areas, associated with the lack of rainfall and drought, on larger regional scale. In this study heat wave periods and individual heat events and days are statistically identified in the time series characteristics of air temperature at selected meteorological stations for the period from the mid-20th century until 2015, in case of available historical data even for longer period.

Boundary Condition Effects on Hillslope Form and Soil Development Along a Climatic Gradient From Semiarid to Hyperarid in Northern Chile

NASA Astrophysics Data System (ADS)

Owen, J. J.; Dietrich, W. E.; Nishiizumi, K.; Bellugi, D.; Amundson, R.

2008-12-01

Modeling the development of hillslopes using mass balance equations has generated many testable hypotheses related to morphology, process rates, and soil properties, however it is only relatively recently that techniques for constraining these models (such as cosmogenic radionuclides) have become commonplace. As such, many hypotheses related to the effects of boundary conditions or climate on process rates and soil properties have been left untested. We selected pairs of hillslopes along a precipitation gradient in northern Chile (24°-30° S) which were either bounded by actively eroding (bedrock-bedded) channels or by stable or aggradational landforms (pediments, colluvial aprons, valley bottoms). For each hillslope we measured soil properties, atmospheric deposition rates, and bedrock denudation rates. We observe significant changes in soil properties with climate: there is a shift from thick, weathered soils in the semiarid south, to the near absence of soil in the arid middle, to salt-rich soils in the hyperarid north. Coincident with these are dramatic changes in the types and rates of processes acting on the soils. We found relatively quick, biotically-driven soil formation and transport in the south, and very slow, salt-driven processes in the north. Additionally, we observe systematic differences between hillslopes of different boundary condition within the same climate zone, such as thicker soils, gentler slopes, and slower erosion rates on hillslopes with a non-eroding boundary versus an eroding boundary. These support general predictions based on hillslope soil mass balance equations and geomorphic transport laws. Using parameters derived from our field data, we attempt to use a mass balance model of hillslope development to explore the effect of changing boundary conditions and/or shifting climate.

Structural Uncertainty in Antarctic sea ice simulations

NASA Astrophysics Data System (ADS)

Schneider, D. P.

2016-12-01

The inability of the vast majority of historical climate model simulations to reproduce the observed increase in Antarctic sea ice has motivated many studies about the quality of the observational record, the role of natural variability versus forced changes, and the possibility of missing or inadequate forcings in the models (such as freshwater discharge from thinning ice shelves or an inadequate magnitude of stratospheric ozone depletion). In this presentation I will highlight another source of uncertainty that has received comparatively little attention: Structural uncertainty, that is, the systematic uncertainty in simulated sea ice trends that arises from model physics and mean-state biases. Using two large ensembles of experiments from the Community Earth System Model (CESM), I will show that the model is predisposed towards producing negative Antarctic sea ice trends during 1979-present, and that this outcome is not simply because the model's decadal variability is out-of-synch with that in nature. In the "Tropical Pacific Pacemaker" ensemble, in which observed tropical Pacific SST anomalies are prescribed, the model produces very realistic atmospheric circulation trends over the Southern Ocean, yet the sea ice trend is negative in every ensemble member. However, if the ensemble-mean trend (commonly interpreted as the forced response) is removed, some ensemble members show a sea ice increase that is very similar to the observed. While this results does confirm the important role of natural variability, it also suggests a strong bias in the forced response. I will discuss the reasons for this systematic bias and explore possible remedies. This an important problem to solve because projections of 21st -Century changes in the Antarctic climate system (including ice sheet surface mass balance changes and related changes in the sea level budget) have a strong dependence on the mean state of and changes in the Antarctic sea ice cover. This problem is not unique to CESM, but is pervasive across CMIP5-class models.

Martian Cryogenic Carbonate Formation: Stable Isotope Variations Observed in Laboratory Studies

NASA Technical Reports Server (NTRS)

Socki, Richard A.; Niles, Paul B.; Sun, Tao; Fu, Qi; Romanek, Christopher S.; Gibson, Everett K. Jr.

2014-01-01

The history of water on Mars is tied to the formation of carbonates through atmospheric CO2 and its control of the climate history of the planet. Carbonate mineral formation under modern martian atmospheric conditions could be a critical factor in controlling the martian climate in a means similar to the rock weathering cycle on Earth. The combination of evidence for liquid water on the martian surface and cold surface conditions suggest fluid freezing could be very common on the surface of Mars. Cryogenic calcite forms easily from freezing solutions when carbon dioxide degasses quickly from Ca-bicarbonate-rich water, a process that has been observed in some terrestrial settings such as arctic permafrost cave deposits, lake beds of the Dry Valleys of Antarctica, and in aufeis (river icings) from rivers of N.E. Alaska. A series of laboratory experiments were conducted that simulated cryogenic carbonate formation on Mars in order to understand their isotopic systematics. The results indicate that carbonates grown under martian conditions show variable enrichments from starting bicarbonate fluids in both carbon and oxygen isotopes beyond equilibrium values.

Quantitative estimation of climatic parameters from vegetation data in North America by the mutual climatic range technique

USGS Publications Warehouse

Anderson, Katherine H.; Bartlein, Patrick J.; Strickland, Laura E.; Pelltier, Richard T.; Thompson, Robert S.; Shafer, Sarah L.

2012-01-01

The mutual climatic range (MCR) technique is perhaps the most widely used method for estimating past climatic parameters from fossil assemblages, largely because it can be conducted on a simple list of the taxa present in an assemblage. When applied to plant macrofossil data, this unweighted approach (MCRun) will frequently identify a large range for a given climatic parameter where the species in an assemblage can theoretically live together. To narrow this range, we devised a new weighted approach (MCRwt) that employs information from the modern relations between climatic parameters and plant distributions to lessen the influence of the "tails" of the distributions of the climatic data associated with the taxa in an assemblage. To assess the performance of the MCR approaches, we applied them to a set of modern climatic data and plant distributions on a 25-km grid for North America, and compared observed and estimated climatic values for each grid point. In general, MCRwt was superior to MCRun in providing smaller anomalies, less bias, and better correlations between observed and estimated values. However, by the same measures, the results of Modern Analog Technique (MAT) approaches were superior to MCRwt. Although this might be reason to favor MAT approaches, they are based on assumptions that may not be valid for paleoclimatic reconstructions, including that: 1) the absence of a taxon from a fossil sample is meaningful, 2) plant associations were largely unaffected by past changes in either levels of atmospheric carbon dioxide or in the seasonal distributions of solar radiation, and 3) plant associations of the past are adequately represented on the modern landscape. To illustrate the application of these MCR and MAT approaches to paleoclimatic reconstructions, we applied them to a Pleistocene paleobotanical assemblage from the western United States. From our examinations of the estimates of modern and past climates from vegetation assemblages, we conclude that the MCRun technique provides reliable and unbiased estimates of the ranges of possible climatic conditions that can reasonably be associated with these assemblages. The application of MCRwt and MAT approaches can further constrain these estimates and may provide a systematic way to assess uncertainty. The data sets required for MCR analyses in North America are provided in a parallel publication.

Constrained parameterisation of photosynthetic capacity causes significant increase of modelled tropical vegetation surface temperature

NASA Astrophysics Data System (ADS)

Kattge, J.; Knorr, W.; Raddatz, T.; Wirth, C.

2009-04-01

Photosynthetic capacity is one of the most sensitive parameters of terrestrial biosphere models whose representation in global scale simulations has been severely hampered by a lack of systematic analyses using a sufficiently broad database. Due to its coupling to stomatal conductance changes in the parameterisation of photosynthetic capacity may potentially influence transpiration rates and vegetation surface temperature. Here, we provide a constrained parameterisation of photosynthetic capacity for different plant functional types in the context of the photosynthesis model proposed by Farquhar et al. (1980), based on a comprehensive compilation of leaf photosynthesis rates and leaf nitrogen content. Mean values of photosynthetic capacity were implemented into the coupled climate-vegetation model ECHAM5/JSBACH and modelled gross primary production (GPP) is compared to a compilation of independent observations on stand scale. Compared to the current standard parameterisation the root-mean-squared difference between modelled and observed GPP is substantially reduced for almost all PFTs by the new parameterisation of photosynthetic capacity. We find a systematic depression of NUE (photosynthetic capacity divided by leaf nitrogen content) on certain tropical soils that are known to be deficient in phosphorus. Photosynthetic capacity of tropical trees derived by this study is substantially lower than standard estimates currently used in terrestrial biosphere models. This causes a decrease of modelled GPP while it significantly increases modelled tropical vegetation surface temperatures, up to 0.8°C. These results emphasise the importance of a constrained parameterisation of photosynthetic capacity not only for the carbon cycle, but also for the climate system.

Urban Climate Map System for Dutch spatial planning

NASA Astrophysics Data System (ADS)

Ren, Chao; Spit, Tejo; Lenzholzer, Sanda; Yim, Hung Lam Steve; Heusinkveld, Bert; van Hove, Bert; Chen, Liang; Kupski, Sebastian; Burghardt, René; Katzschner, Lutz

2012-08-01

Facing climate change and global warming, outdoor climatic environment is an important consideration factor for planners and policy makers because improving it can greatly contribute to achieve citizen's thermal comfort and create a better urban living quality for adaptation. Thus, the climatic information must be assessed systematically and applied strategically into the planning process. This paper presents a tool named Urban Climate Map System (UCMS) that has proven capable of helping compact cities to incorporate climate effects in planning processes in a systematic way. UCMS is developed and presented in a Geographic Information System (GIS) platform in which the lessons learned and experience gained from interdisciplinary studies can be included. The methodology of UCMS of compact cities, the construction procedure, and the basic input factors - including the natural climate resources and planning data - are described. Some literatures that shed light on the applicability of UMCS are reported. The Municipality of Arnhem is one of Dutch compact urban areas and still under fast urban development and urban renewal. There is an urgent need for local planners and policy makers to protect local climate and open landscape resources and make climate change adaptation in urban construction. Thus, Arnhem is chosen to carry out a case study of UCMS. Although it is the first work of Urban Climatic Mapping in The Netherlands, it serves as a useful climatic information platform to local planners and policy makers for their daily on-going works. We attempt to use a quick method to collect available climatic and planning data and create an information platform for planning use. It relies mostly on literature and theoretical understanding that has been well practiced elsewhere. The effort here is to synergize the established understanding for a case at hand and demonstrate how useful guidance can still be made for planners and policy makers.

Water isotope systematics: Improving our palaeoclimate interpretations

USGS Publications Warehouse

Jones, M. D.; Dee, S.; Anderson, L.; Baker, A.; Bowen, G.; Noone, D.

2016-01-01

The stable isotopes of oxygen and hydrogen, measured in a variety of archives, are widely used proxies in Quaternary Science. Understanding the processes that control δ18O change have long been a focus of research (e.g. Shackleton and Opdyke, 1973; Talbot, 1990 ; Leng, 2006). Both the dynamics of water isotope cycling and the appropriate interpretation of geological water-isotope proxy time series remain subjects of active research and debate. It is clear that achieving a complete understanding of the isotope systematics for any given archive type, and ideally each individual archive, is vital if these palaeo-data are to be used to their full potential, including comparison with climate model experiments of the past. Combining information from modern monitoring and process studies, climate models, and proxy data is crucial for improving our statistical constraints on reconstructions of past climate variability.As climate models increasingly incorporate stable water isotope physics, this common language should aid quantitative comparisons between proxy data and climate model output. Water-isotope palaeoclimate data provide crucial metrics for validating GCMs, whereas GCMs provide a tool for exploring the climate variability dominating signals in the proxy data. Several of the studies in this set of papers highlight how collaborations between palaeoclimate experimentalists and modelers may serve to expand the usefulness of palaeoclimate data for climate prediction in future work.This collection of papers follows the session on Water Isotope Systematics held at the 2013 AGU Fall Meeting in San Francisco. Papers in that session, the breadth of which are represented here, discussed such issues as; understanding sub-GNIP scale (Global Network for Isotopes in Precipitation, (IAEA/WMO, 2006)) variability in isotopes in precipitation from different regions, detailed examination of the transfer of isotope signals from precipitation to geological archives, and the implications of advances in understanding in these areas for the interpretation of palaeo records and proxy data – climate model comparison.Here, we briefly review these areas of research, and discuss challenges for the water isotope community in improving our ability to partition climate vs. auxiliary signals in palaeoclimate data.

Response of carbon isotopic compositions of Early-Middle Permian coals in North China to palaeo-climate change

NASA Astrophysics Data System (ADS)

Ding, Dianshi; Liu, Guijian; Sun, Xiaohui; Sun, Ruoyu

2018-01-01

To investigate the magnitude to which the carbon isotopic ratio (δ13C) varies in coals in response to their contemporary terrestrial environment, the Early-Middle Permian Huainan coals (including coals from the Shanxi Formation, Lower Shihezi Formation and Upper Shihezi Formation) in North China were systematically sampled. A 2.5‰ variation range of δ13C values (-25.15‰ to -22.65‰) was observed in Huainan coals, with an average value of -24.06‰. As coal diagenesis exerts little influence on carbon isotope fractionation, δ13C values in coals were mainly imparted by those of coal-forming flora assemblages which were linked to the contemporary climate. The δ13C values in coals from the Shanxi and Lower Shihezi Formations are variable, reflecting unstable climatic oscillations. Heavy carbon isotope is enriched in coals of the Capitanian Upper Shihezi Formation, implying a shift to high positive δ13C values of coeval atmospheric CO2. Notably, our study provides evidence of the Kamura event in the terrestrial environment for the first time.

Future climate change scenarios in Central America at high spatial resolution.

PubMed

Imbach, Pablo; Chou, Sin Chan; Lyra, André; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961-1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021-2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021-2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario.

Future climate change scenarios in Central America at high spatial resolution

PubMed Central

Imbach, Pablo; Chou, Sin Chan; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961–1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021–2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021–2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario. PMID:29694355

Observing Climate with GNSS Radio Occultation: Characterization and Mitigation of Systematic Errors

NASA Astrophysics Data System (ADS)

Foelsche, U.; Scherllin-Pirscher, B.; Danzer, J.; Ladstädter, F.; Schwarz, J.; Steiner, A. K.; Kirchengast, G.

2013-05-01

GNSS Radio Occultation (RO) data a very well suited for climate applications, since they do not require external calibration and only short-term measurement stability over the occultation event duration (1 - 2 min), which is provided by the atomic clocks onboard the GPS satellites. With this "self-calibration", it is possible to combine data from different sensors and different missions without need for inter-calibration and overlap (which is extremely hard to achieve for conventional satellite data). Using the same retrieval for all datasets we obtained monthly refractivity and temperature climate records from multiple radio occultation satellites, which are consistent within 0.05 % and 0.05 K in almost any case (taking global averages over the altitude range 10 km to 30 km). Longer-term average deviations are even smaller. Even though the RO record is still short, its high quality already allows to see statistically significant temperature trends in the lower stratosphere. The value of RO data for climate monitoring is therefore increasingly recognized by the scientific community, but there is also concern about potential residual systematic errors in RO climatologies, which might be common to data from all satellites. We started to look at different error sources, like the influence of the quality control and the high altitude initialization. We will focus on recent results regarding (apparent) constants used in the retrieval and systematic ionospheric errors. (1) All current RO retrievals use a "classic" set of (measured) constants, relating atmospheric microwave refractivity with atmospheric parameters. With the increasing quality of RO climatologies, errors in these constants are not negligible anymore. We show how these parameters can be related to more fundamental physical quantities (fundamental constants, the molecular/atomic polarizabilities of the constituents of air, and the dipole moment of water vapor). This approach also allows computing sensitivities to changes in atmospheric composition. We found that changes caused by the anthropogenic CO2 increase are still almost exactly offset by the concurrent O2 decrease. (2) Since the ionospheric correction of RO data is an approximation to first order, we have to consider an ionospheric residual, which can be expected to be larger when the ionization is high (day vs. night, high vs. low solar activity). In climate applications this could lead to a time dependent bias, which could induce wrong trends in atmospheric parameters at high altitudes. We studied this systematic ionospheric residual by analyzing the bending angle bias characteristics of CHAMP and COSMIC RO data from the years 2001 to 2011. We found that the night time bending angle bias stays constant over the whole period of 11 years, while the day time bias increases from low to high solar activity. As a result, the difference between night and day time bias increases from -0.05 μrad to -0.4 μrad. This behavior paves the way to correct the (small) solar cycle dependent bias of large ensembles of day time RO profiles.

User-relevant, threshold-specific observations of climate change

NASA Astrophysics Data System (ADS)

Stainforth, Dave; Chapman, Sandra; Watkins, Nicholas

2014-05-01

Users of climate information look for details of changing climate at local scales (to inform specific activities) and on the geographical patterns of such changes (to prioritise adaptation investments). They often have user-specific thresholds of vulnerability so the changes of interest must refer to such thresholds or to the related quantile of the climatic distribution. A method for providing such information from timeseries of temperature data has recently been published [1] along with maps of changes at thresholds and quantiles [2] derived from the European Observational dataset E-Obs [3]. In this presentation we will do two things. First we will discuss the opportunities to tailor such methods to provide user-specific information through climate services, using illustrations from the existing methodology applied to daily maximum and minimum temperatures [1,2]. Second we will present new results on threshold specific observed changes in precipitation. The methodology for precipitation is related to that which has been applied to temperature but has been developed to handle the characteristics of precipitation distributions. The results identify some regions with systematic increases in precipitation on the seasonally wettest days and others which show drying across all days, on a seasonal basis. We will present the geographic locations and precipitation thresholds where strong signals of changes are seen across Europe. The coherency of such results and the methodology used to process the observational data will be discussed. We will also highlight the justifications for having confidence in the results in some regions and at some thresholds while having a lack of confidence in others. Such information should be an important element of any climate services. It is worth noting that here "wettest days" refers to events which are uncommon within a season (e.g. one in ~20 wet days). This is in contrast and complementary to, for instance, the one in a hundred year extreme event. Users can be vulnerable to one or the other or both of these event types and climate services are required which are sufficiently flexible to provide tailored information in either situation. It is common to focus on the latter while the former is relatively understudied. [1] Chapman, S C, Stainforth, D A, Watkins, N W. 2013 On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, 371 20120287; [2] Stainforth, D A, Chapman, S. C. & Watkins, N. W. 2013. Mapping climate change in European temperature distributions Environ. Res. Lett. 8 034031 [3] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119

CMIP5 Scientific Gaps and Recommendations for CMIP6

DOE PAGES

Stouffer, R. J.; Eyring, V.; Meehl, G. A.; ...

2017-01-23

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

CMIP5 Scientific Gaps and Recommendations for CMIP6

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

Stouffer, R. J.; Eyring, V.; Meehl, G. A.

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

Plant diversity enhances productivity and soil carbon storage

PubMed Central

Chen, Shiping; Wang, Wantong; Xu, Wenting; Wang, Yang; Wan, Hongwei; Tang, Xuli; Zhou, Guoyi; Xie, Zongqiang; Zhou, Daowei; Shangguan, Zhouping; Huang, Jianhui; Wang, Yanfen; Sheng, Jiandong; Tang, Lisong; Li, Xinrong; Dong, Ming; Wu, Yan; Wang, Qiufeng; Wu, Jianguo; Chapin, F. Stuart; Bai, Yongfei

2018-01-01

Despite evidence from experimental grasslands that plant diversity increases biomass production and soil organic carbon (SOC) storage, it remains unclear whether this is true in natural ecosystems, especially under climatic variations and human disturbances. Based on field observations from 6,098 forest, shrubland, and grassland sites across China and predictions from an integrative model combining multiple theories, we systematically examined the direct effects of climate, soils, and human impacts on SOC storage versus the indirect effects mediated by species richness (SR), aboveground net primary productivity (ANPP), and belowground biomass (BB). We found that favorable climates (high temperature and precipitation) had a consistent negative effect on SOC storage in forests and shrublands, but not in grasslands. Climate favorability, particularly high precipitation, was associated with both higher SR and higher BB, which had consistent positive effects on SOC storage, thus offsetting the direct negative effect of favorable climate on SOC. The indirect effects of climate on SOC storage depended on the relationships of SR with ANPP and BB, which were consistently positive in all biome types. In addition, human disturbance and soil pH had both direct and indirect effects on SOC storage, with the indirect effects mediated by changes in SR, ANPP, and BB. High soil pH had a consistently negative effect on SOC storage. Our findings have important implications for improving global carbon cycling models and ecosystem management: Maintaining high levels of diversity can enhance soil carbon sequestration and help sustain the benefits of plant diversity and productivity. PMID:29666315

Process-based evaluation of the ÖKS15 Austrian climate scenarios: First results

NASA Astrophysics Data System (ADS)

Mendlik, Thomas; Truhetz, Heimo; Jury, Martin; Maraun, Douglas

2017-04-01

The climate scenarios for Austria from the ÖKS15 project consists of 13 downscaled and bias-corrected RCMs from the EURO-CORDEX project. This dataset is meant for the broad public and is now available at the central national archive for climate data (CCCA Data Center). Because of this huge public outreach it is absolutely necessary to objectively discuss the limitations of this dataset and to publish these limitations, which should also be understood by a non-scientific audience. Even though systematical climatological biases have been accounted for by the Scaled-Distribution-Mapping (SDM) bias-correction method, it is not guaranteed that the model biases have been removed for the right reasons. If climate scenarios do not get the patterns of synoptic variability right, biases will still prevail in certain weather patterns. Ultimately this will have consequences for the projected climate change signals. In this study we derive typical weather types in the Alpine Region based on patterns from mean sea level pressure from ERA-INTERIM data and check the occurrence of these synoptic phenomena in EURO-CORDEX data and their corresponding driving GCMs. Based on these weather patterns we analyze the remaining biases of the downscaled and bias-corrected scenarios. We argue that such a process-based evaluation is not only necessary from a scientific point of view, but can also help the broader public to understand the limitations of downscaled climate scenarios, as model errors can be interpreted in terms of everyday observable weather.

Shifting plant species composition in response to climate change stabilizes grassland primary production.

PubMed

Liu, Huiying; Mi, Zhaorong; Lin, Li; Wang, Yonghui; Zhang, Zhenhua; Zhang, Fawei; Wang, Hao; Liu, Lingli; Zhu, Biao; Cao, Guangmin; Zhao, Xinquan; Sanders, Nathan J; Classen, Aimée T; Reich, Peter B; He, Jin-Sheng

2018-04-17

The structure and function of alpine grassland ecosystems, including their extensive soil carbon stocks, are largely shaped by temperature. The Tibetan Plateau in particular has experienced significant warming over the past 50 y, and this warming trend is projected to intensify in the future. Such climate change will likely alter plant species composition and net primary production (NPP). Here we combined 32 y of observations and monitoring with a manipulative experiment of temperature and precipitation to explore the effects of changing climate on plant community structure and ecosystem function. First, long-term climate warming from 1983 to 2014, which occurred without systematic changes in precipitation, led to higher grass abundance and lower sedge abundance, but did not affect aboveground NPP. Second, an experimental warming experiment conducted over 4 y had no effects on any aspect of NPP, whereas drought manipulation (reducing precipitation by 50%), shifted NPP allocation belowground without affecting total NPP. Third, both experimental warming and drought treatments, supported by a meta-analysis at nine sites across the plateau, increased grass abundance at the expense of biomass of sedges and forbs. This shift in functional group composition led to deeper root systems, which may have enabled plant communities to acquire more water and thus stabilize ecosystem primary production even with a changing climate. Overall, our study demonstrates that shifting plant species composition in response to climate change may have stabilized primary production in this high-elevation ecosystem, but it also caused a shift from aboveground to belowground productivity.

Plant diversity enhances productivity and soil carbon storage.

PubMed

Chen, Shiping; Wang, Wantong; Xu, Wenting; Wang, Yang; Wan, Hongwei; Chen, Dima; Tang, Zhiyao; Tang, Xuli; Zhou, Guoyi; Xie, Zongqiang; Zhou, Daowei; Shangguan, Zhouping; Huang, Jianhui; He, Jin-Sheng; Wang, Yanfen; Sheng, Jiandong; Tang, Lisong; Li, Xinrong; Dong, Ming; Wu, Yan; Wang, Qiufeng; Wang, Zhiheng; Wu, Jianguo; Chapin, F Stuart; Bai, Yongfei

2018-04-17

Despite evidence from experimental grasslands that plant diversity increases biomass production and soil organic carbon (SOC) storage, it remains unclear whether this is true in natural ecosystems, especially under climatic variations and human disturbances. Based on field observations from 6,098 forest, shrubland, and grassland sites across China and predictions from an integrative model combining multiple theories, we systematically examined the direct effects of climate, soils, and human impacts on SOC storage versus the indirect effects mediated by species richness (SR), aboveground net primary productivity (ANPP), and belowground biomass (BB). We found that favorable climates (high temperature and precipitation) had a consistent negative effect on SOC storage in forests and shrublands, but not in grasslands. Climate favorability, particularly high precipitation, was associated with both higher SR and higher BB, which had consistent positive effects on SOC storage, thus offsetting the direct negative effect of favorable climate on SOC. The indirect effects of climate on SOC storage depended on the relationships of SR with ANPP and BB, which were consistently positive in all biome types. In addition, human disturbance and soil pH had both direct and indirect effects on SOC storage, with the indirect effects mediated by changes in SR, ANPP, and BB. High soil pH had a consistently negative effect on SOC storage. Our findings have important implications for improving global carbon cycling models and ecosystem management: Maintaining high levels of diversity can enhance soil carbon sequestration and help sustain the benefits of plant diversity and productivity.

Deriving a sea surface temperature record suitable for climate change research from the along-track scanning radiometers

NASA Astrophysics Data System (ADS)

Merchant, C. J.; Llewellyn-Jones, D.; Saunders, R. W.; Rayner, N. A.; Kent, E. C.; Old, C. P.; Berry, D.; Birks, A. R.; Blackmore, T.; Corlett, G. K.; Embury, O.; Jay, V. L.; Kennedy, J.; Mutlow, C. T.; Nightingale, T. J.; O'Carroll, A. G.; Pritchard, M. J.; Remedios, J. J.; Tett, S.

We describe the approach to be adopted for a major new initiative to derive a homogeneous record of sea surface temperature for 1991 2007 from the observations of the series of three along-track scanning radiometers (ATSRs). This initiative is called (A)RC: (Advanced) ATSR Re-analysis for Climate. The main objectives are to reduce regional biases in retrieved sea surface temperature (SST) to less than 0.1 K for all global oceans, while creating a very homogenous record that is stable in time to within 0.05 K decade-1, with maximum independence of the record from existing analyses of SST used in climate change research. If these stringent targets are achieved, this record will enable significantly improved estimates of surface temperature trends and variability of sufficient quality to advance questions of climate change attribution, climate sensitivity and historical reconstruction of surface temperature changes. The approach includes development of new, consistent estimators for SST for each of the ATSRs, and detailed analysis of overlap periods. Novel aspects of the approach include generation of multiple versions of the record using alternative channel sets and cloud detection techniques, to assess for the first time the effect of such choices. There will be extensive effort in quality control, validation and analysis of the impact on climate SST data sets. Evidence for the plausibility of the 0.1 K target for systematic error is reviewed, as is the need for alternative cloud screening methods in this context.

Diagnosis of middle atmosphere chemistry-dynamics interactions

NASA Astrophysics Data System (ADS)

Zhu, X.; Swartz, W. H.; Garcia, R. R.; Chartier, A.; Yee, J. H.; Yue, J.

2017-12-01

We apply the recently developed middle atmosphere climate feedback-response analysis method (MCFRAM) to diagnosing the temperature variations associated with chemistry-dynamics interactions in the middle atmosphere. By using output fields from the Whole Atmosphere Community Climate Model (WACCM) coupled with the measurements, we identify and isolate the distinctive characteristics of different components in the observed temperature variations. Both the temperature trends associated with the anthropogenic forcing and temperature changes associated with natural and internal feedback processes are quantified based on MCFRAM defined partial temperature changes corresponding to localized radiative heating, non-localized chemical heating, eddy transport, and transport by the mean meridional circulation of energy and chemical species. In addition, the temperature responses to variations of CO2, O3, and solar flux have distinctly different spatial structures that can be systematically categorized by the eigenmodes of the generalized damping matrix derived from MCFRAM.

Steps towards a consistent Climate Forecast System Reanalysis wave hindcast (1979-2016)

NASA Astrophysics Data System (ADS)

Stopa, Justin E.; Ardhuin, Fabrice; Huchet, Marion; Accensi, Mickael

2017-04-01

Surface gravity waves are being increasingly recognized as playing an important role within the climate system. Wave hindcasts and reanalysis products of long time series (>30 years) have been instrumental in understanding and describing the wave climate for the past several decades and have allowed a better understanding of extreme waves and inter-annual variability. Wave hindcasts have the advantage of covering the oceans in higher space-time resolution than possible with conventional observations from satellites and buoys. Wave reanalysis systems like ECWMF's ERA-Interim directly included a wave model that is coupled to the ocean and atmosphere, otherwise reanalysis wind fields are used to drive a wave model to reproduce the wave field in long time series. The ERA Interim dataset is consistent in time, but cannot adequately resolve extreme waves. On the other hand, the NCEP Climate Forecast System (CFSR) wind field better resolves the extreme wind speeds, but suffers from discontinuous features in time which are due to the quantity and quality of the remote sensing data incorporated into the product. Therefore, a consistent hindcast that resolves the extreme waves still alludes us limiting our understanding of the wave climate. In this study, we systematically correct the CFSR wind field to reproduce a homogeneous wave field in time. To verify the homogeneity of our hindcast we compute error metrics on a monthly basis using the observations from a merged altimeter wave database which has been calibrated and quality controlled from 1985-2016. Before 1985 only few wave observations exist and are limited to a select number of wave buoys mostly in the North Hemisphere. Therefore we supplement our wave observations with seismic data which responds to nonlinear wave interactions created by opposing waves with nearly equal wavenumbers. Within the CFSR wave hindcast, we find both spatial and temporal discontinuities in the error metrics. The Southern Hemisphere often has wind speed biases larger than the Northern Hemisphere and we propose a simple correction to reduce these features by applying a taper shaped by a half-Hanning window. The discontinuous features in time are corrected by scaling the entire wind field by percentages ranging typically ranging from 1-3%. Our analysis is performed on monthly time series and we expect the monthly statistics to be more adequate for climate studies.

An overview of mineral dust modeling over East Asia

NASA Astrophysics Data System (ADS)

Chen, Siyu; Huang, Jianping; Qian, Yun; Zhao, Chun; Kang, Litai; Yang, Ben; Wang, Yong; Liu, Yuzhi; Yuan, Tiangang; Wang, Tianhe; Ma, Xiaojun; Zhang, Guolong

2017-08-01

East Asian dust (EAD) exerts considerable impacts on the energy balance and climate/climate change of the earth system through its influence on solar and terrestrial radiation, cloud properties, and precipitation efficiency. Providing an accurate description of the life cycle and climate effects of EAD is therefore critical to better understanding of climate change and socioeconomic development in East Asia and even worldwide. Dust modeling has undergone substantial development since the late 1990s, associated with improved understanding of the role of EAD in the earth system. Here, we review the achievements and progress made in recent decades in terms of dust modeling research, including dust emissions, long-range transport, radiative forcing (RF), and climate effects of dust particles over East Asia. Numerous efforts in dust/EAD modeling have been directed towards furnishing more sophisticated physical and chemical processes into the models on higher spatial resolutions. Meanwhile, more systematic observations and more advanced retrieval methods for instruments that address EAD related science issues have made it possible to evaluate model results and quantify the role of EAD in the earth system, and to further reduce the uncertainties in EAD simulations. Though much progress has been made, large discrepancies and knowledge gaps still exist among EAD simulations. The deficiencies and limitations that pertain to the performance of the EAD simulations referred to in the present study are also discussed.

Two hot to handle: How do we manage the simultaneous impacts of climate change and natural disasters on human health?

NASA Astrophysics Data System (ADS)

Phalkey, R. K.; Louis, V. R.

2016-05-01

Climate change is one of the major challenges we face today. There is recognition alongside evidence that the health impacts of both climate change and natural disasters are significant and rising. The impacts of both are also complex and span well beyond health to include environmental, social, demographic, cultural, and economic aspects of human lives. Nonetheless integrated impact assessments are rare and so are system level approaches or systematic preparedness and adaptation strategies to brace the two simultaneously particularly in low and middle-income countries. Ironically the impacts of both climate change as well as natural disasters will be disproportionately borne by low emitters. Sufficiently large and long-term data from comprehensive weather, socio-economic, demographic and health observational systems are currently unavailable to guide adaptation strategies with the necessary precision. In the absence of these and given the uncertainties around the health impact projections alongside the geographic disparities even within the countries, the main question is how can countries then prepare to brace the unknown? We certainly cannot wait to obtain answers to all the questions before we plan solutions. Strengthening health systems is therefore a pragmatic "zero regrets" strategy and should be adopted hastily before the parallel impacts from climate change and associated extreme weather events (disasters thereof) become too hot to handle.

Ensemble climate projections of mean and extreme rainfall over Vietnam

NASA Astrophysics Data System (ADS)

Raghavan, S. V.; Vu, M. T.; Liong, S. Y.

2017-01-01

A systematic ensemble high resolution climate modelling study over Vietnam has been performed using the PRECIS model developed by the Hadley Center in UK. A 5 member subset of the 17-member Perturbed Physics Ensembles (PPE) of the Quantifying Uncertainty in Model Predictions (QUMP) project were simulated and analyzed. The PRECIS model simulations were conducted at a horizontal resolution of 25 km for the baseline period 1961-1990 and a future climate period 2061-2090 under scenario A1B. The results of model simulations show that the model was able to reproduce the mean state of climate over Vietnam when compared to observations. The annual cycles and seasonal averages of precipitation over different sub-regions of Vietnam show the ability of the model in also reproducing the observed peak and magnitude of monthly rainfall. The climate extremes of precipitation were also fairly well captured. Projections of future climate show both increases and decreases in the mean climate over different regions of Vietnam. The analyses of future extreme rainfall using the STARDEX precipitation indices show an increase in 90th percentile precipitation (P90p) over the northern provinces (15-25%) and central highland (5-10%) and over southern Vietnam (up to 5%). The total number of wet days (Prcp) indicates a decrease of about 5-10% all over Vietnam. Consequently, an increase in the wet day rainfall intensity (SDII), is likely inferring that the projected rainfall would be much more severe and intense which have the potential to cause flooding in some regions. Risks due to extreme drought also exist in other regions where the number of wet days decreases. In addition, the maximum 5 day consecutive rainfall (R5d) increases by 20-25% over northern Vietnam but decreases in a similar range over the central and southern Vietnam. These results have strong implications for the management water resources, agriculture, bio diversity and economy and serve as some useful findings to be considered by the policy makers within a wider range of climate uncertainties.

Exploring the implication of climate process uncertainties within the Earth System Framework

NASA Astrophysics Data System (ADS)

Booth, B.; Lambert, F. H.; McNeal, D.; Harris, G.; Sexton, D.; Boulton, C.; Murphy, J.

2011-12-01

Uncertainties in the magnitude of future climate change have been a focus of a great deal of research. Much of the work with General Circulation Models has focused on the atmospheric response to changes in atmospheric composition, while other processes remain outside these frameworks. Here we introduce an ensemble of new simulations, based on an Earth System configuration of HadCM3C, designed to explored uncertainties in both physical (atmospheric, oceanic and aerosol physics) and carbon cycle processes, using perturbed parameter approaches previously used to explore atmospheric uncertainty. Framed in the context of the climate response to future changes in emissions, the resultant future projections represent significantly broader uncertainty than existing concentration driven GCM assessments. The systematic nature of the ensemble design enables interactions between components to be explored. For example, we show how metrics of physical processes (such as climate sensitivity) are also influenced carbon cycle parameters. The suggestion from this work is that carbon cycle processes represent a comparable contribution to uncertainty in future climate projections as contributions from atmospheric feedbacks more conventionally explored. The broad range of climate responses explored within these ensembles, rather than representing a reason for inaction, provide information on lower likelihood but high impact changes. For example while the majority of these simulations suggest that future Amazon forest extent is resilient to the projected climate changes, a small number simulate dramatic forest dieback. This ensemble represents a framework to examine these risks, breaking them down into physical processes (such as ocean temperature drivers of rainfall change) and vegetation processes (where uncertainties point towards requirements for new observational constraints).

A roadmap to effective urban climate change adaptation

NASA Astrophysics Data System (ADS)

Setiadi, R.

2018-03-01

This paper outlines a roadmap to effective urban climate change adaptation built from our practical understanding of the evidence and effects of climate change and the preparation of climate change adaptation strategies and plans. This roadmap aims to drive research in achieving fruitful knowledge and solution-based achievable recommendations in adapting to climate change in urban areas with effective and systematic manner. This paper underscores the importance of the interplay between local government initiatives and a national government for effective adaptation to climate change and takes into account the policy process and politics. This paper argues that effective urban climate change adaptation has a contribution to build urban resilience and helps the achievement of national government goals and targets in climate change adaptation.

Historical trends and high-resolution future climate projections in northern Tuscany (Italy)

NASA Astrophysics Data System (ADS)

D'Oria, Marco; Ferraresi, Massimo; Tanda, Maria Giovanna

2017-12-01

This paper analyzes the historical precipitation and temperature trends and the future climate projections with reference to the northern part of Tuscany (Italy). The trends are identified and quantified at monthly and annual scale at gauging stations with data collected for long periods (60-90 years). An ensemble of 13 Regional Climate Models (RCMs), based on two Representative Concentration Pathways (RCP4.5 and RCP8.5), was then used to assess local scale future precipitation and temperature projections and to represent the uncertainty in the results. The historical data highlight a general decrease of the annual rainfall at a mean rate of 22 mm per decade but, in many cases, the tendencies are not statistically significant. Conversely, the annual mean temperature exhibits an upward trend, statistically significant in the majority of cases, with a warming rate of about 0.1 °C per decade. With reference to the model projections and the annual precipitation, the results are not concordant; the deviations between models in the same period are higher than the future changes at medium- (2031-2040) and long-term (2051-2060) and highlight that the model uncertainty and variability is high. According to the climate model projections, the warming of the study area is unequivocal; a mean positive increment of 0.8 °C at medium-term and 1.1 °C at long-term is expected with respect to the reference period (2003-2012) and the scenario RCP4.5; the increments grow to 0.9 °C and 1.9 °C for the RCP8.5. Finally, in order to check the observed climate change signals, the climate model projections were compared with the trends based on the historical data. A satisfactory agreement is obtained with reference to the precipitation; a systematic underestimation of the trend values with respect to the models, at medium- and long-term, is observed for the temperature data.

Linear Regression Quantile Mapping (RQM) - A new approach to bias correction with consistent quantile trends

NASA Astrophysics Data System (ADS)

Passow, Christian; Donner, Reik

2017-04-01

Quantile mapping (QM) is an established concept that allows to correct systematic biases in multiple quantiles of the distribution of a climatic observable. It shows remarkable results in correcting biases in historical simulations through observational data and outperforms simpler correction methods which relate only to the mean or variance. Since it has been shown that bias correction of future predictions or scenario runs with basic QM can result in misleading trends in the projection, adjusted, trend preserving, versions of QM were introduced in the form of detrended quantile mapping (DQM) and quantile delta mapping (QDM) (Cannon, 2015, 2016). Still, all previous versions and applications of QM based bias correction rely on the assumption of time-independent quantiles over the investigated period, which can be misleading in the context of a changing climate. Here, we propose a novel combination of linear quantile regression (QR) with the classical QM method to introduce a consistent, time-dependent and trend preserving approach of bias correction for historical and future projections. Since QR is a regression method, it is possible to estimate quantiles in the same resolution as the given data and include trends or other dependencies. We demonstrate the performance of the new method of linear regression quantile mapping (RQM) in correcting biases of temperature and precipitation products from historical runs (1959 - 2005) of the COSMO model in climate mode (CCLM) from the Euro-CORDEX ensemble relative to gridded E-OBS data of the same spatial and temporal resolution. A thorough comparison with established bias correction methods highlights the strengths and potential weaknesses of the new RQM approach. References: A.J. Cannon, S.R. Sorbie, T.Q. Murdock: Bias Correction of GCM Precipitation by Quantile Mapping - How Well Do Methods Preserve Changes in Quantiles and Extremes? Journal of Climate, 28, 6038, 2015 A.J. Cannon: Multivariate Bias Correction of Climate Model Outputs - Matching Marginal Distributions and Inter-variable Dependence Structure. Journal of Climate, 29, 7045, 2016

An improved standardization procedure to remove systematic low frequency variability biases in GCM simulations

NASA Astrophysics Data System (ADS)

Mehrotra, Rajeshwar; Sharma, Ashish

2012-12-01

The quality of the absolute estimates of general circulation models (GCMs) calls into question the direct use of GCM outputs for climate change impact assessment studies, particularly at regional scales. Statistical correction of GCM output is often necessary when significant systematic biasesoccur between the modeled output and observations. A common procedure is to correct the GCM output by removing the systematic biases in low-order moments relative to observations or to reanalysis data at daily, monthly, or seasonal timescales. In this paper, we present an extension of a recently published nested bias correction (NBC) technique to correct for the low- as well as higher-order moments biases in the GCM-derived variables across selected multiple time-scales. The proposed recursive nested bias correction (RNBC) approach offers an improved basis for applying bias correction at multiple timescales over the original NBC procedure. The method ensures that the bias-corrected series exhibits improvements that are consistently spread over all of the timescales considered. Different variations of the approach starting from the standard NBC to the more complex recursive alternatives are tested to assess their impacts on a range of GCM-simulated atmospheric variables of interest in downscaling applications related to hydrology and water resources. Results of the study suggest that three to five iteration RNBCs are the most effective in removing distributional and persistence related biases across the timescales considered.

Hospital cultural competency as a systematic organizational intervention: Key findings from the national center for healthcare leadership diversity demonstration project.

PubMed

Weech-Maldonado, Robert; Dreachslin, Janice L; Epané, Josué Patien; Gail, Judith; Gupta, Shivani; Wainio, Joyce Anne

Cultural competency or the ongoing capacity of health care systems to provide for high-quality care to diverse patient populations (National Quality Forum, 2008) has been proposed as an organizational strategy to address disparities in quality of care, patient experience, and workforce representation. But far too many health care organizations still do not treat cultural competency as a business imperative and driver of strategy. The aim of the study was to examine the impact of a systematic, multifaceted, and organizational level cultural competency initiative on hospital performance metrics at the organizational and individual levels. This demonstration project employs a pre-post control group design. Two hospital systems participated in the study. Within each system, two hospitals were selected to serve as the intervention and control hospitals. Executive leadership (C-suite) and all staff at one general medical/surgical nursing unit at the intervention hospitals experienced a systematic, planned cultural competency intervention. Assessments and interventions focused on three organizational level competencies of cultural competency (diversity leadership, strategic human resource management, and patient cultural competency) and three individual level competencies (diversity attitudes, implicit bias, and racial/ethnic identity status). In addition, we evaluated the impact of the intervention on diversity climate and workforce diversity. Overall performance improvement was greater in each of the two intervention hospitals than in the control hospital within the same health care system. Both intervention hospitals experienced improvements in the organizational level competencies of diversity leadership and strategic human resource management. Similarly, improvements were observed in the individual level competencies for diversity attitudes and implicit bias for Blacks among the intervention hospitals. Furthermore, intervention hospitals outperformed their respective control hospitals with respect to diversity climate. A focused and systematic approach to organizational change when coupled with interventions that encourage individual growth and development may be an effective approach to building culturally competent health care organizations.

Using expert opinion to prioritize impacts of climate change on sea turtles' nesting grounds.

PubMed

Fuentes, M M P B; Cinner, J E

2010-12-01

Managers and conservationists often need to prioritize which impacts from climate change to deal with from a long list of threats. However, data which allows comparison of the relative impact from climatic threats for decision-making is often unavailable. This is the case for the management of sea turtles in the face of climate change. The terrestrial life stages of sea turtles can be negatively impacted by various climatic processes, such as sea level rise, altered cyclonic activity, and increased sand temperatures. However, no study has systematically investigated the relative impact of each of these climatic processes, making it challenging for managers to prioritize their decisions and resources. To address this we offer a systematic method for eliciting expert knowledge to estimate the relative impact of climatic processes on sea turtles' terrestrial reproductive phase. For this we used as an example the world's largest population of green sea turtles and asked 22 scientists and managers to answer a paper based survey with a series of pair-wise comparison matrices that compared the anticipated impacts from each climatic process. Both scientists and managers agreed that increased sand temperature will likely cause the most threat to the reproductive output of the nGBR green turtle population followed by sea level rise, then altered cyclonic activity. The methodology used proved useful to determine the relative impact of the selected climatic processes on sea turtles' reproductive output and provided valuable information for decision-making. Thus, the methodological approach can potentially be applied to other species and ecosystems of management concern. Copyright © 2009 Elsevier Ltd. All rights reserved.

Global Changes of the Water Cycle Intensity

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Schubert, Siegfried D.; Walker, Gregory K.

2003-01-01

In this study, we evaluate numerical simulations of the twentieth century climate, focusing on the changes in the intensity of the global water cycle. A new diagnostic of atmospheric water vapor cycling rate is developed and employed, that relies on constituent tracers predicted at the model time step. This diagnostic is compared to a simplified traditional calculation of cycling rate, based on monthly averages of precipitation and total water content. The mean sensitivity of both diagnostics to variations in climate forcing is comparable. However, the new diagnostic produces systematically larger values and more variability than the traditional average approach. Climate simulations were performed using SSTs of the early (1902-1921) and late (1979- 1998) twentieth century along with the appropriate C02 forcing. In general, the increase of global precipitation with the increases in SST that occurred between the early and late twentieth century is small. However, an increase of atmospheric temperature leads to a systematic increase in total precipitable water. As a result, the residence time of water in the atmosphere increased, indicating a reduction of the global cycling rate. This result was explored further using a number of 50-year climate simulations from different models forced with observed SST. The anomalies and trends in the cycling rate and hydrologic variables of different GCMs are remarkably similar. The global annual anomalies of precipitation show a significant upward trend related to the upward trend of surface temperature, during the latter half of the twentieth century. While this implies an increase in the hydrologic cycle intensity, a concomitant increase of total precipitable water again leads to a decrease in the calculated global cycling rate. An analysis of the land/sea differences shows that the simulated precipitation over land has a decreasing trend while the oceanic precipitation has an upward trend consistent with previous studies and the available observations. The decreasing continental trend in precipitation is located primarily over tropical land regions, with some other regions, such as North America experiencing an increasing trend. Precipitation trends are diagnosed further using the water tracers to delineate the precipitation that occurs because of continental evaporation, as opposed to oceanic evaporation. These diagnostics show that over global land areas, the recycling of continental moisture is decreasing in time. However, the recycling changes are not spatially uniform so that some regions, most notably over the United States, experience continental recycling of water that increases in time.

The impact of pCO2 and climate on D/H and 13C/12C fractionation of higher-plant biomarkers: Implications for paleoclimate and paleoelevation reconstruction during global warm periods

NASA Astrophysics Data System (ADS)

Hren, M. T.; Tipple, B. J.; Pagani, M.

2012-12-01

Stable hydrogen isotope compositions (D/H) of plant biomarkers record the hydrogen isotopic composition of leaf water at the time of plant growth. However, the magnitude of the apparent hydrogen isotope fractionation between biomarkers and precipitation can vary due to soil- or leaf-water evaporation or differing water-use strategies. As a result, climate-induced changes in soil- or leaf-water evaporation rates and/or changes in plant assemblages during periods of global warming and high atmospheric CO2 could impact apparent carbon and hydrogen isotope fractionations. We measured hydrogen and carbon isotope ratios of long-carbon chain n-alkanes from modern and ~50 million year old fossil leaves preserved in paleo-Sierra Nevada riverine sediments to determine how climate and ecosystem differences during a period of extremely high pCO2 impact the magnitude and variability of D/H and 13C/12C ratios of leaf-waxes across a topographic gradient. δDalkanes (nC27 to nC31) of individual fossil and modern leaves decrease systematically across the topographic gradient and follow the change in the D/H of precipitation due to orographic lifting and continuous rainout. Using estimated values of Eocene δDprecip at the Pacific margin (-43 to -61‰), apparent fractionations (ɛalkane - precip) for Eocene angiosperm trees are similar to that seen for modern, humid environments (~ -106 to -124‰ ±10‰ 1σ), and more negative than observed in modern sun-exposed leaves in the Sierra Nevada (-96 to -102‰) or soils (-87 to -92‰). Single site variability in leaf-wax δD from individual fossil angiosperms can exceed 20‰, but is considerably smaller than observed for modern, mixed angiosperm/gymnosperm forests of the seasonally dry Sierra Nevada range. δ13Calkane values show little or no systematic variation across the range. However, carbon isotope discrimination in ancient and modern leaves is similar, suggesting strong climatic and weak pCO2 controls on D/H and 13C/12C fractionation. Site average δDalkane of multiple leaves closely mirrors bulk sediment δD values and suggests that the isotopic composition of bulk sediments provides a more robust record of local environmental and hydrologic conditions than analyses of biomarkers from individual leaves.

Cloud Feedbacks in the Climate System: A Critical Review.

NASA Astrophysics Data System (ADS)

Stephens, Graeme L.

2005-01-01

This paper offers a critical review of the topic of cloud-climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet's hydrological cycle to climate radiative forcings.The paper provides a brief overview of the effects of clouds on the radiation budget of the earth-atmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative-convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global-time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis.It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model's credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress.Although progress in understanding the cloud feedback problem has been slow and confused by past analysis, there are legitimate reasons outlined in the paper that give hope for real progress in the future.

Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

NASA Astrophysics Data System (ADS)

Scholze, Marko; Buchwitz, Michael; Dorigo, Wouter; Guanter, Luis; Quegan, Shaun

2017-07-01

The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations.

The Climate Hazards group InfraRed Precipitation (CHIRP) with Stations (CHIRPS): Development and Validation

NASA Astrophysics Data System (ADS)

Peterson, P.; Funk, C. C.; Husak, G. J.; Pedreros, D. H.; Landsfeld, M.; Verdin, J. P.; Shukla, S.

2013-12-01

CHIRP and CHIRPS are new quasi-global precipitation products with daily to seasonal time scales, a 0.05° resolution, and a 1981 to near real-time period of record. Developed by the Climate Hazards Group at UCSB and scientists at the U.S. Geological Survey Earth Resources Observation and Science Center specifically for drought early warning and environmental monitoring, CHIRPS provides moderate latency precipitation estimates that place observed hydrologic extremes in their historic context. Three main types of information are used in the CHIRPS: (1) global 0.05° precipitation climatologies, (2) time-varying grids of satellite-based precipitation estimates, and (3) in situ precipitation observations. CHIRP: The global grids of long-term (1980-2009) average precipitation were estimated for each month based on station data, averaged satellite observations, and physiographic parameters. 1981-present time-varying grids of satellite precipitation were derived from spatially varying regression models based on pentadal cold cloud duration (CCD) values and TRMM V7 training data. The CCD time-series were derived from the CPC and NOAA B1 datasets. Pentadal CCD-percent anomaly values were multiplied by pentadal climatology fields to produce low bias pentadal precipitation estimates. CHIRPS: The CHG station blending procedure uses the satellite-observed spatial covariance structure to assign relative weights to neighboring stations and the CHIRP values. The CHIRPS blending procedure is based on the expected correlation between precipitation at a given target location and precipitation at the locations of the neighboring observation stations. These correlations are estimated using the CHIRP fields. The CHG has developed an extensive archive of in situ daily, pentadal and monthly precipitation totals. The CHG database has over half a billion daily rainfall observations since 1980 and another half billion before 1980. Most of these observations come from four sets of global climate observations: the monthly Global Historical Climate Network version 2 archive, the daily Global Historical Climate Network archive, the Global Summary of the Day dataset (GSOD), and the daily Global Telecommunication System (GTS) archive provided by NOAA's Climate Prediction Center (CPC). A screening procedure was developed to flag and remove potential false zeros from the daily data, since these potentially spurious data can artificially suppress rainfall totals. Validation: Our validation focused on precipitation products with global coverage, long periods of record and near real-time availability: CHIRP, CHIRPS, CPC-Unified, CFS Reanalysis and ECMWF datasets were compared to GPCC and high quality datasets from Uganda, Colombia and the Sahel. The CHIRP and CHIRPS are shown to have low systematic errors (bias) and low mean absolute errors. Analyses in Uganda, Colombia and the Sahel indicate that the ECMWF, CPC-Unified and CFS-Reanalysis have large inhomogeneities, making them unsuitable for drought monitoring. The CHIRPS performance appears quite similar to research quality products like the GPCC and GPCP, but with higher resolution and lower latency.

Long Term Decline in Eastern US Winter Temperature Extremes.

NASA Astrophysics Data System (ADS)

Trenary, L. L.; DelSole, T. M.; Tippett, M. K.; Doty, B.

2016-12-01

States along the US eastern seaboard have experienced successively harsh winter conditions in recent years. This has prompted speculation that climate change is leading to more extreme winter conditions. In this study we quantify changes in the observed winter extremes over the period 1950-2015, by examining year-to-year differences in intensity, frequency and likelihood of daily cold temperature extremes in the north, mid, and south Atlantic states along the US east coast. Analyzing station data for these three regions, we find that while the north and mid-Atlantic regions experienced record-breaking cold temperatures in 2015, there is no long-term increase in the intensity of cold extremes anywhere along the eastern seaboard. Likewise, despite the record number of cold days in these two regions during 2014 and 2015, there is no systematic increase in the frequency of cold extremes. To determine whether the observed changes are natural or human-forced, we repeat our analysis using a suite of climate simulations, with and without external forcing. Generally, model simulations suggest that human-induced forcing does not significantly influence the range of daily winter temperature. Combining this result with the fact that the observed winter temperatures are becoming warmer and less variable, we conclude that the recent intensification of eastern US cold extremes is only temporary.

Can we use Earth Observations to improve monthly water level forecasts?

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.

2017-12-01

Dynamical-statistical hydrologic forecasting approaches benefit from different strengths in comparison with traditional hydrologic forecasting systems: they are computationally efficient, can integrate and `learn' from a broad selection of input data (e.g., General Circulation Model (GCM) forecasts, Earth Observation time series, teleconnection patterns), and can take advantage of recent progress in machine learning (e.g. multi-model blending, post-processing and ensembling techniques). Recent efforts to develop a dynamical-statistical ensemble approach for forecasting seasonal streamflow using both GCM forecasts and changing land cover have shown promising results over the U.S. Midwest. Here, we use climate forecasts from several GCMs of the North American Multi Model Ensemble (NMME) alongside 15-minute stage time series from the National River Flow Archive (NRFA) and land cover classes extracted from the European Space Agency's Climate Change Initiative 300 m annual Global Land Cover time series. With these data, we conduct systematic long-range probabilistic forecasting of monthly water levels in UK catchments over timescales ranging from one to twelve months ahead. We evaluate the improvement in model fit and model forecasting skill that comes from using land cover classes as predictors in the models. This work opens up new possibilities for combining Earth Observation time series with GCM forecasts to predict a variety of hazards from space using data science techniques.

On the climate impacts from the volcanic and solar forcings

NASA Astrophysics Data System (ADS)

Varotsos, Costas A.; Lovejoy, Shaun

2016-04-01

The observed and the modelled estimations show that the main forcings on the atmosphere are of volcanic and solar origins, which act however in an opposite way. The former can be very strong and decrease at short time scales, whereas, the latter increase with time scale. On the contrary, the observed fluctuations in temperatures increase at long scales (e.g. centennial and millennial), and the solar forcings do increase with scale. The common practice is to reduce forcings to radiative equivalents assuming that their combination is linear. In order to clarify the validity of the linearity assumption and determine its range of validity, we systematically compare the statistical properties of solar only, volcanic only and combined solar and volcanic forcings over the range of time scales from one to 1000 years. Additionally, we attempt to investigate plausible reasons for the discrepancies observed between the measured and modeled anomalies of tropospheric temperatures in the tropics. For this purpose, we analyse tropospheric temperature anomalies for both the measured and modeled time series. The results obtained show that the measured temperature fluctuations reveal white noise behavior, while the modeled ones exhibit long-range power law correlations. We suggest that the persistent signal, should be removed from the modeled values in order to achieve better agreement with observations. Keywords: Scaling, Nonlinear variability, Climate system, Solar radiation

Large-Scale Controls of the Surface Water Balance Over Land: Insights From a Systematic Review and Meta-Analysis

NASA Astrophysics Data System (ADS)

Padrón, Ryan S.; Gudmundsson, Lukas; Greve, Peter; Seneviratne, Sonia I.

2017-11-01

The long-term surface water balance over land is described by the partitioning of precipitation (P) into runoff and evapotranspiration (ET), and is commonly characterized by the ratio ET/P. The ratio between potential evapotranspiration (PET) and P is explicitly considered to be the primary control of ET/P within the Budyko framework, whereas all other controls are often integrated into a single parameter, ω. Although the joint effect of these additional controlling factors of ET/P can be significant, a detailed understanding of them is yet to be achieved. This study therefore introduces a new global data set for the long-term mean partitioning of P into ET and runoff in 2,733 catchments, which is based on in situ observations and assembled from a systematic examination of peer-reviewed studies. A total of 26 controls of ET/P that are proposed in the literature are assessed using the new data set. Results reveal that: (i) factors controlling ET/P vary between regions with different climate types; (ii) controls other than PET/P explain at least 35% of the ET/P variance in all regions, and up to ˜90% in arid climates; (iii) among these, climate factors and catchment slope dominate over other landscape characteristics; and (iv) despite the high attention that vegetation-related indices receive as controls of ET/P, they are found to play a minor and often nonsignificant role. Overall, this study provides a comprehensive picture on factors controlling the partitioning of P, with valuable insights for model development, watershed management, and the assessment of water resources around the globe.

Comparing impacts of climate change and mitigation on global agriculture by 2050

NASA Astrophysics Data System (ADS)

van Meijl, Hans; Havlik, Petr; Lotze-Campen, Hermann; Stehfest, Elke; Witzke, Peter; Pérez Domínguez, Ignacio; Bodirsky, Benjamin Leon; van Dijk, Michiel; Doelman, Jonathan; Fellmann, Thomas; Humpenöder, Florian; Koopman, Jason F. L.; Müller, Christoph; Popp, Alexander; Tabeau, Andrzej; Valin, Hugo; van Zeist, Willem-Jan

2018-06-01

Systematic model inter-comparison helps to narrow discrepancies in the analysis of the future impact of climate change on agricultural production. This paper presents a set of alternative scenarios by five global climate and agro-economic models. Covering integrated assessment (IMAGE), partial equilibrium (CAPRI, GLOBIOM, MAgPIE) and computable general equilibrium (MAGNET) models ensures a good coverage of biophysical and economic agricultural features. These models are harmonized with respect to basic model drivers, to assess the range of potential impacts of climate change on the agricultural sector by 2050. Moreover, they quantify the economic consequences of stringent global emission mitigation efforts, such as non-CO2 emission taxes and land-based mitigation options, to stabilize global warming at 2 °C by the end of the century under different Shared Socioeconomic Pathways. A key contribution of the paper is a vis-à-vis comparison of climate change impacts relative to the impact of mitigation measures. In addition, our scenario design allows assessing the impact of the residual climate change on the mitigation challenge. From a global perspective, the impact of climate change on agricultural production by mid-century is negative but small. A larger negative effect on agricultural production, most pronounced for ruminant meat production, is observed when emission mitigation measures compliant with a 2 °C target are put in place. Our results indicate that a mitigation strategy that embeds residual climate change effects (RCP2.6) has a negative impact on global agricultural production relative to a no-mitigation strategy with stronger climate impacts (RCP6.0). However, this is partially due to the limited impact of the climate change scenarios by 2050. The magnitude of price changes is different amongst models due to methodological differences. Further research to achieve a better harmonization is needed, especially regarding endogenous food and feed demand, including substitution across individual commodities, and endogenous technological change.

Developing an approach to effectively use super ensemble experiments for the projection of hydrological extremes under climate change

NASA Astrophysics Data System (ADS)

Watanabe, S.; Kim, H.; Utsumi, N.

2017-12-01

This study aims to develop a new approach which projects hydrology under climate change using super ensemble experiments. The use of multiple ensemble is essential for the estimation of extreme, which is a major issue in the impact assessment of climate change. Hence, the super ensemble experiments are recently conducted by some research programs. While it is necessary to use multiple ensemble, the multiple calculations of hydrological simulation for each output of ensemble simulations needs considerable calculation costs. To effectively use the super ensemble experiments, we adopt a strategy to use runoff projected by climate models directly. The general approach of hydrological projection is to conduct hydrological model simulations which include land-surface and river routing process using atmospheric boundary conditions projected by climate models as inputs. This study, on the other hand, simulates only river routing model using runoff projected by climate models. In general, the climate model output is systematically biased so that a preprocessing which corrects such bias is necessary for impact assessments. Various bias correction methods have been proposed, but, to the best of our knowledge, no method has proposed for variables other than surface meteorology. Here, we newly propose a method for utilizing the projected future runoff directly. The developed method estimates and corrects the bias based on the pseudo-observation which is a result of retrospective offline simulation. We show an application of this approach to the super ensemble experiments conducted under the program of Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI). More than 400 ensemble experiments from multiple climate models are available. The results of the validation using historical simulations by HAPPI indicates that the output of this approach can effectively reproduce retrospective runoff variability. Likewise, the bias of runoff from super ensemble climate projections is corrected, and the impact of climate change on hydrologic extremes is assessed in a cost-efficient way.

Global Impacts and Regional Actions: Preparing for the 1997-98 El Niño.

NASA Astrophysics Data System (ADS)

Buizer, James L.; Foster, Josh; Lund, David

2000-09-01

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.

Objective calibration of regional climate models

NASA Astrophysics Data System (ADS)

Bellprat, O.; Kotlarski, S.; Lüthi, D.; SchäR, C.

2012-12-01

Climate models are subject to high parametric uncertainty induced by poorly confined model parameters of parameterized physical processes. Uncertain model parameters are typically calibrated in order to increase the agreement of the model with available observations. The common practice is to adjust uncertain model parameters manually, often referred to as expert tuning, which lacks objectivity and transparency in the use of observations. These shortcomings often haze model inter-comparisons and hinder the implementation of new model parameterizations. Methods which would allow to systematically calibrate model parameters are unfortunately often not applicable to state-of-the-art climate models, due to computational constraints facing the high dimensionality and non-linearity of the problem. Here we present an approach to objectively calibrate a regional climate model, using reanalysis driven simulations and building upon a quadratic metamodel presented by Neelin et al. (2010) that serves as a computationally cheap surrogate of the model. Five model parameters originating from different parameterizations are selected for the optimization according to their influence on the model performance. The metamodel accurately estimates spatial averages of 2 m temperature, precipitation and total cloud cover, with an uncertainty of similar magnitude as the internal variability of the regional climate model. The non-linearities of the parameter perturbations are well captured, such that only a limited number of 20-50 simulations are needed to estimate optimal parameter settings. Parameter interactions are small, which allows to further reduce the number of simulations. In comparison to an ensemble of the same model which has undergone expert tuning, the calibration yields similar optimal model configurations, but leading to an additional reduction of the model error. The performance range captured is much wider than sampled with the expert-tuned ensemble and the presented methodology is effective and objective. It is argued that objective calibration is an attractive tool and could become standard procedure after introducing new model implementations, or after a spatial transfer of a regional climate model. Objective calibration of parameterizations with regional models could also serve as a strategy toward improving parameterization packages of global climate models.

Toward Civility: Assessment as a Means toward Improving Campus Climate.

ERIC Educational Resources Information Center

Davis, Wanda M.

1998-01-01

Presents assessment as a means toward systematically gauging the climate and culture of American colleges and universities and provides a brief overview of historical factors which impact today's concept of diversity. Includes a discussion of the number and location of incidents related to race, gender, and sexual orientation as reported by the…

Improved cloud parameterization for Arctic climate simulations based on satellite data

NASA Astrophysics Data System (ADS)

Klaus, Daniel; Dethloff, Klaus; Dorn, Wolfgang; Rinke, Annette

2015-04-01

The defective representation of Arctic cloud processes and properties remains a crucial problem in climate modelling and in reanalysis products. Satellite-based cloud observations (MODIS and CPR/CALIOP) and single-column model simulations (HIRHAM5-SCM) were exploited to evaluate and improve the simulated Arctic cloud cover of the atmospheric regional climate model HIRHAM5. The ECMWF reanalysis dataset 'ERA-Interim' (ERAint) was used for the model initialization, the lateral boundary forcing as well as the dynamical relaxation inside the pan-Arctic domain. HIRHAM5 has a horizontal resolution of 0.25° and uses 40 pressure-based and terrain-following vertical levels. In comparison with the satellite observations, the HIRHAM5 control run (HH5ctrl) systematically overestimates total cloud cover, but to a lesser extent than ERAint. The underestimation of high- and mid-level clouds is strongly outweighed by the overestimation of low-level clouds. Numerous sensitivity studies with HIRHAM5-SCM suggest (1) the parameter tuning, enabling a more efficient Bergeron-Findeisen process, combined with (2) an extension of the prognostic-statistical (PS) cloud scheme, enabling the use of negatively skewed beta distributions. This improved model setup was then used in a corresponding HIRHAM5 sensitivity run (HH5sens). While the simulated high- and mid-level cloud cover is improved only to a limited extent, the large overestimation of low-level clouds can be systematically and significantly reduced, especially over sea ice. Consequently, the multi-year annual mean area average of total cloud cover with respect to sea ice is almost 14% lower than in HH5ctrl. Overall, HH5sens slightly underestimates the observed total cloud cover but shows a halved multi-year annual mean bias of 2.2% relative to CPR/CALIOP at all latitudes north of 60° N. Importantly, HH5sens produces a more realistic ratio between the cloud water and ice content. The considerably improved cloud simulation manifests in a more correct radiative transfer and better energy budget in the atmospheric boundary layer and results also in a more realistic surface energy budget associated with more reasonable turbulent fluxes. All this mitigates the positive temperature, relative humidity and horizontal wind speed biases in the lower model levels.

Climate change and sustainable development: realizing the opportunity.

PubMed

Robinson, John; Bradley, Mike; Busby, Peter; Connor, Denis; Murray, Anne; Sampson, Bruce; Soper, Wayne

2006-02-01

Manifold linkages exist between climate change and sustainable development. Although these are starting to receive attention in the climate exchange literature, the focus has typically been on examining sustainable development through a climate change lens, rather than vice versa. And there has been little systematic examination of how these linkages may be fostered in practice. This paper examines climate change through a sustainable development lens. To illustrate how this might change the approach to climate change issues, it reports on the findings of a panel of business, local government, and academic representatives in British Columbia, Canada, who were appointed to advise the provincial government on climate change policy. The panel found that sustainable development may offer a significantly more fruitful way to pursue climate policy goals than climate policy itself. The paper discusses subsequent climate change developments in the province and makes suggestions as how best to pursue such a sustainability approach in British Columbia and other jurisdictions.

Shifting plant species composition in response to climate change stabilizes grassland primary production

PubMed Central

Liu, Huiying; Mi, Zhaorong; Lin, Li; Wang, Yonghui; Zhang, Zhenhua; Zhang, Fawei; Wang, Hao; Liu, Lingli; Zhu, Biao; Cao, Guangmin; Zhao, Xinquan; Sanders, Nathan J.; Reich, Peter B.

2018-01-01

The structure and function of alpine grassland ecosystems, including their extensive soil carbon stocks, are largely shaped by temperature. The Tibetan Plateau in particular has experienced significant warming over the past 50 y, and this warming trend is projected to intensify in the future. Such climate change will likely alter plant species composition and net primary production (NPP). Here we combined 32 y of observations and monitoring with a manipulative experiment of temperature and precipitation to explore the effects of changing climate on plant community structure and ecosystem function. First, long-term climate warming from 1983 to 2014, which occurred without systematic changes in precipitation, led to higher grass abundance and lower sedge abundance, but did not affect aboveground NPP. Second, an experimental warming experiment conducted over 4 y had no effects on any aspect of NPP, whereas drought manipulation (reducing precipitation by 50%), shifted NPP allocation belowground without affecting total NPP. Third, both experimental warming and drought treatments, supported by a meta-analysis at nine sites across the plateau, increased grass abundance at the expense of biomass of sedges and forbs. This shift in functional group composition led to deeper root systems, which may have enabled plant communities to acquire more water and thus stabilize ecosystem primary production even with a changing climate. Overall, our study demonstrates that shifting plant species composition in response to climate change may have stabilized primary production in this high-elevation ecosystem, but it also caused a shift from aboveground to belowground productivity. PMID:29666319

Attribution of extreme weather and climate-related events.

PubMed

Stott, Peter A; Christidis, Nikolaos; Otto, Friederike E L; Sun, Ying; Vanderlinden, Jean-Paul; van Oldenborgh, Geert Jan; Vautard, Robert; von Storch, Hans; Walton, Peter; Yiou, Pascal; Zwiers, Francis W

2016-01-01

Extreme weather and climate-related events occur in a particular place, by definition, infrequently. It is therefore challenging to detect systematic changes in their occurrence given the relative shortness of observational records. However, there is a clear interest from outside the climate science community in the extent to which recent damaging extreme events can be linked to human-induced climate change or natural climate variability. Event attribution studies seek to determine to what extent anthropogenic climate change has altered the probability or magnitude of particular events. They have shown clear evidence for human influence having increased the probability of many extremely warm seasonal temperatures and reduced the probability of extremely cold seasonal temperatures in many parts of the world. The evidence for human influence on the probability of extreme precipitation events, droughts, and storms is more mixed. Although the science of event attribution has developed rapidly in recent years, geographical coverage of events remains patchy and based on the interests and capabilities of individual research groups. The development of operational event attribution would allow a more timely and methodical production of attribution assessments than currently obtained on an ad hoc basis. For event attribution assessments to be most useful, remaining scientific uncertainties need to be robustly assessed and the results clearly communicated. This requires the continuing development of methodologies to assess the reliability of event attribution results and further work to understand the potential utility of event attribution for stakeholder groups and decision makers. WIREs Clim Change 2016, 7:23-41. doi: 10.1002/wcc.380 For further resources related to this article, please visit the WIREs website.

You can't improve what you don't measure: Safety climate measures available in the German-speaking countries to support safety culture development in healthcare.

PubMed

Manser, Tanja; Brösterhaus, Mareen; Hammer, Antje

2016-01-01

Safety climate measurement is a key input into safety culture development. The aim of this review is to provide an overview of the safety climate measures that have been evaluated for their psychometric properties in a German-speaking country and to make recommendations on how to use them in quality and patient safety improvement. A systematic search strategy was implemented to obtain relevant articles. PubMed and Web of Science databases were searched, and 128 abstracts were identified. After application of limits, 33 full texts were retrieved for subsequent evaluation. Studies were included on the basis of predetermined inclusion criteria and independent assessment by two reviewers. Publications were reviewed concerning healthcare setting, target group, safety culture dimensions covered and results of their psychometric evaluation. This review identified 11 instruments for safety climate assessment in different healthcare settings (i. e. hospitals, nursing homes, primary care, dental care and community pharmacy) for which acceptable to good internal consistency was reported. We observed wide variability concerning the number of dimensions (1 to 14; in some cases including outcome dimensions) and items (9 to 128) that the instruments were comprised of. Nevertheless, consistency with regard to the thematic areas covered was rather high. While there is clear evidence that we can assess safety climate in healthcare, the application of safety climate measures by quality and patient safety practitioners has so far been rather limited. This review bridges this gap between research and improvement practice by highlighting the central role of safety climate assessment in a mixed methods approach to inform safety culture development. Copyright © 2016. Published by Elsevier GmbH.

Assessing safety climate in acute hospital settings: a systematic review of the adequacy of the psychometric properties of survey measurement tools.

PubMed

Alsalem, Gheed; Bowie, Paul; Morrison, Jillian

2018-05-10

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.

LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

NASA Technical Reports Server (NTRS)

Van Den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; Seneviratne, Sonia I.; Derksen, Chris; Oki, Taikan; Douville, Herve; Colin, Jeanne; Ducharne, Agnes; Cheruy, Frederique;

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

DOE PAGES

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; ...

2016-08-24

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

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

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

Improving oceanographic data delivery through pipeline processing in a Commercial Cloud Services environment: the Australian Integrated Marine Observing System

NASA Astrophysics Data System (ADS)

Besnard, Laurent; Blain, Peter; Mancini, Sebastien; Proctor, Roger

2017-04-01

The Integrated Marine Observing System (IMOS) is a national project funded by the Australian government established to deliver ocean observations to the marine and climate science community. Now in its 10th year its mission is to undertake systematic and sustained observations and to turn them into data, products and analyses that can be freely used and reused for broad societal benefits. As IMOS has matured as an observing system expectation on the system's availability and reliability has also increased and IMOS is now seen as delivering 'operational' information. In responding to this expectation, IMOS has relocated its services to the commercial cloud service Amazon Web Services. This has enabled IMOS to improve the system architecture, utilizing more advanced features like object storage (S3 - Simple Storage Service) and autoscaling features, and introducing new checking procedures in a pipeline approach. This has improved data availability and resilience while protecting against human errors in data handling and providing a more efficient ingestion process.

Advancing Climate Change and Impacts Science Through Climate Informatics

NASA Astrophysics Data System (ADS)

Lenhardt, W.; Pouchard, L. C.; King, A. W.; Branstetter, M. L.; Kao, S.; Wang, D.

2010-12-01

This poster will outline the work to date on developing a climate informatics capability at Oak Ridge National Laboratory (ORNL). The central proposition of this effort is that the application of informatics and information science to the domain of climate change science is an essential means to bridge the realm of high performance computing (HPC) and domain science. The goal is to facilitate knowledge capture and the creation of new scientific insights. For example, a climate informatics capability will help with the understanding and use of model results in domain sciences that were not originally in the scope. From there, HPC can also benefit from feedback as the new approaches may lead to better parameterization in the models. In this poster we will summarize the challenges associated with climate change science that can benefit from the systematic application of informatics and we will highlight our work to date in creating the climate informatics capability to address these types of challenges. We have identified three areas that are particularly challenging in the context of climate change science: 1) integrating model and observational data across different spatial and temporal scales, 2) model linkages, i.e. climate models linked to other models such as hydrologic models, and 3) model diagnostics. Each of these has a methodological component and an informatics component. Our project under way at ORNL seeks to develop new approaches and tools in the context of linking climate change and water issues. We are basing our work on the following four use cases: 1) Evaluation/test of CCSM4 biases in hydrology (precipitation, soil water, runoff, river discharge) over the Rio Grande Basin. User: climate modeler. 2) Investigation of projected changes in hydrology of Rio Grande Basin using the VIC (Variable Infiltration Capacity Macroscale) Hydrologic Model. User: watershed hydrologist/modeler. 3) Impact of climate change on agricultural productivity of the Rio Grande Basin. User: climate impact scientist, agricultural economist. 4) Renegotiation of the 1944 “Treaty for the Utilization of Waters of the Colorado and Tijuana Rivers and of the Rio Grande”. User: A US State Department analyst or their counterpart in Mexico.

Urban Cholera and Water Sustainability Challenges under Climatic and Anthropogenic Change

NASA Astrophysics Data System (ADS)

Akanda, A. S.; Jutla, A.; Huq, A.; Faruque, A. G.; Colwell, R. R.

2013-12-01

The last three decades of surveillance data shows a drastic increase of cholera prevalence in the largest cholera-endemic city of the world - Dhaka, Bangladesh. Emerging megacities in the developing world, especially those located in coastal regions of the tropics remain vulnerable to similar. However, there has not been any systematic study on linking the long-term disease trends with changes in related climatic, environmental, or societal variables. Here, we analyze the 30-year dynamics of urban cholera prevalence in Dhaka with changes in climatic or societal factors: regional hydrology, flooding, water usage, changes in distribution systems, population growth and density in urban settlements, as well as shifting climate patterns. An interesting change is observed in the seasonal trends of cholera incidence; while an endemic upward trend is seen in the dry season, the post-monsoon trend seem to be more epidemic in nature. Evidence points to growing urbanization and rising population in unplanned settlements that have negligible to poor water and sanitation systems compounded by increasing frequency of record flood events. Growing water scarcity in the dry season and lack of sustainable water and sanitation infrastructure for urban settlements have increased endemicity of spring outbreaks, while record flood events and prolonged post-monsoon inundation have contributed to increased epidemic outbreaks in fall. We analyze our findings with the World Health Organization recommended guidelines and investigate water sustainability challenges in the context of climatic and anthropogenic changes in the region.

Preface: Impacts of extreme climate events and disturbances on carbon dynamics

USGS Publications Warehouse

Xiao, Jingfeng; Liu, Shuguang; Stoy, Paul C.

2016-01-01

The impacts of extreme climate events and disturbances (ECE&D) on the carbon cycle have received growing attention in recent years. This special issue showcases a collection of recent advances in understanding the impacts of ECE&D on carbon cycling. Notable advances include quantifying how harvesting activities impact forest structure, carbon pool dynamics, and recovery processes; observed drastic increases of the concentrations of dissolved organic carbon and dissolved methane in thermokarst lakes in western Siberia during a summer warming event; disentangling the roles of herbivores and fire on forest carbon dioxide flux; direct and indirect impacts of fire on the global carbon balance; and improved atmospheric inversion of regional carbon sources and sinks by incorporating disturbances. Combined, studies herein indicate several major research needs. First, disturbances and extreme events can interact with one another, and it is important to understand their overall impacts and also disentangle their effects on the carbon cycle. Second, current ecosystem models are not skillful enough to correctly simulate the underlying processes and impacts of ECE&D (e.g., tree mortality and carbon consequences). Third, benchmark data characterizing the timing, location, type, and magnitude of disturbances must be systematically created to improve our ability to quantify carbon dynamics over large areas. Finally, improving the representation of ECE&D in regional climate/earth system models and accounting for the resulting feedbacks to climate are essential for understanding the interactions between climate and ecosystem dynamics.

Evidence of resilience to past climate change in Southwest Asia: Early farming communities and the 9.2 and 8.2 ka events

NASA Astrophysics Data System (ADS)

Flohr, Pascal; Fleitmann, Dominik; Matthews, Roger; Matthews, Wendy; Black, Stuart

2016-03-01

Climate change is often cited as a major factor in social change. The so-called 8.2 ka event was one of the most pronounced and abrupt Holocene cold and arid events. The 9.2 ka event was similar, albeit of a smaller magnitude. Both events affected the Northern Hemisphere climate and caused cooling and aridification in Southwest Asia. Yet, the impacts of the 8.2 and 9.2 ka events on early farming communities in this region are not well understood. Current hypotheses for an effect of the 8.2 ka event vary from large-scale site abandonment and migration (including the Neolithisation of Europe) to continuation of occupation and local adaptation, while impacts of the 9.2 ka have not previously been systematically studied. In this paper, we present a thorough assessment of available, quality-checked radiocarbon (14C) dates for sites from Southwest Asia covering the time interval between 9500 and 7500 cal BP, which we interpret in combination with archaeological evidence. In this way, the synchronicity between changes observed in the archaeological record and the rapid climate events is tested. It is shown that there is no evidence for a simultaneous and widespread collapse, large-scale site abandonment, or migration at the time of the events. However, there are indications for local adaptation. We conclude that early farming communities were resilient to the abrupt, severe climate changes at 9250 and 8200 cal BP.

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

NASA Technical Reports Server (NTRS)

Funk, Chris; Peterson, Pete; Shukla, Shraddhanand; Husak, Gregory; Landsfeld, Marty; Hoell, Andrew; Pedreros, Diego; Roberts, J. B.; Robertson, F. R.; Tadesse, Tsegae;

A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

DOE PAGES

Zhang, Yu; Pan, Ming; Sheffield, Justin; ...

2018-01-12

Closing the terrestrial water budget is necessary to provide consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g., in situ observation, satellite remote sensing, land surface model, and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. Conditioned on the current limited data availability, a systematic method is developed to optimally combine multiple available data sources for precipitation ( P), evapotranspiration (ET), runoff ( R), and the totalmore » water storage change (TWSC) at 0.5° spatial resolution globally and to obtain water budget closure (i.e., to enforce P-ET- R-TWSC = 0) through a constrained Kalman filter (CKF) data assimilation technique under the assumption that the deviation from the ensemble mean of all data sources for the same budget variable is used as a proxy of the uncertainty in individual water budget variables. The resulting long-term (1984–2010), monthly 0.5° resolution global terrestrial water cycle Climate Data Record (CDR) data set is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This data set serves to bridge the gap between sparsely gauged regions and the regions with sufficient in situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS), and ET from FLUXNET. The data set is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.« less

A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

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

Zhang, Yu; Pan, Ming; Sheffield, Justin

Closing the terrestrial water budget is necessary to provide consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g., in situ observation, satellite remote sensing, land surface model, and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. Conditioned on the current limited data availability, a systematic method is developed to optimally combine multiple available data sources for precipitation ( P), evapotranspiration (ET), runoff ( R), and the totalmore » water storage change (TWSC) at 0.5° spatial resolution globally and to obtain water budget closure (i.e., to enforce P-ET- R-TWSC = 0) through a constrained Kalman filter (CKF) data assimilation technique under the assumption that the deviation from the ensemble mean of all data sources for the same budget variable is used as a proxy of the uncertainty in individual water budget variables. The resulting long-term (1984–2010), monthly 0.5° resolution global terrestrial water cycle Climate Data Record (CDR) data set is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This data set serves to bridge the gap between sparsely gauged regions and the regions with sufficient in situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS), and ET from FLUXNET. The data set is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.« less

Development of a Water Clarity Index for the Southeastern U.S. As a Climate Indicator

NASA Astrophysics Data System (ADS)

Sheridan, S. C.; Hu, C.; Lee, C. C.; Barnes, B.; Pirhalla, D.; Ransi, V.; Shein, K. A.

2014-12-01

A common index of water quality is water clarity, which can be estimated by measuring the diffuse attenuation coefficient for downwelling irradiance (Kd). Kd estimates the availability of light to marine organisms at various depths. Marine habitats, including such species as coral and seagrass, can be negatively affected by extreme episodes of sediment suspension, where water clarity is reduced and little light penetrates. Evidence of increased stress on coastal ecosystems exists, partially due to climate change, yet a systematic analysis of extreme events and trends is difficult due to limited data. To address this concern, we have developed as a potential climate indicator a Kd-Index for nine regions along the US coast of the Gulf of Mexico, in which Kd values have been standardized over time and space to allow for a more holistic assessment of climate drivers and their trends. Variability in the Kd-Index is then assessed with regard to occurrences of surface weather types (using the Spatial Synoptic Classification), a synoptic climatology of mean sea-level-pressure patterns across the region, along with heavy precipitation events. Kd can be estimated from MODIS and SeaWiFS observations from 1997 to date; an earlier period of satellite observations from 1978-86 is also available. A non-linear autoregressive neural network model with external input (NARX) is used to develop the historical relationship between Kd-Index and atmospheric conditions, and then this model is used to simulate a full time series from 1948 to 2013. The modeled data set is strongly correlated with observations, with correlations above 0.8 for many regions. Hit rates of extreme Kd-Index values - those which would most likely be associated with a negative environmental impact - exceed 70% in some regions. Across the full data set, long term trends vary slightly across regions but are generally small. Trends in extreme events appear to be more consistently increasing across the domain.

A Climate Data Record (CDR) for the global terrestrial water budget: 1984-2010

NASA Astrophysics Data System (ADS)

Zhang, Yu; Pan, Ming; Sheffield, Justin; Siemann, Amanda L.; Fisher, Colby K.; Liang, Miaoling; Beck, Hylke E.; Wanders, Niko; MacCracken, Rosalyn F.; Houser, Paul R.; Zhou, Tian; Lettenmaier, Dennis P.; Pinker, Rachel T.; Bytheway, Janice; Kummerow, Christian D.; Wood, Eric F.

2018-01-01

Closing the terrestrial water budget is necessary to provide consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g., in situ observation, satellite remote sensing, land surface model, and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. Conditioned on the current limited data availability, a systematic method is developed to optimally combine multiple available data sources for precipitation (P), evapotranspiration (ET), runoff (R), and the total water storage change (TWSC) at 0.5° spatial resolution globally and to obtain water budget closure (i.e., to enforce P - ET - R - TWSC = 0) through a constrained Kalman filter (CKF) data assimilation technique under the assumption that the deviation from the ensemble mean of all data sources for the same budget variable is used as a proxy of the uncertainty in individual water budget variables. The resulting long-term (1984-2010), monthly 0.5° resolution global terrestrial water cycle Climate Data Record (CDR) data set is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This data set serves to bridge the gap between sparsely gauged regions and the regions with sufficient in situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS), and ET from FLUXNET. The data set is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.

Temporal distribution of suicide mortality: A systematic review.

PubMed

Galvão, Pauliana Valéria Machado; Silva, Hugo Rafael Souza E; Silva, Cosme Marcelo Furtado Passos da

2018-03-01

suicide is a problem with world impact and the leading cause of premature deaths. The study of its distribution over time can bring a changed understanding of parameters attributed to, and the prevention of, suicide. to identify the temporal pattern of suicide by systematic review. Pubmed (Medline), LILACS, Virtual Health Library (VHL), Science Direct and Scopus (Elsevier), Web of Science (Thomson Reuters) and PsyNET (APA) were searched, using suicide-related descriptors and terms, for observational epidemiological studies of the temporal distribution of suicide. The review protocol was registered in PROSPERO (CRD42016038470). The lack of uniformity in reporting or standardisation of methodology in the studies selected, hindered comparison of populations with similar socioeconomic and cultural profiles, considerably limiting the scope of the results of this review. forty-five studies from 26 different countries were included in this review. Clear seasonal patterns were observed by day of the week, month, season and age-period-cohort effects. Few studies studied by trend, time of day or day of the month. the review findings provide further evidence of substantial temporal patterns influenced by geographic, climatic and social conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Continental drift and climate change drive instability in insect assemblages

NASA Astrophysics Data System (ADS)

Li, Fengqing; Tierno de Figueroa, José Manuel; Lek, Sovan; Park, Young-Seuk

2015-06-01

Global change has already had observable effects on ecosystems worldwide, and the accelerated rate of global change is predicted in the future. However, the impacts of global change on the stability of biodiversity have not been systematically studied in terms of both large spatial (continental drift) and temporal (from the last inter-glacial period to the next century) scales. Therefore, we analyzed the current geographical distribution pattern of Plecoptera, a thermally sensitive insect group, and evaluated its stability when coping with global change across both space and time throughout the Mediterranean region—one of the first 25 global biodiversity hotspots. Regional biodiversity of Plecoptera reflected the geography in both the historical movements of continents and the current environmental conditions in the western Mediterranean region. The similarity of Plecoptera assemblages between areas in this region indicated that the uplift of new land and continental drift were the primary determinants of the stability of regional biodiversity. Our results revealed that climate change caused the biodiversity of Plecoptera to slowly diminish in the past and will cause remarkably accelerated biodiversity loss in the future. These findings support the theory that climate change has had its greatest impact on biodiversity over a long temporal scale.

Evaluating controls on fluvial sand-body clustering in the Ferris Formation (Cretaceous/Paleogene, Wyoming, USA)

NASA Astrophysics Data System (ADS)

Hajek, E. A.; Heller, P.

2009-12-01

A primary goal of sedimentary geologists is to interpret past tectonic, climatic, and eustatic conditions from the stratigraphic record. Stratigraphic changes in alluvial-basin fills are routinely interpreted as the result of past tectonic movements or changes in climate or sea level. Recent physical and numerical models have shown that sedimentary systems can exhibit self-organization on basin-filling time scales, suggesting that structured stratigraphic patterns can form spontaneously rather than as the result of changing boundary conditions. The Ferris Formation (Upper Cretaceous/Paleogene, Hanna Basin, Wyoming) exhibits stratigraphic organization where clusters of closely-spaced channel deposits are separated from other clusters by intervals dominated by overbank material. In order to evaluate the role of basinal controls on deposition and ascertain the potential for self-organization in this ancient deposit, the spatial patterns of key channel properties (including sand-body dimensions, paleoflow depth, maximum clast size, paleocurrent direction, and sediment provenance) are analyzed. Overall the study area lacks strong trends sand-body properties through the stratigraphic succession and in cluster groups. Consequently there is no indication that the stratigraphic pattern observed in the Ferris Formation was driven by systematic changes in climate or tectonics.

Continental drift and climate change drive instability in insect assemblages

PubMed Central

Li, Fengqing; Tierno de Figueroa, José Manuel; Lek, Sovan; Park, Young-Seuk

2015-01-01

Global change has already had observable effects on ecosystems worldwide, and the accelerated rate of global change is predicted in the future. However, the impacts of global change on the stability of biodiversity have not been systematically studied in terms of both large spatial (continental drift) and temporal (from the last inter-glacial period to the next century) scales. Therefore, we analyzed the current geographical distribution pattern of Plecoptera, a thermally sensitive insect group, and evaluated its stability when coping with global change across both space and time throughout the Mediterranean region—one of the first 25 global biodiversity hotspots. Regional biodiversity of Plecoptera reflected the geography in both the historical movements of continents and the current environmental conditions in the western Mediterranean region. The similarity of Plecoptera assemblages between areas in this region indicated that the uplift of new land and continental drift were the primary determinants of the stability of regional biodiversity. Our results revealed that climate change caused the biodiversity of Plecoptera to slowly diminish in the past and will cause remarkably accelerated biodiversity loss in the future. These findings support the theory that climate change has had its greatest impact on biodiversity over a long temporal scale. PMID:26081036

Continental drift and climate change drive instability in insect assemblages.

PubMed

Li, Fengqing; Tierno de Figueroa, José Manuel; Lek, Sovan; Park, Young-Seuk

2015-06-17

Global change has already had observable effects on ecosystems worldwide, and the accelerated rate of global change is predicted in the future. However, the impacts of global change on the stability of biodiversity have not been systematically studied in terms of both large spatial (continental drift) and temporal (from the last inter-glacial period to the next century) scales. Therefore, we analyzed the current geographical distribution pattern of Plecoptera, a thermally sensitive insect group, and evaluated its stability when coping with global change across both space and time throughout the Mediterranean region--one of the first 25 global biodiversity hotspots. Regional biodiversity of Plecoptera reflected the geography in both the historical movements of continents and the current environmental conditions in the western Mediterranean region. The similarity of Plecoptera assemblages between areas in this region indicated that the uplift of new land and continental drift were the primary determinants of the stability of regional biodiversity. Our results revealed that climate change caused the biodiversity of Plecoptera to slowly diminish in the past and will cause remarkably accelerated biodiversity loss in the future. These findings support the theory that climate change has had its greatest impact on biodiversity over a long temporal scale.

Damage capitation in the modern liability climate: a primer for neurosurgeons and systematic review of the literature.

PubMed

Lepard, Jacob R; Walters, Beverly C; Rozzelle, Curtis J

2018-04-01

OBJECTIVE Neurosurgery, and particularly spine surgery, is among the most highly litigated medical specialties in the US, rendering the current malpractice climate of primary importance to spine surgeons nationwide. One of the primary methods of tort reform in the civil justice system is malpractice damage capitation (or "caps"); however, its efficacy is widely debated. The purpose of this article is to serve as a review for the practicing neurosurgeon, with particular emphasis on short- and long-term effects of damage caps and on the current debate regarding their utility, based on a systematic review of the literature. METHODS The Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelines for systematic review of observational studies were used in the design of the study. Multiple medical and legal online databases (MEDLINE, Scopus, EMBASE, and JSTOR) were queried using the key words "malpractice" and "damage capitation" for articles from 2000 to 2014. A total of 96 abstracts were screened for inclusion and exclusion criteria. Of these, 22 articles were reviewed in full and another 15 were excluded for study design or poor quality of data. Five more studies were added after cross-checking the bibliographies of the included articles. The resulting 12 articles were evaluated; relevant data were extracted using a standardized metric. RESULTS Five studies were found showing varying effects of capitation on physician availability, with only 1 of these specifically showing increased availability of neurosurgery and elective spine coverage in states with capitation. Four studies demonstrated that capitation overall succeeds in decreasing jury awards and frequency of claims filed. Last, 3 studies were found showing an overall decrease in malpractice premiums for states that passed damage capitation. CONCLUSIONS There is evidence in the literature showing that total and noneconomic damage capitation has the potential to improve the practice environment for neurosurgeons nationwide. Additionally, there are other factors that affect malpractice premium rates, such as the investment markets, which are not affected by these laws. All of these are important for spine surgeons to consider and be aware of in advocating for appropriate reform measures in their states.

The Problem of Alluvial Fan Slopes

NASA Astrophysics Data System (ADS)

Stock, J. D.; Schmidt, K.

2005-12-01

Water and debris flows exiting confined valleys have a tendency to deposit sediment on steep fans. On alluvial fans, where water transport predominates, channel slopes tend to decrease downfan from ~0.08 to ~0.01 across wide ranges of climate and tectonism. Some have argued that this pattern reflects downfan grainsize fining so that higher slopes are required just to entrain coarser particles in the waters of the upper fan, while entrainment of finer grains downfan requires lower slopes (threshold hypothesis). An older hypothesis is that slope is adjusted to transport the supplied sediment load, which decreases downfan as deposition occurs (transport hypothesis). We have begun to test these hypotheses using detailed field measurements of hydraulic and sediment variables in sediment transport models. On some fans in the western U.S. we find that alluvial fan channel bankfull depths are largely 0.5-1.5 m at fan heads, decreasing to 0.1-0.2 m at distal margins. Contrary to many previous studies, we find that median gravel diameter does not change systematically along the upper 60- 80% of active fan channels. So downstream gravel fining cannot explain most of the observed channel slope reduction. However, as slope declines, surface sand cover increases systematically downfan from values of <20% above fan heads to distal fan values in excess of 70%. As a result, the threshold for sediment motion might decrease systematically downfan, leading to lower slopes. However, current models of this effect alone tend to underpredict downfan slope changes. This is likely due to off- channel gravel deposition. Calculations that match observed fan long-profiles require an exponential decline in gravel transport rate, so that on some fans approximately half of the load must be deposited off-channel every ~0.25-1.25 km downfan. This leads us to hypothesize that alluvial fan long- profiles are largely statements about the rate of deposition downfan. If so, there may be climatic and tectonic information in the long-profile, but a mechanistic theory for downfan deposition rate will be needed.

Maritime Continent seasonal climate biases in AMIP experiments of the CMIP5 multimodel ensemble

NASA Astrophysics Data System (ADS)

Toh, Ying Ying; Turner, Andrew G.; Johnson, Stephanie J.; Holloway, Christopher E.

2018-02-01

The fidelity of 28 Coupled Model Intercomparison Project phase 5 (CMIP5) models in simulating mean climate over the Maritime Continent in the Atmospheric Model Intercomparison Project (AMIP) experiment is evaluated in this study. The performance of AMIP models varies greatly in reproducing seasonal mean climate and the seasonal cycle. The multi-model mean has better skill at reproducing the observed mean climate than the individual models. The spatial pattern of 850 hPa wind is better simulated than the precipitation in all four seasons. We found that model horizontal resolution is not a good indicator of model performance. Instead, a model's local Maritime Continent biases are somewhat related to its biases in the local Hadley circulation and global monsoon. The comparison with coupled models in CMIP5 shows that AMIP models generally performed better than coupled models in the simulation of the global monsoon and local Hadley circulation but less well at simulating the Maritime Continent annual cycle of precipitation. To characterize model systematic biases in the AMIP runs, we performed cluster analysis on Maritime Continent annual cycle precipitation. Our analysis resulted in two distinct clusters. Cluster I models are able to capture both the winter monsoon and summer monsoon shift, but they overestimate the precipitation; especially during the JJA and SON seasons. Cluster II models simulate weaker seasonal migration than observed, and the maximum rainfall position stays closer to the equator throughout the year. The tropics-wide properties of these clusters suggest a connection between the skill of simulating global properties of the monsoon circulation and the skill of simulating the regional scale of Maritime Continent precipitation.

Controls on desert dune activity - a geospatial approach

NASA Astrophysics Data System (ADS)

Lancaster, N.; Hesse, P. P.

2017-12-01

Desert and other inland dunes occur on a wide spectrum of activity (defined loosely as the proportion of the surface area subject to sand movement) from unvegetated to sparsely vegetated "active" dunes through discontinuously vegetated inactive dunes to completely vegetated and degraded dunes. Many of the latter are relicts of past climatic conditions. Although field studies and modeling of the interactions between winds, vegetation cover, and dune activity can provide valuable insights, the response of dune systems to climate change and variability past, present, and future has until now been hampered by the lack of pertinent observational data on geomorphic and climatic boundary conditions and dune activity status for most dune areas. We have developed GIS-based approach that permits analysis of boundary conditions and controls on dune activity at a range of spatial scales from dunefield to global. In this approach, the digital mapping of dune field and sand sea extent has been combined with systematic observations of dune activity at 0.2° intervals from high resolution satellite image data, resulting in four classes of activity. 1 km resolution global gridded datasets for the aridity index (AI); precipitation, satellite-derived percent vegetation cover; and estimates of sand transport potential (DP) were re-sampled for each 0.2° grid cell, and dune activity was compared to vegetation cover, sand transport potential, precipitation, and the aridity index. Results so far indicate that there are broad-scale relationships between dunefield mean activity, climate, and vegetation cover. However, the scatter in the data suggest that other local factors may be at work. Intra-dune field patterns are complex in many cases. Overall, much more work needs to be done to gain a full understanding of controls at different spatial and temporal scales, which can be faciliated by this spatial database.

How does Interactive Chemistry Influence the Representation of Stratosphere-Troposphere Coupling in a Climate Model?

NASA Astrophysics Data System (ADS)

Haase, S.; Matthes, K. B.

2017-12-01

Changes in stratospheric ozone can trigger tropospheric circulation changes. In the Southern hemisphere (SH), the observed shift of the Southern Annular Mode was attributed to the observed trend in lower stratospheric ozone. In the Northern Hemisphere (NH), a recent study showed that extremely low stratospheric ozone conditions during spring produce robust anomalies in the troposphere (zonal wind, temperature and precipitation). This could only be reproduced in a coupled chemistry climate model indicating that chemical-dynamical feedbacks are also important on the NH. To further investigate the importance of interactive chemistry for surface climate, we conducted a set of experiments using NCAR's Community Earth System Model (CESM1) with the Whole Atmosphere Community Climate Model (WACCM) as the atmosphere component. WACCM contains a fully interactive stratospheric chemistry module in its standard configuration. It also allows for an alternative configuration, referred to as SC-WACCM, in which the chemistry (O3, NO, O, O2, CO2 and chemical and shortwave heating rates) is specified as a 2D field in the radiation code. A comparison of the interactive vs. the specified chemistry version enables us to evaluate the relative importance of interactive chemistry by systematically inhibiting the feedbacks between chemistry and dynamics. To diminish the effect of temporal interpolation when prescribing ozone, we use daily resolved zonal mean ozone fields for the specified chemistry run. Here, we investigate the differences in stratosphere-troposphere coupling between the interactive and specified chemistry simulations for the mainly chemically driven SH as well as for the mainly dynamically driven NH. We will especially consider years that are characterized by extremely low stratospheric ozone on the one hand and by large dynamical disturbances, i.e. Sudden Stratospheric Warmings, on the other hand.

Systematic Conservation Planning in the Face of Climate Change: Bet-Hedging on the Columbia Plateau

PubMed Central

Schloss, Carrie A.; Lawler, Joshua J.; Larson, Eric R.; Papendick, Hilary L.; Case, Michael J.; Evans, Daniel M.; DeLap, Jack H.; Langdon, Jesse G. R.; Hall, Sonia A.; McRae, Brad H.

2011-01-01

Systematic conservation planning efforts typically focus on protecting current patterns of biodiversity. Climate change is poised to shift species distributions, reshuffle communities, and alter ecosystem functioning. In such a dynamic environment, lands selected to protect today's biodiversity may fail to do so in the future. One proposed approach to designing reserve networks that are robust to climate change involves protecting the diversity of abiotic conditions that in part determine species distributions and ecological processes. A set of abiotically diverse areas will likely support a diversity of ecological systems both today and into the future, although those two sets of systems might be dramatically different. Here, we demonstrate a conservation planning approach based on representing unique combinations of abiotic factors. We prioritize sites that represent the diversity of soils, topographies, and current climates of the Columbia Plateau. We then compare these sites to sites prioritized to protect current biodiversity. This comparison highlights places that are important for protecting both today's biodiversity and the diversity of abiotic factors that will likely determine biodiversity patterns in the future. It also highlights places where a reserve network designed solely to protect today's biodiversity would fail to capture the diversity of abiotic conditions and where such a network could be augmented to be more robust to climate-change impacts. PMID:22174897

Climate change streamflow scenarios designed for critical period water resources planning studies

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Snover, A. K.; Lettenmaier, D. P.

2003-04-01

Long-range water planning in the United States is usually conducted by individual water management agencies using a critical period planning exercise based on a particular period of the observed streamflow record and a suite of internally-developed simulation tools representing the water system. In the context of planning for climate change, such an approach is flawed in that it assumes that the future climate will be like the historic record. Although more sophisticated planning methods will probably be required as time goes on, a short term strategy for incorporating climate uncertainty into long-range water planning as soon as possible is to create alternate inputs to existing planning methods that account for climate uncertainty as it affects both supply and demand. We describe a straight-forward technique for constructing streamflow scenarios based on the historic record that include the broad-based effects of changed regional climate simulated by several global climate models (GCMs). The streamflow scenarios are based on hydrologic simulations driven by historic climate data perturbed according to regional climate signals from four GCMs using the simple "delta" method. Further data processing then removes systematic hydrologic model bias using a quantile-based bias correction scheme, and lastly, the effects of random errors in the raw hydrologic simulations are removed. These techniques produce streamflow scenarios that are consistent in time and space with the historic streamflow record while incorporating fundamental changes in temperature and precipitation from the GCM scenarios. Planning model simulations based on these climate change streamflow scenarios can therefore be compared directly to planning model simulations based on the historic record of streamflows to help planners understand the potential impacts of climate uncertainty. The methods are currently being tested and refined in two large-scale planning exercises currently being conducted in the Pacific Northwest (PNW) region of the US, and the resulting streamflow scenarios will be made freely available on the internet for a large number of sites in the PNW to help defray the costs of including climate change information in other studies.

Impacts of droughts and extreme-temperature events on gross primary production and ecosystem respiration: a systematic assessment across ecosystems and climate zones

USDA-ARS?s Scientific Manuscript database

Extreme climatic events, such as droughts and heat stress induce anomalies in ecosystem-atmosphere CO2 fluxes, such as gross primary production (GPP) and ecosystem respiration (Reco), and, hence, can change the net ecosystem carbon balance. However, despite our increasing understanding of the underl...

Internal Communication and Job Satisfaction Revisited: The Impact of Organizational Trust and Influence on Commercial Bank Supervisors.

ERIC Educational Resources Information Center

Pincus, J. David; And Others

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,…

Soil Moisture-Atmosphere Feedbacks on Atmospheric Tracers: The Effects of Soil Moisture on Precipitation and Near-Surface Chemistry

NASA Astrophysics Data System (ADS)

Tawfik, Ahmed B.

The atmospheric component is described by rapid fluctuations in typical state variables, such as temperature and water vapor, on timescales of hours to days and the land component evolves on daily to yearly timescales. This dissertation examines the connection between soil moisture and atmospheric tracers under varying degrees of soil moisture-atmosphere coupling. Land-atmosphere coupling is defined over the United States using a regional climate model. A newly examined soil moisture-precipitation feedback is identified for winter months extending the previous summer feedback to colder temperature climates. This feedback is driven by the freezing and thawing of soil moisture, leading to coupled land-atmosphere conditions near the freezing line. Soil moisture can also affect the composition of the troposphere through modifying biogenic emissions of isoprene (C5H8). A novel first-order Taylor series decomposition indicates that isoprene emissions are jointly driven by temperature and soil moisture in models. These compounds are important precursors for ozone formation, an air pollutant and a short-lived forcing agent for climate. A mechanistic description of commonly observed relationships between ground-level ozone and meteorology is presented using the concept of soil moisture-temperature coupling regimes. The extent of surface drying was found to be a better predictor of ozone concentrations than temperature or humidity for the Eastern U.S. This relationship is evaluated in a coupled regional chemistry-climate model under several land-atmosphere coupling and isoprene emissions cases. The coupled chemistry-climate model can reproduce the observed soil moisture-temperature coupling pattern, yet modeled ozone is insensitive to changes in meteorology due to the balance between isoprene and the primary atmospheric oxidant, the hydroxyl radical (OH). Overall, this work highlights the importance of soil moisture-atmosphere coupling for previously neglected cold climate regimes, controlling isoprene emissions variability, and providing a processed-based description of observed ozone-meteorology relationships. From the perspective of ozone air quality, the lack of sensitivity of ozone to meteorology suggests a systematic deficiency in chemistry models in high isoprene emission regions. This shortcoming must be addressed to better estimate tropospheric ozone radiative forcing and to understanding how ozone air quality may respond to future warming.

Understanding the Role of the Saharan Heat Low in Modifying Atmospheric Dust Distributions - Observations From Two Research Aircraft Flying Simultaneously Over Western Africa

NASA Astrophysics Data System (ADS)

Engelstaedter, S.; Washington, R.; Allen, C.; Flamant, C.; Chaboureau, J.-P.; Kocha, C.; Lavaysse, C.

2012-04-01

The near-surface low pressure system that develops over western Africa in Boreal summer (know as the Saharan Heat Low) is thought to have a significant influence on regional and global climate due to its links with the Monsoon, the Northern Atlantic and the Mediterranean climate system. The SHL is associated with the deepest atmospheric boundary layer on the planet and is co-located with the highest dust loadings in the world. The processes that link the heat low and dust distribution are only poorly understood. Improving the representation of the heat low and the processes that control the emission and atmospheric distribution of dust in climate and NWP models is crucial if we are to reduce known systematic errors in climate predictions and weather forecasts. In collaboration with European partners, the UK-based consortium project "Fennec - The Saharan Climate System" aims at improving our understanding of this complex climate system by integrating for the first time coordinated ground and aircraft observations from the central Sahara, newly developed satellite products, and the application of regional and global models. On 22 June 2011, two research aircraft operating out of Fuerteventura (Spain) surveyed the Saharan Heat Low centred over Mauritania-Mali border. The aircraft flew simultaneously in the morning and in the afternoon on two different tracks thereby sampling each track four times on that day. Both aircraft were equipped with a downward looking LIDAR for aerosol detection. In total, 51 sondes were dropped during the flights making this the most comprehensive dataset to study the spatio-temporal diurnal evolution of the heat low including the interactions between the atmospheric boundary layer and dust distributions. Combining LIDAR observations, satellite imagery and back-trajectory modelling we show that an aged dust layer was present in the heat low region resulting from previous day's dust activity associated with a south-moving density current from the Atlas mountains and westward-moving Haboob fronts originating along the Algeria-Mali border. We show how the dust is distributed within the atmosphere and how it is modified during the course of the day by various processes including the development of the atmospheric boundary layer and associated dry convection as well as the inflow of moisture-rich monsoon air from the south.

Recent advances in research on climate and human conflict

NASA Astrophysics Data System (ADS)

Hsiang, S. M.

2014-12-01

A rapidly growing body of empirical, quantitative research examines whether rates of human conflict can be systematically altered by climatic changes. We discuss recent advances in this field, including Bayesian meta-analyses of the effect of temperature and rainfall on current and future large-scale conflicts, the impact of climate variables on gang violence and suicides in Mexico, and probabilistic projections of personal violence and property crime in the United States under RCP scenarios. Criticisms of this research field will also be explained and addressed.

Climate and Edaphic Controls on Humid Tropical Forest Tree Height

NASA Astrophysics Data System (ADS)

Yang, Y.; Saatchi, S. S.; Xu, L.

2014-12-01

Uncertainty in the magnitude and spatial variations of forest carbon density in tropical regions is due to under sampling of forest structure from inventory plots and the lack of regional allometry to estimate the carbon density from structure. Here we quantify the variation of tropical forest structure by using more than 2.5 million measurements of canopy height from systematic sampling of Geoscience Laser Altimeter System (GLAS) satellite observations between 2004 to 2008 and examine the climate and edaphic variables influencing the variations. We used top canopy height of GLAS footprints (~ 0.25 ha) to grid the statistical mean and 90 percentile of samples at 0.5 degrees to capture the regional variability of large trees in tropics. GLAS heights were also aggregated based on a stratification of tropical regions using soil, elevation, and forest types. Both approaches provided consistent patterns of statistically dominant large trees and the least heterogeneity, both as strong drivers of distribution of high biomass forests. Statistical models accounting for spatial autocorrelation suggest that climate, soil and spatial features together can explain more than 60% of the variations in observed tree height information, while climate-only variables explains about one third of the first-order changes in tree height. Soil basics, including physical compositions such as clay and sand contents, chemical properties such as PH values and cation-exchange capacity, as well as biological variables such as organic matters, all present independent but statistically significant relationships to tree height variations. The results confirm other landscape and regional studies that soil fertility, geology and climate may jointly control a majority of the regional variations of forest structure in pan-tropics and influencing both biomass stocks and dynamics. Consequently, other factors such as biotic and disturbance regimes, not included in this study, may have less influence on regional variations but strongly mediate landscape and small-scale forest structure and dynamics.

Climate Change and Algal Blooms =

NASA Astrophysics Data System (ADS)

Lin, Shengpan

Algal blooms are new emerging hazards that have had important social impacts in recent years. However, it was not very clear whether future climate change causing warming waters and stronger storm events would exacerbate the algal bloom problem. The goal of this dissertation was to evaluate the sensitivity of algal biomass to climate change in the continental United States. Long-term large-scale observations of algal biomass in inland lakes are challenging, but are necessary to relate climate change to algal blooms. To get observations at this scale, this dissertation applied machine-learning algorithms including boosted regression trees (BRT) in remote sensing of chlorophyll-a with Landsat TM/ETM+. The results show that the BRT algorithm improved model accuracy by 15%, compared to traditional linear regression. The remote sensing model explained 46% of the total variance of the ground-measured chlorophyll- a in the first National Lake Assessment conducted by the US Environmental Protection Agency. That accuracy was ecologically meaningful to study climate change impacts on algal blooms. Moreover, the BRT algorithm for chlorophyll- a would not have systematic bias that is introduced by sediments and colored dissolved organic matter, both of which might change concurrently with climate change and algal blooms. This dissertation shows that the existing atmospheric corrections for Landsat TM/ETM+ imagery might not be good enough to improve the remote sensing of chlorophyll-a in inland lakes. After deriving long-term algal biomass estimates from Landsat TM/ETM+, time series analysis was used to study the relations of climate change and algal biomass in four Missouri reservoirs. The results show that neither temperature nor precipitation was the only factor that controlled temporal variation of algal biomass. Different reservoirs, even different zones within the same reservoir, responded differently to temperature and precipitation changes. These findings were further tested in 1157 lakes across the continental United States. The results show that mean annual algal biomass generally increased with annual temperature. Greater increase was found in lakes with more nutrients. Mean annual algal biomass generally decreased with annual total precipitation. In both the "low" and the "high" greenhouse-gas emission scenarios, mean annual algal biomass in lakes generally increased with climate change, and greater increases are predicted from the high emission scenario.

Quantifying climate feedbacks in polar regions.

PubMed

Goosse, Hugues; Kay, Jennifer E; Armour, Kyle C; Bodas-Salcedo, Alejandro; Chepfer, Helene; Docquier, David; Jonko, Alexandra; Kushner, Paul J; Lecomte, Olivier; Massonnet, François; Park, Hyo-Seok; Pithan, Felix; Svensson, Gunilla; Vancoppenolle, Martin

2018-05-15

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range of feedbacks, offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.

Discriminating low frequency components from long range persistent fluctuations in daily atmospheric temperature variability

NASA Astrophysics Data System (ADS)

Lanfredi, M.; Simoniello, T.; Cuomo, V.; Macchiato, M.

2009-02-01

This study originated from recent results reported in literature, which support the existence of long-range (power-law) persistence in atmospheric temperature fluctuations on monthly and inter-annual scales. We investigated the results of Detrended Fluctuation Analysis (DFA) carried out on twenty-two historical daily time series recorded in Europe in order to evaluate the reliability of such findings in depth. More detailed inspections emphasized systematic deviations from power-law and high statistical confidence for functional form misspecification. Rigorous analyses did not support scale-free correlation as an operative concept for Climate modelling, as instead suggested in literature. In order to understand the physical implications of our results better, we designed a bivariate Markov process, parameterised on the basis of the atmospheric observational data by introducing a slow dummy variable. The time series generated by this model, analysed both in time and frequency domains, tallied with the real ones very well. They accounted for both the deceptive scaling found in literature and the correlation details enhanced by our analysis. Our results seem to evidence the presence of slow fluctuations from another climatic sub-system such as ocean, which inflates temperature variance up to several months. They advise more precise re-analyses of temperature time series before suggesting dynamical paradigms useful for Climate modelling and for the assessment of Climate Change.

Discriminating low frequency components from long range persistent fluctuations in daily atmospheric temperature variability

NASA Astrophysics Data System (ADS)

Lanfredi, M.; Simoniello, T.; Cuomo, V.; Macchiato, M.

2009-07-01

This study originated from recent results reported in literature, which support the existence of long-range (power-law) persistence in atmospheric temperature fluctuations on monthly and inter-annual scales. We investigated the results of Detrended Fluctuation Analysis (DFA) carried out on twenty-two historical daily time series recorded in Europe in order to evaluate the reliability of such findings in depth. More detailed inspections emphasized systematic deviations from power-law and high statistical confidence for functional form misspecification. Rigorous analyses did not support scale-free correlation as an operative concept for Climate modelling, as instead suggested in literature. In order to understand the physical implications of our results better, we designed a bivariate Markov process, parameterised on the basis of the atmospheric observational data by introducing a slow dummy variable. The time series generated by this model, analysed both in time and frequency domains, tallied with the real ones very well. They accounted for both the deceptive scaling found in literature and the correlation details enhanced by our analysis. Our results seem to evidence the presence of slow fluctuations from another climatic sub-system such as ocean, which inflates temperature variance up to several months. They advise more precise re-analyses of temperature time series before suggesting dynamical paradigms useful for Climate modelling and for the assessment of Climate Change.

Performance of the WRF model to simulate the seasonal and interannual variability of hydrometeorological variables in East Africa: a case study for the Tana River basin in Kenya

NASA Astrophysics Data System (ADS)

Kerandi, Noah Misati; Laux, Patrick; Arnault, Joel; Kunstmann, Harald

2017-10-01

This study investigates the ability of the regional climate model Weather Research and Forecasting (WRF) in simulating the seasonal and interannual variability of hydrometeorological variables in the Tana River basin (TRB) in Kenya, East Africa. The impact of two different land use classifications, i.e., the Moderate Resolution Imaging Spectroradiometer (MODIS) and the US Geological Survey (USGS) at two horizontal resolutions (50 and 25 km) is investigated. Simulated precipitation and temperature for the period 2011-2014 are compared with Tropical Rainfall Measuring Mission (TRMM), Climate Research Unit (CRU), and station data. The ability of Tropical Rainfall Measuring Mission (TRMM) and Climate Research Unit (CRU) data in reproducing in situ observation in the TRB is analyzed. All considered WRF simulations capture well the annual as well as the interannual and spatial distribution of precipitation in the TRB according to station data and the TRMM estimates. Our results demonstrate that the increase of horizontal resolution from 50 to 25 km, together with the use of the MODIS land use classification, significantly improves the precipitation results. In the case of temperature, spatial patterns and seasonal cycle are well reproduced, although there is a systematic cold bias with respect to both station and CRU data. Our results contribute to the identification of suitable and regionally adapted regional climate models (RCMs) for East Africa.

Organizational stressors associated with job stress and burnout in correctional officers: a systematic review.

PubMed

Finney, Caitlin; Stergiopoulos, Erene; Hensel, Jennifer; Bonato, Sarah; Dewa, Carolyn S

2013-01-29

In adult correctional facilities, correctional officers (COs) are responsible for the safety and security of the facility in addition to aiding in offender rehabilitation and preventing recidivism. COs experience higher rates of job stress and burnout that stem from organizational stressors, leading to negative outcomes for not only the CO but the organization as well. Effective interventions could aim at targeting organizational stressors in order to reduce these negative outcomes as well as COs' job stress and burnout. This paper fills a gap in the organizational stress literature among COs by systematically reviewing the relationship between organizational stressors and CO stress and burnout in adult correctional facilities. In doing so, the present review identifies areas that organizational interventions can target in order to reduce CO job stress and burnout. A systematic search of the literature was conducted using Medline, PsycINFO, Criminal Justice Abstracts, and Sociological Abstracts. All retrieved articles were independently screened based on criteria developed a priori. All included articles underwent quality assessment. Organizational stressors were categorized according to Cooper and Marshall's (1976) model of job stress. The systematic review yielded 8 studies that met all inclusion and quality assessment criteria. The five categories of organizational stressors among correctional officers are: stressors intrinsic to the job, role in the organization, rewards at work, supervisory relationships at work and the organizational structure and climate. The organizational structure and climate was demonstrated to have the most consistent relationship with CO job stress and burnout. The results of this review indicate that the organizational structure and climate of correctional institutions has the most consistent relationship with COs' job stress and burnout. Limitations of the studies reviewed include the cross-sectional design and the use of varying measures for organizational stressors. The results of this review indicate that interventions should aim to improve the organizational structure and climate of the correctional facility by improving communication between management and COs.

Organizational stressors associated with job stress and burnout in correctional officers: a systematic review

PubMed Central

2013-01-01

Background In adult correctional facilities, correctional officers (COs) are responsible for the safety and security of the facility in addition to aiding in offender rehabilitation and preventing recidivism. COs experience higher rates of job stress and burnout that stem from organizational stressors, leading to negative outcomes for not only the CO but the organization as well. Effective interventions could aim at targeting organizational stressors in order to reduce these negative outcomes as well as COs’ job stress and burnout. This paper fills a gap in the organizational stress literature among COs by systematically reviewing the relationship between organizational stressors and CO stress and burnout in adult correctional facilities. In doing so, the present review identifies areas that organizational interventions can target in order to reduce CO job stress and burnout. Methods A systematic search of the literature was conducted using Medline, PsycINFO, Criminal Justice Abstracts, and Sociological Abstracts. All retrieved articles were independently screened based on criteria developed a priori. All included articles underwent quality assessment. Organizational stressors were categorized according to Cooper and Marshall’s (1976) model of job stress. Results The systematic review yielded 8 studies that met all inclusion and quality assessment criteria. The five categories of organizational stressors among correctional officers are: stressors intrinsic to the job, role in the organization, rewards at work, supervisory relationships at work and the organizational structure and climate. The organizational structure and climate was demonstrated to have the most consistent relationship with CO job stress and burnout. Conclusions The results of this review indicate that the organizational structure and climate of correctional institutions has the most consistent relationship with COs’ job stress and burnout. Limitations of the studies reviewed include the cross-sectional design and the use of varying measures for organizational stressors. The results of this review indicate that interventions should aim to improve the organizational structure and climate of the correctional facility by improving communication between management and COs. PMID:23356379

Simulation of the West African Monsoon using the MIT Regional Climate Model

NASA Astrophysics Data System (ADS)

Im, Eun-Soon; Gianotti, Rebecca L.; Eltahir, Elfatih A. B.

2013-04-01

We test the performance of the MIT Regional Climate Model (MRCM) in simulating the West African Monsoon. MRCM introduces several improvements over Regional Climate Model version 3 (RegCM3) including coupling of Integrated Biosphere Simulator (IBIS) land surface scheme, a new albedo assignment method, a new convective cloud and rainfall auto-conversion scheme, and a modified boundary layer height and cloud scheme. Using MRCM, we carried out a series of experiments implementing two different land surface schemes (IBIS and BATS) and three convection schemes (Grell with the Fritsch-Chappell closure, standard Emanuel, and modified Emanuel that includes the new convective cloud scheme). Our analysis primarily focused on comparing the precipitation characteristics, surface energy balance and large scale circulations against various observations. We document a significant sensitivity of the West African monsoon simulation to the choices of the land surface and convection schemes. In spite of several deficiencies, the simulation with the combination of IBIS and modified Emanuel schemes shows the best performance reflected in a marked improvement of precipitation in terms of spatial distribution and monsoon features. In particular, the coupling of IBIS leads to representations of the surface energy balance and partitioning that are consistent with observations. Therefore, the major components of the surface energy budget (including radiation fluxes) in the IBIS simulations are in better agreement with observation than those from our BATS simulation, or from previous similar studies (e.g Steiner et al., 2009), both qualitatively and quantitatively. The IBIS simulations also reasonably reproduce the dynamical structure of vertically stratified behavior of the atmospheric circulation with three major components: westerly monsoon flow, African Easterly Jet (AEJ), and Tropical Easterly Jet (TEJ). In addition, since the modified Emanuel scheme tends to reduce the precipitation amount, it improves the precipitation over regions suffering from systematic wet bias.

Ice-shelf collapse from subsurface warming as a trigger for Heinrich events

PubMed Central

Marcott, Shaun A.; Clark, Peter U.; Padman, Laurie; Klinkhammer, Gary P.; Springer, Scott R.; Liu, Zhengyu; Otto-Bliesner, Bette L.; Carlson, Anders E.; Ungerer, Andy; Padman, June; He, Feng; Cheng, Jun; Schmittner, Andreas

2011-01-01

Episodic iceberg-discharge events from the Hudson Strait Ice Stream (HSIS) of the Laurentide Ice Sheet, referred to as Heinrich events, are commonly attributed to internal ice-sheet instabilities, but their systematic occurrence at the culmination of a large reduction in the Atlantic meridional overturning circulation (AMOC) indicates a climate control. We report Mg/Ca data on benthic foraminifera from an intermediate-depth site in the northwest Atlantic and results from a climate-model simulation that reveal basin-wide subsurface warming at the same time as large reductions in the AMOC, with temperature increasing by approximately 2 °C over a 1–2 kyr interval prior to a Heinrich event. In simulations with an ocean model coupled to a thermodynamically active ice shelf, the increase in subsurface temperature increases basal melt rate under an ice shelf fronting the HSIS by a factor of approximately 6. By analogy with recent observations in Antarctica, the resulting ice-shelf loss and attendant HSIS acceleration would produce a Heinrich event. PMID:21808034

United States Temperature and Precipitation Extremes: Phenomenology, Large-Scale Organization, Physical Mechanisms and Model Representation

NASA Astrophysics Data System (ADS)

Black, R. X.

2017-12-01

We summarize results from a project focusing on regional temperature and precipitation extremes over the continental United States. Our project introduces a new framework for evaluating these extremes emphasizing their (a) large-scale organization, (b) underlying physical sources (including remote-excitation and scale-interaction) and (c) representation in climate models. Results to be reported include the synoptic-dynamic behavior, seasonality and secular variability of cold waves, dry spells and heavy rainfall events in the observational record. We also study how the characteristics of such extremes are systematically related to Northern Hemisphere planetary wave structures and thus planetary- and hemispheric-scale forcing (e.g., those associated with major El Nino events and Arctic sea ice change). The underlying physics of event onset are diagnostically quantified for different categories of events. Finally, the representation of these extremes in historical coupled climate model simulations is studied and the origins of model biases are traced using new metrics designed to assess the large-scale atmospheric forcing of local extremes.

Climate change and potato cropping in the Peruvian Altiplano

NASA Astrophysics Data System (ADS)

Sanabria, J.; Lhomme, J. P.

2013-05-01

The potential impacts of climate change on potatoes cropping in the Peruvian highlands (Altiplano) is assessed using climate projections for 2071-2100, obtained from the HadRM3P regional atmospheric model of the Hadley Centre. The atmospheric model is run under two different special report on emission scenarios: high CO2 concentration (A2) and moderate CO2 concentration (B2) for four locations situated in the surroundings of Lake Titicaca. The two main varieties of potato cultivated in the area are studied: the Andean potato ( Solanum tuberosum) and the bitter potato ( Solanum juzepczukii). A simple process-oriented model is used to quantify the climatic impacts on crops cycles and yields by combining the effects of temperature on phenology, of radiation and CO2 on maximum yield and of water balance on yield deficit. In future climates, air temperature systematically increases, precipitation tends to increase at the beginning of the rainy season and slightly decreases during the rest of the season. The direct effects of these climatic changes are earlier planting dates, less planting failures and shorter crop cycles in all the four locations and for both scenarios. Consequently, the harvesting dates occur systematically earlier: roughly in January for the Andean potato instead of March in the current situation and in February for the bitter potato instead of April. Overall, yield deficits will be higher under climate change than in the current climate. There will be a strong negative impact on yields for S. tuberosum (stronger under A2 scenario than under B2); the impact on S. juzepczukii yields, however, appears to be relatively mixed and not so negative.

Impacts of climatic variation on trout: A global synthesis and path forward

USGS Publications Warehouse

Kovach, Ryan; Muhlfeld, Clint C.; Al-Chokhachy, Robert K.; Dunham, Jason B.; Letcher, Benjamin; Kershner, Jeffrey L.

2016-01-01

Despite increasing concern that climate change may negatively impact trout—a globally distributed group of fish with major economic, ecological, and cultural value—a synthetic assessment of empirical data quantifying relationships between climatic variation and trout ecology does not exist. We conducted a systematic review to describe how temporal variation in temperature and streamflow influences trout ecology in freshwater ecosystems. Few studies (n = 42) have quantified relationships between temperature or streamflow and trout demography, growth, or phenology, and nearly all estimates (96 %) were for Salvelinus fontinalis and Salmo trutta. Only seven studies used temporal data to quantify climate-driven changes in trout ecology. Results from these studies were beset with limitations that prohibited quantitatively rigorous meta-analysis, a concerning inadequacy given major investment in trout conservation and management worldwide. Nevertheless, consistent patterns emerged from our synthesis, particularly a positive effect of summer streamflow on trout demography and growth; 64 % of estimates were positive and significant across studies, age classes, species, and locations, highlighting that climate-induced changes in hydrology may have numerous consequences for trout. To a lesser degree, summer and fall temperatures were negatively related to population demography (51 and 53 % of estimates, respectively), but temperature was rarely related to growth. To address limitations and uncertainties, we recommend: (1) systematically improving data collection, description, and sharing; (2) appropriately integrating climate impacts with other intrinsic and extrinsic drivers over the entire lifecycle; (3) describing indirect consequences of climate change; and (4) acknowledging and describing intrinsic resiliency.

Broken Robustness Analysis: How to make proper climate change conclusions in contradictory multimodal measurement contexts.

NASA Astrophysics Data System (ADS)

Keyser, V.

2015-12-01

Philosophers of science discuss how multiple modes of measurement can generate evidence for the existence and character of a phenomenon (Horwich 1982; Hacking 1983; Franklin and Howson 1984; Collins 1985; Sober 1989; Trout 1993; Culp 1995; Keeley 2002; Staley 2004; Weber 2005; Keyser 2012). But how can this work systematically in climate change measurement? Additionally, what conclusions can scientists and policy-makers draw when different modes of measurement fail to be robust by producing contradictory results? First, I present a new technical account of robust measurement (RAMP) that focuses on the physical independence of measurement processes. I detail how physically independent measurement processes "check each other's results." (This account is in contrast to philosophical accounts of robustness analysis that focus on independent model assumptions or independent measurement products or results.) Second, I present a puzzle about contradictory and divergent climate change measures, which has consistently re-emerged in climate measurement. This discussion will focus on land, drilling, troposphere, and computer simulation measures. Third, to systematically solve this climate measurement puzzle, I use RAMP in the context of drought measurement in order to generate a classification of measurement processes. Here, I discuss how multimodal precipitation measures—e.g., measures of precipitation deficit like the Standard Precipitation Index vs. air humidity measures like the Standardized Relative Humidity Index--can help with the classification scheme of climate change measurement processes. Finally, I discuss how this classification of measures can help scientists and policy-makers draw effective conclusions in contradictory multimodal climate change measurement contexts.

Climate Variability and the Occurrence of Human Puumala Hantavirus Infections in Europe: A Systematic Review.

PubMed

Roda Gracia, J; Schumann, B; Seidler, A

2015-09-01

Hantaviruses are distributed worldwide and are transmitted by rodents. In Europe, the infection usually manifests as a mild form of haemorrhagic fever with renal syndrome (HFRS) known as nephropathia epidemica (NE), which is triggered by the virus species Puumala. Its host is the bank vole (Myodes glareolus). In the context of climate change, interest in the role of climatic factors for the disease has increased. A systematic review was conducted to investigate the association between climate variability and the occurrence of human Puumala hantavirus infections in Europe. We performed a literature search in the databases MEDLINE, EMBASE and Web of Science. Studies that investigated Puumala virus infection and climatic factors in any European country with a minimum collection period of 2 years were included. The selection of abstracts and the evaluation of included studies were performed by two independent reviewers. A total of 434 titles were identified in the databases, of which nine studies fulfilled the inclusion criteria. The majority of studies were conducted in central Europe (Belgium, France and Germany), while only two came from the north (Sweden) and one from the south (Bosnia). Strong evidence was found for a positive association between temperature and NE incidence in central Europe, while the evidence for northern Europe so far appears insufficient. Results regarding precipitation were contradictory. Overall, the complex relationships between climate and hantavirus infections need further exploration to identify specific health risks and initiate appropriate intervention measures in the context of climate change. © 2014 Blackwell Verlag GmbH.

Global biogeochemical cycles: Studies of interaction and change, some views on the strategy of approach

NASA Technical Reports Server (NTRS)

Bolin, B.

1984-01-01

The global biosphere is an exceedingly complex system. To gain an understanding of its structure and dynamic features, it is necessary to increase knowledge about the detailed processes, but also to develop models of how global interactions take place. Attempts to analyze the detailed physical, chemical and biological processes need, in this context, to be guided by an advancement of understanding of the latter. It is necessary to develop a strategy of data gathering that serves both these purposes simultaneously. climate research during the last decade may serve as a useful example of how to approach this difficult problem in a systematic way. Large programs for data collection may easily become rigid and costly. While realizing the necessity of a systematic and long lasting effort of observing the atmosphere, the oceans, land and life on Earth, such a program must remain flexible enough to permit the modifications and even sometimes improvisations that are necessary to maintain a viable program.

Systematic review of current efforts to quantify the impacts of climate change on undernutrition.

PubMed

Phalkey, Revati K; Aranda-Jan, Clara; Marx, Sabrina; Höfle, Bernhard; Sauerborn, Rainer

2015-08-18

Malnutrition is a challenge to the health and productivity of populations and is viewed as one of the five largest adverse health impacts of climate change. Nonetheless, systematic evidence quantifying these impacts is currently limited. Our aim was to assess the scientific evidence base for the impact of climate change on childhood undernutrition (particularly stunting) in subsistence farmers in low- and middle-income countries. A systematic review was conducted to identify peer-reviewed and gray full-text documents in English with no limits for year of publication or study design. Fifteen manuscripts were reviewed. Few studies use primary data to investigate the proportion of stunting that can be attributed to climate/weather variability. Although scattered and limited, current evidence suggests a significant but variable link between weather variables, e.g., rainfall, extreme weather events (floods/droughts), seasonality, and temperature, and childhood stunting at the household level (12 of 15 studies, 80%). In addition, we note that agricultural, socioeconomic, and demographic factors at the household and individual levels also play substantial roles in mediating the nutritional impacts. Comparable interdisciplinary studies based on primary data at a household level are urgently required to guide effective adaptation, particularly for rural subsistence farmers. Systemization of data collection at the global level is indispensable and urgent. We need to assimilate data from long-term, high-quality agricultural, environmental, socioeconomic, health, and demographic surveillance systems and develop robust statistical methods to establish and validate causal links, quantify impacts, and make reliable predictions that can guide evidence-based health interventions in the future.

Systematic review of current efforts to quantify the impacts of climate change on undernutrition

PubMed Central

Phalkey, Revati K.; Aranda-Jan, Clara; Marx, Sabrina; Höfle, Bernhard; Sauerborn, Rainer

2015-01-01

Malnutrition is a challenge to the health and productivity of populations and is viewed as one of the five largest adverse health impacts of climate change. Nonetheless, systematic evidence quantifying these impacts is currently limited. Our aim was to assess the scientific evidence base for the impact of climate change on childhood undernutrition (particularly stunting) in subsistence farmers in low- and middle-income countries. A systematic review was conducted to identify peer-reviewed and gray full-text documents in English with no limits for year of publication or study design. Fifteen manuscripts were reviewed. Few studies use primary data to investigate the proportion of stunting that can be attributed to climate/weather variability. Although scattered and limited, current evidence suggests a significant but variable link between weather variables, e.g., rainfall, extreme weather events (floods/droughts), seasonality, and temperature, and childhood stunting at the household level (12 of 15 studies, 80%). In addition, we note that agricultural, socioeconomic, and demographic factors at the household and individual levels also play substantial roles in mediating the nutritional impacts. Comparable interdisciplinary studies based on primary data at a household level are urgently required to guide effective adaptation, particularly for rural subsistence farmers. Systemization of data collection at the global level is indispensable and urgent. We need to assimilate data from long-term, high-quality agricultural, environmental, socioeconomic, health, and demographic surveillance systems and develop robust statistical methods to establish and validate causal links, quantify impacts, and make reliable predictions that can guide evidence-based health interventions in the future. PMID:26216952

Decomposing climate-induced temperature and water effects on the expansion and operation of the US electricity system

NASA Astrophysics Data System (ADS)

Sun, Y.; Eurek, K.; Macknick, J.; Steinberg, D. C.; Averyt, K.; Badger, A.; Livneh, B.

2017-12-01

Climate change has the potential to affect the supply and demands of the U.S. power sector. Rising air temperatures can affect the seasonal and total demand for electricity, alter the thermal efficiency of power plants, and lower the maximum capacity of electric transmission lines. Changes in hydrology can affect seasonal and total availability of water used for power plant operations. Prior studies have examined some climate impacts on the electricity sector, but there has been no systematic study quantifying and comparing the importance of these climate-induced effects in isolation and in combination. Here, we perform a systematic assessment using the Regional Energy Deployment System (ReEDS) electricity sector model in combination with downscaled climate results from four models in the CMIP5 archive that provide contrasting temperature and precipitation trends for key regions in the U.S. The ReEDS model captures dynamic climate and hydrological resource data .when choosing the cost optimal mix of generation resources necessary to balance supply and demand for electricity. We examine how different climate-induced changes in air temperature and water availability, considered in isolation and in combination, may affect energy and economic outcomes at a regional and national level from the present through 2050. Results indicate that temperature-induced impacts on electricity consumption show consistent trends nationwide across all climate scenarios. Hydrological impacts and variability differ by model and tend to have a minor effect on national electricity trends, but can be important determinants regionally. Taken together, this suggests that isolated climate change impacts on the electricity system depend on the geographic scale of interest - the effect of rising temperatures on demand, which is qualitatively robust to the choice of climate model, largely determines impacts on generation, capacity and cost at the national level, whereas other impact pathways may dominate at regional level.

Actual evapotranspiration for a reference crop within measured and future changing climate periods in the Mediterranean region

NASA Astrophysics Data System (ADS)

Katerji, Nader; Rana, Gianfranco; Ferrara, Rossana Monica

2017-08-01

The study compares two formulas for calculating the daily evapotranspiration ET0 for a reference crop. The first formula was proposed by Allen et al. (AL), while the second one was proposed by Katerji and Perrier with the addition of the carbon dioxide (CO2) effect on evapotranspiration (KP). The study analyses the impact of the calculation by the two formulas on the irrigation requirement (IR). Both formulas are based on the Penman-Monteith equation but adopt different approaches for parameterising the canopy resistance r c . In the AL formula, r c is assumed constant and not sensitive to climate change, whereas in the KP formula, r c is first parameterised as a function of climatic variables, then ET0 is corrected for the air CO2 concentration. The two formulas were compared in two periods. The first period involves data from two sites in the Mediterranean region within a measured climate change period (1981-2006) when all the input climatic variables were measured. The second period (2070-2100) involves data from a future climate change period at one site when the input climatic variables were forecasted for two future climate scenarios (A2 and B2). The annual cumulated values of ET0 calculated by the AL formula are systematically lower than those determined by the KP formula. The differences between the ET0 estimation with the AL and KP formulas have a strong impact on the determination of the IR for the reference crop. In fact, for the two periods, the annual values of IR when ET0 is calculated by the AL formula are systematically lower than those calculated by the KP formula. For the actual measured climate change period, this reduction varied from 26 to 28 %, while for the future climate change period, it varied based on the scenario from 16 % (A2) to 20 % (B2).

Systematic Correlation Matrix Evaluation (SCoMaE) - a bottom-up, science-led approach to identifying indicators

NASA Astrophysics Data System (ADS)

Mengis, Nadine; Keller, David P.; Oschlies, Andreas

2018-01-01

This study introduces the Systematic Correlation Matrix Evaluation (SCoMaE) method, a bottom-up approach which combines expert judgment and statistical information to systematically select transparent, nonredundant indicators for a comprehensive assessment of the state of the Earth system. The methods consists of two basic steps: (1) the calculation of a correlation matrix among variables relevant for a given research question and (2) the systematic evaluation of the matrix, to identify clusters of variables with similar behavior and respective mutually independent indicators. Optional further analysis steps include (3) the interpretation of the identified clusters, enabling a learning effect from the selection of indicators, (4) testing the robustness of identified clusters with respect to changes in forcing or boundary conditions, (5) enabling a comparative assessment of varying scenarios by constructing and evaluating a common correlation matrix, and (6) the inclusion of expert judgment, for example, to prescribe indicators, to allow for considerations other than statistical consistency. The example application of the SCoMaE method to Earth system model output forced by different CO2 emission scenarios reveals the necessity of reevaluating indicators identified in a historical scenario simulation for an accurate assessment of an intermediate-high, as well as a business-as-usual, climate change scenario simulation. This necessity arises from changes in prevailing correlations in the Earth system under varying climate forcing. For a comparative assessment of the three climate change scenarios, we construct and evaluate a common correlation matrix, in which we identify robust correlations between variables across the three considered scenarios.

Adaptive and interactive climate futures: systematic review of ‘serious games’ for engagement and decision-making

NASA Astrophysics Data System (ADS)

Flood, Stephen; Cradock-Henry, Nicholas A.; Blackett, Paula; Edwards, Peter

2018-06-01

Climate change is already having adverse impacts on ecosystems, communities and economic activities through higher temperatures, prolonged droughts, and more frequent extremes. However, a gap remains between public understanding, scientific knowledge about climate change, and changes in behaviour to effect adaptation. ‘Serious games’—games used for purposes other than entertainment—are one way to reduce this adaptation deficit by enhancing opportunities for social learning and enabling positive action. Games can provide communities with the opportunity to interactively explore different climate futures, build capability and capacity for dealing with complex challenges, and socialise adaptation priorities with diverse publics. Using systematic review methods, this paper identifies, reviews, synthesises and assesses the literature on serious games for climate change adaptation. To determine where and how impact is achieved, we draw on an evaluation framework grounded in social learning, to assess which combinations of cognitive (knowledge and thinking), normative (norms and approaches) and relational (how people connect and network building) learning are achieved. Results show that factors influencing the overall success in influencing behaviour and catalysing learning for adaptation include generating high levels of inter- and intra- level trust between researchers, practitioners and community participants; strong debriefing and evaluation practices; and the use of experienced and knowledgeable facilitators. These results can help inform future game design, and research methodologies to develop robust ways for engaging with stakeholders and end users, and enhance learning effects for resilient climate futures.

Assessment of Global Annual Atmospheric Energy Balance from Satellite Observations

NASA Technical Reports Server (NTRS)

Lin, Bing; Stackhouse, Paul; Minnis, Patrick; Wielicki, Bruce A.; Hu, Yongxiang; Sun, Wenbo; Fan, Tai-Fang (Alice); Hinkelman, Laura

2008-01-01

Global atmospheric energy balance is one of the fundamental processes for the earth's climate system. This study uses currently available satellite data sets of radiative energy at the top of atmosphere (TOA) and surface and latent and sensible heat over oceans for the year 2000 to assess the global annual energy budget. Over land, surface radiation data are used to constrain assimilated results and to force the radiation, turbulent heat, and heat storage into balance due to a lack of observation-based turbulent heat flux estimations. Global annual means of the TOA net radiation obtained from both direct measurements and calculations are close to zero. The net radiative energy fluxes into the surface and the surface latent heat transported into the atmosphere are about 113 and 86 Watts per square meter, respectively. The estimated atmospheric and surface heat imbalances are about -8 9 Watts per square meter, values that are within the uncertainties of surface radiation and sea surface turbulent flux estimates and likely systematic biases in the analyzed observations. The potential significant additional absorption of solar radiation within the atmosphere suggested by previous studies does not appear to be required to balance the energy budget the spurious heat imbalances in the current data are much smaller (about half) than those obtained previously and debated at about a decade ago. Progress in surface radiation and oceanic turbulent heat flux estimations from satellite measurements significantly reduces the bias errors in the observed global energy budgets of the climate system.

Land surface phenology as a coarse-filter indicator of disturbance and climatic effects across the coast redwood range

Treesearch

Steven P. Norman; William W. Hargrove

2012-01-01

Satellite-based measurements provide a systematic measure of the seasonal fluctuations and general condition of forest vegetation, including that of the coast redwood region. Year-toyear variation in greenness may be caused by gradual disturbances, successional recovery or climatic variation, while within-year variation reflects disturbance events and the response of...

A systematic review of dynamics in climate risk and vulnerability assessments

NASA Astrophysics Data System (ADS)

Jurgilevich, Alexandra; Räsänen, Aleksi; Groundstroem, Fanny; Juhola, Sirkku

2017-01-01

Understanding climate risk is crucial for effective adaptation action, and a number of assessment methodologies have emerged. We argue that the dynamics of the individual components in climate risk and vulnerability assessments has received little attention. In order to highlight this, we systematically reviewed 42 sub-national climate risk and vulnerability assessments. We analysed the assessments using an analytical framework with which we evaluated (1) the conceptual approaches to vulnerability and exposure used, (2) if current or future risks were assessed, and (3) if and how changes over time (i.e. dynamics) were considered. Of the reviewed assessments, over half addressed future risks or vulnerability; and of these future-oriented studies, less than 1/3 considered both vulnerability and exposure dynamics. While the number of studies that include dynamics is growing, and while all studies included socio-economic aspects, often only biophysical dynamics was taken into account. We discuss the challenges of assessing socio-economic and spatial dynamics, particularly the poor availability of data and methods. We suggest that future-oriented studies assessing risk dynamics would benefit from larger stakeholder involvement, discussion of the assessment purpose, the use of multiple methods, inclusion of uncertainty/sensitivity analyses and pathway approaches.

Water isotope tracers of tropical hydroclimate in a warming world

NASA Astrophysics Data System (ADS)

Konecky, B. L.; Noone, D.; Nusbaumer, J. M.; Cobb, K. M.; Di Nezio, P. N.; Otto-Bliesner, B. L.

2016-12-01

The tropical water cycle is projected to undergo substantial changes under a warming climate, but direct meteorological observations to contextualize these changes are rare prior to the 20th century. Stable oxygen and hydrogen isotope ratios (δ18O, δD) of environmental waters preserved in geologic archives are increasingly being used to reconstruct terrestrial rainfall over many decades to millions of years. However, a rising number of new, modern-day observations and model simulations have challenged previous interpretations of these isotopic signatures. This presentation systematically evaluates the three main influences on the δ18O and δD of modern precipitation - rainfall amount, cloud type, and moisture transport - from terrestrial stations throughout the tropics, and uses this interpretive framework to understand past changes in terrestrial tropical rainfall. Results indicate that cloud type and moisture transport have a larger influence on modern δ18O and δD of tropical precipitation than previously believed, indicating that isotope records track changes in cloud characteristics and circulation that accompany warmer and cooler climate states. We use our framework to investigate isotopic records of the land-based tropical rain belt during the Last Glacial Maximum, the period of warming following the Little Ice Age, and the 21st century. Proxy and observational data are compared with water isotope-enabled simulations with the Community Earth System Model in order to discuss how global warming and cooling may influence tropical terrestrial hydroclimate.

Importance of ensembles in projecting regional climate trends

NASA Astrophysics Data System (ADS)

Arritt, Raymond; Daniel, Ariele; Groisman, Pavel

2016-04-01

We have performed an ensemble of simulations using RegCM4 to examine the ability to reproduce observed trends in precipitation intensity and to project future changes through the 21st century for the central United States. We created a matrix of simulations over the CORDEX North America domain for 1950-2099 by driving the regional model with two different global models (HadGEM2-ES and GFDL-ESM2M, both for RCP8.5), by performing simulations at both 50 km and 25 km grid spacing, and by using three different convective parameterizations. The result is a set of 12 simulations (two GCMs by two resolutions by three convective parameterizations) that can be used to systematically evaluate the influence of simulation design on predicted precipitation. The two global models were selected to bracket the range of climate sensitivity in the CMIP5 models: HadGEM2-ES has the highest ECS of the CMIP5 models, while GFDL-ESM2M has one of the lowestt. Our evaluation metrics differ from many other RCM studies in that we focus on the skill of the models in reproducing past trends rather than the mean climate state. Trends in frequency of extreme precipitation (defined as amounts exceeding 76.2 mm/day) for most simulations are similar to the observed trend but with notable variations depending on RegCM4 configuration and on the driving GCM. There are complex interactions among resolution, choice of convective parameterization, and the driving GCM that carry over into the future climate projections. We also note that biases in the current climate do not correspond to biases in trends. As an example of these points the Emanuel scheme is consistently "wet" (positive bias in precipitation) yet it produced the smallest precipitation increase of the three convective parameterizations when used in simulations driven by HadGEM2-ES. However, it produced the largest increase when driven by GFDL-ESM2M. These findings reiterate that ensembles using multiple RCM configurations and driving GCMs are essential for projecting regional climate change, even when a single RCM is used. This research was sponsored by the U.S. Department of Agriculture National Institute of Food and Agriculture.

Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

NASA Astrophysics Data System (ADS)

Kang, Suchul; Im, Eun-Soon; Eltahir, Elfatih A. B.

2018-03-01

In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

Climate Stability: Pathway to understand abrupt glacial climate shifts

NASA Astrophysics Data System (ADS)

Zhang, X.; Knorr, G.; Barker, S.; Lohmann, G.

2017-12-01

Glacial climate is marked by abrupt, millennial-scale climate changes known as Dansgaard-Oeschger (DO) cycles that have been linked to variations in the Atlantic meridional overturning circulation (AMOC). The most pronounced stadial coolings, Heinrich Stadials (HSs), are associated with massive iceberg discharges to the North Atlantic. This motivates scientists to consider that the North Atlantic freshwater perturbations is a common trigger of the associated abrupt transitions between weak and strong AMOC states. However, recent studies suggest that the Heinrich ice-surging events are triggered by ocean subsurface warming associated with an AMOC slow-down. Furthermore, the duration of ice-rafting events does not systematically coincide with the beginning and end of the pronounced cold conditions during HSs. In this context, we show that both, changes in atmospheric CO2 and ice sheet configuration can provide important control on the stability of the AMOC, using a coupled atmosphere-ocean model. Our simulations reveal that gradual changes in Northern Hemisphere ice sheet height and atmospheric CO2 can act as a trigger of abrupt glacial/deglacial climate changes. The simulated global climate responses—including abrupt warming in the North Atlantic, a northward shift of the tropical rain belts, and Southern Hemisphere cooling related to the bipolar seesaw—are generally consistent with empirical evidence. We further find that under a delicate configuration of atmospheric CO2 and ice sheet height the AMOC can be characterized by a self-oscillation (resonance) feature (Hopf Bifucation) with a 1000-year cycle that is comparable with observed small DO events during the MIS 3. This provides an alternative explanation for millennial-scale DO variability during glacial periods.

Challenges of coordinating global climate observations - Role of satellites in climate monitoring

NASA Astrophysics Data System (ADS)

Richter, C.

2017-12-01

Global observation of the Earth's atmosphere, ocean and land is essential for identifying climate variability and change, and for understanding their causes. Observation also provides data that are fundamental for evaluating, refining and initializing the models that predict how the climate system will vary over the months and seasons ahead, and that project how climate will change in the longer term under different assumptions concerning greenhouse gas emissions and other human influences. Long-term observational records have enabled the Intergovernmental Panel on Climate Change to deliver the message that warming of the global climate system is unequivocal. As the Earth's climate enters a new era, in which it is forced by human activities, as well as natural processes, it is critically important to sustain an observing system capable of detecting and documenting global climate variability and change over long periods of time. High-quality climate observations are required to assess the present state of the ocean, cryosphere, atmosphere and land and place them in context with the past. The global observing system for climate is not a single, centrally managed observing system. Rather, it is a composite "system of systems" comprising a set of climate-relevant observing, data-management, product-generation and data-distribution systems. Data from satellites underpin many of the Essential Climate Variables(ECVs), and their historic and contemporary archives are a key part of the global climate observing system. In general, the ECVs will be provided in the form of climate data records that are created by processing and archiving time series of satellite and in situ measurements. Early satellite data records are very valuable because they provide unique observations in many regions which were not otherwise observed during the 1970s and which can be assimilated in atmospheric reanalyses and so extend the satellite climate data records back in time.

Analytic Perturbation Method for Estimating Ground Flash Fraction from Satellite Lightning Observations

NASA Technical Reports Server (NTRS)

Koshak, William; Solakiewicz, Richard

2013-01-01

An analytic perturbation method is introduced for estimating the lightning ground flash fraction in a set of N lightning flashes observed by a satellite lightning mapper. The value of N is large, typically in the thousands, and the observations consist of the maximum optical group area produced by each flash. The method is tested using simulated observations that are based on Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) data. National Lightning Detection NetworkTM (NLDN) data is used to determine the flash-type (ground or cloud) of the satellite-observed flashes, and provides the ground flash fraction truth for the simulation runs. It is found that the mean ground flash fraction retrieval errors are below 0.04 across the full range 0-1 under certain simulation conditions. In general, it is demonstrated that the retrieval errors depend on many factors (i.e., the number, N, of satellite observations, the magnitude of random and systematic measurement errors, and the number of samples used to form certain climate distributions employed in the model).

Analysis of the regional MiKlip decadal prediction system over Europe: skill, added value of regionalization, and ensemble size dependeny

NASA Astrophysics Data System (ADS)

Reyers, Mark; Moemken, Julia; Pinto, Joaquim; Feldmann, Hendrik; Kottmeier, Christoph; MiKlip Module-C Team

2017-04-01

Decadal climate predictions can provide a useful basis for decision making support systems for the public and private sectors. Several generations of decadal hindcasts and predictions have been generated throughout the German research program MiKlip. Together with the global climate predictions computed with MPI-ESM, the regional climate model (RCM) COSMO-CLM is used for regional downscaling by MiKlip Module-C. The RCMs provide climate information on spatial and temporal scales closer to the needs of potential users. In this study, two downscaled hindcast generations are analysed (named b0 and b1). The respective global generations are both initialized by nudging them towards different reanalysis anomaly fields. An ensemble of five starting years (1961, 1971, 1981, 1991, and 2001), each comprising ten ensemble members, is used for both generations in order to quantify the regional decadal prediction skill for precipitation and near-surface temperature and wind speed over Europe. All datasets (including hindcasts, observations, reanalysis, and historical MPI-ESM runs) are pre-processed in an analogue manner by (i) removing the long-term trend and (ii) re-gridding to a common grid. Our analysis shows that there is potential for skillful decadal predictions over Europe in the regional MiKlip ensemble, but the skill is not systematic and depends on the PRUDENCE region and the variable. Further, the differences between the two hindcast generations are mostly small. As we used detrended time series, the predictive skill found in our study can probably attributed to reasonable predictions of anomalies which are associated with the natural climate variability. In a sensitivity study, it is shown that the results may strongly change when the long-term trend is kept in the datasets, as here the skill of predicting the long-term trend (e.g. for temperature) also plays a major role. The regionalization of the global ensemble provides an added value for decadal predictions for some complex regions like the Mediterranean and Iberian Peninsula, while for other regions no systematic improvement is found. A clear dependence of the performance of the regional MiKlip system on the ensemble size is detected. For all variables in both hindcast generations, the skill increases when the ensemble is enlarged. The results indicate that a number of ten members is an appropriate ensemble size for decadal predictions over Europe.

Observations of Co-variation in Cloud Properties and their Relationships with Atmospheric State

NASA Astrophysics Data System (ADS)

Sinclair, K.; van Diedenhoven, B.; Fridlind, A. M.; Arnold, T. G.; Yorks, J. E.; Heymsfield, G. M.; McFarquhar, G. M.; Um, J.

2017-12-01

Radiative properties of upper tropospheric ice clouds are generally not well represented in global and cloud models. Cloud top height, cloud thermodynamic phase, cloud optical thickness, cloud water path, particle size and ice crystal shape all serve as observational targets for models to constrain cloud properties. Trends or biases in these cloud properties could have profound effects on the climate since they affect cloud radiative properties. Better understanding of co-variation between these cloud properties and linkages with atmospheric state variables can lead to better representation of clouds in models by reducing biases in their micro- and macro-physical properties as well as their radiative properties. This will also enhance our general understanding of cloud processes. In this analysis we look at remote sensing, in situ and reanalysis data from the MODIS Airborne Simulator (MAS), Cloud Physics Lidar (CPL), Cloud Radar System (CRS), GEOS-5 reanalysis data and GOES imagery obtained during the Tropical Composition, Cloud and Climate Coupling (TC4) airborne campaign. The MAS, CPL and CRS were mounted on the ER-2 high-altitude aircraft during this campaign. In situ observations of ice size and shape were made aboard the DC8 and WB57 aircrafts. We explore how thermodynamic phase, ice effective radius, particle shape and radar reflectivity vary with altitude and also investigate how these observed cloud properties vary with cloud type, cloud top temperature, relative humidity and wind profiles. Observed systematic relationships are supported by physical interpretations of cloud processes and any unexpected differences are examined.

A framework for tracking post-wildfire trajectories and desired future conditions using NDVI time series

NASA Astrophysics Data System (ADS)

Norman, S. P.; Hargrove, W. W.; Lee, D. C.; Spruce, J.

2013-12-01

Wildfires could provide a cost-effective means to maintain or restore some aspects of fire-adapted landscapes. Yet with the added influence of climate change and invasives, wildfires may also facilitate or accelerate undesired type conversions. As megafires are becoming increasingly common across portions of the US West, managers require a framework for long-term monitoring that integrates the trajectories of fire-prone landscapes and objectives, not just conditions immediately after a burn. Systematic use of satellite data provides an efficient cross-jurisdictional solution to this problem. Since 2000, MODIS-technology has provided high frequency, 240m resolution observations of Earth. Using this data stream, the ForWarn system, developed through a partnership of the US Forest Service, NASA-Stennis and others, provides 46 estimates of the Normalized Difference Vegetation Index (NDVI) per year for the conterminous US. From this time series, a variety of secondary metrics have been derived including median annual NDVI, amplitude, and phenological spikiness. Each is both a fire and recovery sensitive measure that allows managers to systematically track conditions with respect to either the pre-fire baseline or desired future conditions more adaptively. In dry interior forests where wildfires could be used to thin stands, recovery to untreated conditions may not be desired given fuels objectives or climate change. In more mesic systems, fire effects may be monitored as staged succession. With both coarse filter monitoring and desired conditions in hand, managers can better recognize and prioritize problems in disturbance-prone landscapes.

Quantifying climate feedbacks in polar regions

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

Goosse, Hugues; Kay, Jennifer E.; Armour, Kyle C.

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range ofmore » feedbacks, thus offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.« less

Quantifying climate feedbacks in polar regions

DOE PAGES

Goosse, Hugues; Kay, Jennifer E.; Armour, Kyle C.; ...

2018-05-15

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range ofmore » feedbacks, thus offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.« less

Arctic Sea ice thickness loss determined using subsurface, aircraft, and satellite observations

NASA Astrophysics Data System (ADS)

Lindsay, R. W.; Schweiger, A. J. B.

2014-12-01

Sea ice thickness is a fundamental climate state variable. However, observations of ice thickness have been sparse in time and space making the construction of observation-based time series difficult. Moreover, different groups use a variety of methods and processing procedures to measure ice thickness and each observational source likely has different and poorly characterized measurement and sampling biases. Observational sources include upward looking sonars mounted on submarines or moorings, electromagnetic sensors on helicopters or aircraft, and lidar or radar altimeters on airplanes or satellites. Are these data sources now adequate so that we can construct time series of the mean sea ice thickness with meaningful information about thickness changes? How do the different measurement systems compare in the mean? Are there systematic differences? Very few of the observations provide overlapping measurements of ice of a variety of thickness classes or types for direct comparisons. Error characteristics may vary considerably depending on the presence or thickness of the ridged ice. Here we use a curve-fitting approach to evaluate the systematic differences between eight different observation systems in the Arctic Basin, including ICESat and IceBridge measurements. The approach determines the large-scale spatial and temporal variability of the ice thickness as well as the mean differences between the observation systems using over 3000 estimates of the ice thickness. The thickness estimates are measured over spatial scales of approximately 50 km or time scales of 1 month and the primary time period analyzed is 2000-2013 when the modern mix of observations is available. Good agreement is found between five of the systems, within 0.15 m, while systematic differences of up to 0.5 m are found for three others compare to the five. The annual mean ice thickness for the central Arctic Basin based on observations only has decreased from 3.45 m in 1975 to 1.11 m in 2013, a 68% reduction and there is no indication it may be leveling off as seen in an earlier study of submarine ice drafts by Rothrock et al. (2008). This is nearly double the 36% decline report by them. These results provide additional direct observational confirmation of sea ice losses found in model reanalyses.

'Achieving ensemble': communication in orthopaedic surgical teams and the development of situation awareness--an observational study using live videotaped examples.

PubMed

Bleakley, Alan; Allard, Jon; Hobbs, Adrian

2013-03-01

Focused dialogue, as good communication between practitioners, offers a condition of possibility for development of high levels of situation awareness in surgical teams. This has been termed "achieving ensemble". Situation awareness grasps what is happening in time and space with regard to one's own unfolding work in relation to that of colleagues, and is necessary to maintain patient safety throughout a surgical list. We refined a typology, initially developed for use in studying the dynamics of teams in aviation safety, of 10 kinds of communication within two broad areas: 'Reports', or authoritative acts of communication setting up a monological or authoritative climate; and 'Requests', or facilitative acts of communication setting up a dialogical or participatory climate. We systematically mapped how orthopaedic surgical teams use verbal communication through analysis of videotaped operations using the typology. We asked: 'do orthopaedic surgical teams set up the conditions of possibility for the emergence of situation awareness through effective communication?' We found that orthopaedic surgical teams tend to produce monological rather than dialogical climates. Dialogue increases with more complex cases, but in routine work, communication levels are depressed and one-way, influenced by surgeons working within a traditionally hierarchical and authoritative culture. We suggest that such a monological climate inhibits development of situation awareness and then compromises patient safety. The same teams, however, generate potentially rich educational climates through exchange of profession-specific knowledge and skills, and we suggest that where technical skill exchange is good, non-technical or interpersonal communication skill levels can follow.

Three Decades of Precision Orbit Determination Progress, Achievements, Future Challenges and its Vital Contribution to Oceanography and Climate Research

NASA Technical Reports Server (NTRS)

Luthcke, Scott; Rowlands, David; Lemoine, Frank; Zelensky, Nikita; Beckley, Brian; Klosko, Steve; Chinn, Doug

2006-01-01

Although satellite altimetry has been around for thirty years, the last fifteen beginning with the launch of TOPEX/Poseidon (TP) have yielded an abundance of significant results including: monitoring of ENS0 events, detection of internal tides, determination of accurate global tides, unambiguous delineation of Rossby waves and their propagation characteristics, accurate determination of geostrophic currents, and a multi-decadal time series of mean sea level trend and dynamic ocean topography variability. While the high level of accuracy being achieved is a result of both instrument maturity and the quality of models and correction algorithms applied to the data, improving the quality of the Climate Data Records produced from altimetry is highly dependent on concurrent progress being made in fields such as orbit determination. The precision orbits form the reference frame from which the radar altimeter observations are made. Therefore, the accuracy of the altimetric mapping is limited to a great extent by the accuracy to which a satellite orbit can be computed. The TP mission represents the first time that the radial component of an altimeter orbit was routinely computed with an accuracy of 2-cm. Recently it has been demonstrated that it is possible to compute the radial component of Jason orbits with an accuracy of better than 1-cm. Additionally, still further improvements in TP orbits are being achieved with new techniques and algorithms largely developed from combined Jason and TP data analysis. While these recent POD achievements are impressive, the new accuracies are now revealing subtle systematic orbit error that manifest as both intra and inter annual ocean topography errors. Additionally the construction of inter-decadal time series of climate data records requires the removal of systematic differences across multiple missions. Current and future efforts must focus on the understanding and reduction of these errors in order to generate a complete and consistent time series of improved orbits across multiple missions and decades required for the most stringent climate-related research. This presentation discusses the POD progress and achievements made over nearly three decades, and presents the future challenges, goals and their impact on altimetric derived ocean sciences.

How Can Urban Policies Improve Air Quality and Help Mitigate Global Climate Change: a Systematic Mapping Review.

PubMed

Slovic, Anne Dorothée; de Oliveira, Maria Aparecida; Biehl, João; Ribeiro, Helena

2016-02-01

Tackling climate change at the global level is central to a growing field of scientific research on topics such as environmental health, disease burden, and its resulting economic impacts. At the local level, cities constitute an important hub of atmospheric pollution due to the large amount of pollutants that they emit. As the world population shifts to urban centers, cities will increasingly concentrate more exposed populations. Yet, there is still significant progress to be made in understanding the contribution of urban pollutants other than CO2, such as vehicle emissions, to global climate change. It is therefore particularly important to study how local governments are managing urban air pollution. This paper presents an overview of local air pollution control policies and programs that aim to reduce air pollution levels in megacities. It also presents evidence measuring their efficacy. The paper argues that local air pollution policies are not only beneficial for cities but are also important for mitigating and adapting to global climate change. The results systematize several policy approaches used around the world and suggest the need for more in-depth cross-city studies with the potential to highlight best practices both locally and globally. Finally, it calls for the inclusion of a more human rights-based approach as a mean of guaranteeing of clean air for all and reducing factors that exacerbate climate change.

Phenological sensitivity to climate across taxa and trophic levels.

PubMed

Thackeray, Stephen J; Henrys, Peter A; Hemming, Deborah; Bell, James R; Botham, Marc S; Burthe, Sarah; Helaouet, Pierre; Johns, David G; Jones, Ian D; Leech, David I; Mackay, Eleanor B; Massimino, Dario; Atkinson, Sian; Bacon, Philip J; Brereton, Tom M; Carvalho, Laurence; Clutton-Brock, Tim H; Duck, Callan; Edwards, Martin; Elliott, J Malcolm; Hall, Stephen J G; Harrington, Richard; Pearce-Higgins, James W; Høye, Toke T; Kruuk, Loeske E B; Pemberton, Josephine M; Sparks, Tim H; Thompson, Paul M; White, Ian; Winfield, Ian J; Wanless, Sarah

2016-07-14

Differences in phenological responses to climate change among species can desynchronise ecological interactions and thereby threaten ecosystem function. To assess these threats, we must quantify the relative impact of climate change on species at different trophic levels. Here, we apply a Climate Sensitivity Profile approach to 10,003 terrestrial and aquatic phenological data sets, spatially matched to temperature and precipitation data, to quantify variation in climate sensitivity. The direction, magnitude and timing of climate sensitivity varied markedly among organisms within taxonomic and trophic groups. Despite this variability, we detected systematic variation in the direction and magnitude of phenological climate sensitivity. Secondary consumers showed consistently lower climate sensitivity than other groups. We used mid-century climate change projections to estimate that the timing of phenological events could change more for primary consumers than for species in other trophic levels (6.2 versus 2.5-2.9 days earlier on average), with substantial taxonomic variation (1.1-14.8 days earlier on average).

Health Implications of Climate Change: a Review of the Literature About the Perception of the Public and Health Professionals.

PubMed

Hathaway, Julia; Maibach, Edward W

2018-03-01

Through a systematic search of English language peer-reviewed studies, we assess how health professionals and the public, worldwide, perceive the health implications of climate change. Among health professionals, perception that climate change is harming health appears to be high, although self-assessed knowledge is low, and perceived need to learn more is high. Among the public, few North Americans can list any health impacts of climate change, or who is at risk, but appear to view climate change as harmful to health. Among vulnerable publics in Asia and Africa, awareness of increasing health harms due to specific changing climatic conditions is high. Americans across the political and climate change opinion spectra appear receptive to information about the health aspects of climate change, although findings are mixed. Health professionals feel the need to learn more, and the public appears open to learning more, about the health consequences of climate change.

The Ocean Colour Climate Change Initiative: II. Spatial and Temporal Homogeneity of Satellite Data Retrieval Due to Systematic Effects in Atmospheric Correction Processors

NASA Technical Reports Server (NTRS)

Muller, Dagmar; Krasemann, Hajo; Brewin, Robert J. W.; Brockmann, Carsten; Deschamps, Pierre-Yves; Fomferra, Norman; Franz, Bryan A.; Grant, Mike G.; Groom, Steve B.; Melin, Frederic;

Designing the Climate Observing System of the Future

NASA Astrophysics Data System (ADS)

Weatherhead, Elizabeth C.; Wielicki, Bruce A.; Ramaswamy, V.; Abbott, Mark; Ackerman, Thomas P.; Atlas, Robert; Brasseur, Guy; Bruhwiler, Lori; Busalacchi, Antonio J.; Butler, James H.; Clack, Christopher T. M.; Cooke, Roger; Cucurull, Lidia; Davis, Sean M.; English, Jason M.; Fahey, David W.; Fine, Steven S.; Lazo, Jeffrey K.; Liang, Shunlin; Loeb, Norman G.; Rignot, Eric; Soden, Brian; Stanitski, Diane; Stephens, Graeme; Tapley, Byron D.; Thompson, Anne M.; Trenberth, Kevin E.; Wuebbles, Donald

2018-01-01

Climate observations are needed to address a large range of important societal issues including sea level rise, droughts, floods, extreme heat events, food security, and freshwater availability in the coming decades. Past, targeted investments in specific climate questions have resulted in tremendous improvements in issues important to human health, security, and infrastructure. However, the current climate observing system was not planned in a comprehensive, focused manner required to adequately address the full range of climate needs. A potential approach to planning the observing system of the future is presented in this article. First, this article proposes that priority be given to the most critical needs as identified within the World Climate Research Program as Grand Challenges. These currently include seven important topics: melting ice and global consequences; clouds, circulation and climate sensitivity; carbon feedbacks in the climate system; understanding and predicting weather and climate extremes; water for the food baskets of the world; regional sea-level change and coastal impacts; and near-term climate prediction. For each Grand Challenge, observations are needed for long-term monitoring, process studies and forecasting capabilities. Second, objective evaluations of proposed observing systems, including satellites, ground-based and in situ observations as well as potentially new, unidentified observational approaches, can quantify the ability to address these climate priorities. And third, investments in effective climate observations will be economically important as they will offer a magnified return on investment that justifies a far greater development of observations to serve society's needs.

Nonlinear dynamics and predictability in the atmospheric sciences

NASA Technical Reports Server (NTRS)

Ghil, M.; Kimoto, M.; Neelin, J. D.

1991-01-01

Systematic applications of nonlinear dynamics to studies of the atmosphere and climate are reviewed for the period 1987-1990. Problems discussed include paleoclimatic applications, low-frequency atmospheric variability, and interannual variability of the ocean-atmosphere system. Emphasis is placed on applications of the successive bifurcation approach and the ergodic theory of dynamical systems to understanding and prediction of intraseasonal, interannual, and Quaternary climate changes.

How well does climate change and human health research match the demands of policymakers? A scoping review.

PubMed

Hosking, Jamie; Campbell-Lendrum, Diarmid

2012-08-01

In 2008, the World Health Organization (WHO) Member States passed a World Health Assembly resolution that identified the following five priority areas for research and pilot projects on climate change and human health: health vulnerability, health protection, health impacts of mitigation and adaptation policies, decision-support and other tools, and costs of health protection from climate change. To assess the extent to which recently published research corresponds to these priorities, we undertook a scoping review of original research on climate change and human health. Scoping reviews address topics that are too broad for a systematic review and commonly aim to identify research gaps in existing literature. We also assessed recent publication trends for climate change and health research. We searched for original quantitative research published from 2008 onward. We included disease burden studies that were specific to climate change and health and included intervention studies that focused on climate change and measured health outcomes. We used MEDLINE, Embase, and Web of Science databases and extracted data on research priority areas, geographic regions, health fields, and equity (systematic differences between advantaged and disadvantaged social groups). We identified 40 eligible studies. Compared with other health topics, the number of climate change publications has grown rapidly, with a larger proportion of reviews or editorials. Recent original research addressed four of the five priority areas identified by the WHO Member States, but we found no eligible studies of health adaptation interventions, and most of the studies focused on high-income countries. Climate change and health is a rapidly growing area of research, but quantitative studies remain rare. Among recently published studies, we found gaps in adaptation research and a deficit of studies in most developing regions. Funders and researchers should monitor and respond to research gaps to help ensure that the needs of policymakers are met.

Climate change vulnerability of native and alien freshwater fishes of California: a systematic assessment approach.

PubMed

Moyle, Peter B; Kiernan, Joseph D; Crain, Patrick K; Quiñones, Rebecca M

2013-01-01

Freshwater fishes are highly vulnerable to human-caused climate change. Because quantitative data on status and trends are unavailable for most fish species, a systematic assessment approach that incorporates expert knowledge was developed to determine status and future vulnerability to climate change of freshwater fishes in California, USA. The method uses expert knowledge, supported by literature reviews of status and biology of the fishes, to score ten metrics for both (1) current status of each species (baseline vulnerability to extinction) and (2) likely future impacts of climate change (vulnerability to extinction). Baseline and climate change vulnerability scores were derived for 121 native and 43 alien fish species. The two scores were highly correlated and were concordant among different scorers. Native species had both greater baseline and greater climate change vulnerability than did alien species. Fifty percent of California's native fish fauna was assessed as having critical or high baseline vulnerability to extinction whereas all alien species were classified as being less or least vulnerable. For vulnerability to climate change, 82% of native species were classified as highly vulnerable, compared with only 19% for aliens. Predicted climate change effects on freshwater environments will dramatically change the fish fauna of California. Most native fishes will suffer population declines and become more restricted in their distributions; some will likely be driven to extinction. Fishes requiring cold water (<22°C) are particularly likely to go extinct. In contrast, most alien fishes will thrive, with some species increasing in abundance and range. However, a few alien species will likewise be negatively affected through loss of aquatic habitats during severe droughts and physiologically stressful conditions present in most waterways during summer. Our method has high utility for predicting vulnerability to climate change of diverse fish species. It should be useful for setting conservation priorities in many different regions.

Climate Change Vulnerability of Native and Alien Freshwater Fishes of California: A Systematic Assessment Approach

PubMed Central

Moyle, Peter B.; Kiernan, Joseph D.; Crain, Patrick K.; Quiñones, Rebecca M.

2013-01-01

Freshwater fishes are highly vulnerable to human-caused climate change. Because quantitative data on status and trends are unavailable for most fish species, a systematic assessment approach that incorporates expert knowledge was developed to determine status and future vulnerability to climate change of freshwater fishes in California, USA. The method uses expert knowledge, supported by literature reviews of status and biology of the fishes, to score ten metrics for both (1) current status of each species (baseline vulnerability to extinction) and (2) likely future impacts of climate change (vulnerability to extinction). Baseline and climate change vulnerability scores were derived for 121 native and 43 alien fish species. The two scores were highly correlated and were concordant among different scorers. Native species had both greater baseline and greater climate change vulnerability than did alien species. Fifty percent of California’s native fish fauna was assessed as having critical or high baseline vulnerability to extinction whereas all alien species were classified as being less or least vulnerable. For vulnerability to climate change, 82% of native species were classified as highly vulnerable, compared with only 19% for aliens. Predicted climate change effects on freshwater environments will dramatically change the fish fauna of California. Most native fishes will suffer population declines and become more restricted in their distributions; some will likely be driven to extinction. Fishes requiring cold water (<22°C) are particularly likely to go extinct. In contrast, most alien fishes will thrive, with some species increasing in abundance and range. However, a few alien species will likewise be negatively affected through loss of aquatic habitats during severe droughts and physiologically stressful conditions present in most waterways during summer. Our method has high utility for predicting vulnerability to climate change of diverse fish species. It should be useful for setting conservation priorities in many different regions. PMID:23717503

A GLM Post-processor to Adjust Ensemble Forecast Traces

NASA Astrophysics Data System (ADS)

Thiemann, M.; Day, G. N.; Schaake, J. C.; Draijer, S.; Wang, L.

2011-12-01

The skill of hydrologic ensemble forecasts has improved in the last years through a better understanding of climate variability, better climate forecasts and new data assimilation techniques. Having been extensively utilized for probabilistic water supply forecasting, interest is developing to utilize these forecasts in operational decision making. Hydrologic ensemble forecast members typically have inherent biases in flow timing and volume caused by (1) structural errors in the models used, (2) systematic errors in the data used to calibrate those models, (3) uncertain initial hydrologic conditions, and (4) uncertainties in the forcing datasets. Furthermore, hydrologic models have often not been developed for operational decision points and ensemble forecasts are thus not always available where needed. A statistical post-processor can be used to address these issues. The post-processor should (1) correct for systematic biases in flow timing and volume, (2) preserve the skill of the available raw forecasts, (3) preserve spatial and temporal correlation as well as the uncertainty in the forecasted flow data, (4) produce adjusted forecast ensembles that represent the variability of the observed hydrograph to be predicted, and (5) preserve individual forecast traces as equally likely. The post-processor should also allow for the translation of available ensemble forecasts to hydrologically similar locations where forecasts are not available. This paper introduces an ensemble post-processor (EPP) developed in support of New York City water supply operations. The EPP employs a general linear model (GLM) to (1) adjust available ensemble forecast traces and (2) create new ensembles for (nearby) locations where only historic flow observations are available. The EPP is calibrated by developing daily and aggregated statistical relationships form historical flow observations and model simulations. These are then used in operation to obtain the conditional probability density function (PDF) of the observations to be predicted, thus jointly adjusting individual ensemble members. These steps are executed in a normalized transformed space ('z'-space) to account for the strong non-linearity in the flow observations involved. A data window centered on each calibration date is used to minimize impacts from sampling errors and data noise. Testing on datasets from California and New York suggests that the EPP can successfully minimize biases in ensemble forecasts, while preserving the raw forecast skill in a 'days to weeks' forecast horizon and reproducing the variability of climatology for 'weeks to years' forecast horizons.

A data centred method to estimate and map how the local distribution of daily precipitation is changing

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nick

2014-05-01

Estimates of how our climate is changing are needed locally in order to inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles in distributions of variables such as daily temperature or precipitation. Here we focus on these local changes and on a method to transform daily observations of precipitation into patterns of local climate change. We develop a method[1] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes, to specifically address the challenges presented by daily precipitation data. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the relative amount of precipitation in those days. Our method is a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of how fast different quantiles of precipitation distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily precipitation from specific locations across Europe over the last 60 years. We treat geographical location and precipitation as independent variables and thus obtain as outputs the pattern of change at a given threshold of precipitation and with geographical location. This is model- independent, thus providing data of direct value in model calibration and assessment. Our results show regionally consistent patterns of systematic increase in precipitation on the wettest days, and of drying across all days which is of potential value in adaptation planning. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, 371 20120287; D. A. Stainforth, 2013, S. C. Chapman, N. W. Watkins, Mapping climate change in European temperature distributions, Environ. Res. Lett. 8, 034031 [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119

Trends and Bioclimatic Assessment of Extreme Indices: Emerging Insights for Rainfall Derivative Crop Microinsurance in Central-West Nigeria

NASA Astrophysics Data System (ADS)

Awolala, D. O.

2015-12-01

Scientific predictions have forecasted increasing economic losses by which farming households will be forced to consider new adaptation pathways to close the food gap and be income secure. Pro-poor adaptation planning decisions therefore must rely on location-specific details from systematic assessment of extreme climate indices to provide template for most suitable financial adaptation instruments. This paper examined critical loss point to water stress in maize production and risk-averse behaviour to extreme local climate in Central West Nigeria. Trends of extreme indices and bio-climatic assessment based on RClimDex for numerical weather predictions were carried out using a 3-decade time series daily observational climate data of the sub-humid region. The study reveals that the flowering and seed formation stage was identified as the most critical loss point when seed formation is a function of per unit soil water available for uptake. The sub-humid has a bi-modal rainfall pattern but faces longer dry spell with a fast disappearing mild climate measured by budyko evaporation of 80.1%. Radiation index of dryness of 1.394 confirms the region is rapidly becoming drier at an evaporation rate of 949 mm/year and rainfall deficit of 366 mm/year. Net primary production from rainfall is fast declining by 1634 g(DM)/m2/year. These conditions influenced by monthly rainfall uncertainties are associated with losses of standing crops because farmers are uncertain of rainfall probability distribution especially during most important vegetative stage. In a simulated warmer climate, an absolute dryness of months was observed compared with 4 dry months in a normal climate which explains triggers of food deficits and income losses. Positive coefficients of tropical nights (TR20), warm nights (TN90P) and warm days (TX90P), and the negative coefficient of cold days (TX10P) with time are significant at P<0.05. The increasing gradient of warm spell indicator (WSDI), the decreasing gradients of cold nights (TN10P) and cold days (TX10P) are added evidence of aridity arising from increasing rainfall deficits. This paper recommends that the region needs rainfall-based index microinsurance adaptation financial instruments capable of sharing covariate shocks with farmers within an incentive-based risk sharing framework.

Evaluating NASA S-NPP continuity cloud products for climate research using CALIPSO, CATS and Level-3 analysis

NASA Astrophysics Data System (ADS)

Holz, R.; Platnick, S. E.; Meyer, K.; Frey, R.; Wind, G.; Ackerman, S. A.; Heidinger, A. K.; Botambekov, D.; Yorks, J. E.; McGill, M. J.

2016-12-01

The launch of VIIRS and CrIS on Suomi NPP in the fall of 2011 introduced the next generation of U.S. operational polar orbiting environmental observations. Similar to MODIS, VIIRS provides visible and IR observations at moderate spatial resolution and has a 1:30 pm equatorial crossing time consistent with the MODIS on Aqua platform. However unlike MODIS, VIIRS lacks water vapor and CO2 absorbing channels that are used by the MODIS cloud algorithms for both cloud detection and to retrieve cloud top height and cloud emissivity for ice clouds. Given the different spectral and spatial characteristics of VIIRS, we seek to understand the extent to which the 15-year MODIS climate record can be continued with VIIRS/CrIS observations while maintaining consistent sensitivities across the observational systems. This presentation will focus on the evaluation of the latest version of the NASA funded cloud retrieval algorithms being developed for climate research. We will present collocated inter-comparisons between the imagers (VIIRS and MODIS Aqua) with CALIPSO and Cloud Aerosol Transport System (CATS) lidar observations as well as long term statistics based on a new Level-3 (L3) product being developed as part the project. The CALIPSO inter-comparisons will focus on cloud detection (cloud mask) with a focus on the impact of recent modifications to the cloud mask and how these changes impact the global statistics. For the first time we will provide inter-comparisons between two different cloud lidar systems (CALIOP and CATS) and investigate how the different sensitivities of the lidars impact the cloud mask and cloud comparisons. Using CALIPSO and CATS as the reference, and applying the same algorithms to VIIRS and MODIS, we will discuss the consistency between products from both imagers. The L3 analysis will focus on the regional and seasonal consistency between the suite of MODIS and VIIRS continuity cloud products. Do systematic biases remains when using consistent algorithms but applied to different observations (MODIS or VIIRS)?

From WHAT We Know to HOW We Know It: Students Talk about Climate Change

NASA Astrophysics Data System (ADS)

Holthuis, N.; Lotan, R.; Saltzman, J.; Mastrandrea, M. D.

2012-12-01

The climate change community has begun to look carefully at how the public understands, or fails to understand, climate change data and the scientific claims made based on these data. Researchers (Bowen et al, 2008) have found that a deficit model of knowledge doesn't fully explain why people continue to disagree about climate change or are unwilling to change their behaviors. "Deniers" do not become "acceptors" simply by filling up their cognitive data banks with more information. This suggests that teachers need to provide scaffolding that supports not only students' understanding of how climate systems work or the causes and effects of climate change but includes how we know what we know. That is, instruction shifts from an exclusive focus on content knowledge to one that aims to develop critical analytic skills and scientific habits of mind. For example, students need to not only understand the effects of human activity on climate change, but also learn to identify and analyze the evidence for anthropogenic climate change and how that evidence has built over time. They can then evaluate the evidence as well as whether the claims made are justified given the data. Climate literacy then includes content knowledge as well as understanding of the scientific practices that lead to building that knowledge. In this study, we report on the research and evaluation of the NASA-funded Stanford Global Climate Change: Professional Development for K-12 Teachers. We focus on data from the last year of a three-year project in which climate scientists and science educators collaborated to develop curriculum and provide professional development for secondary school teachers on the science and the pedagogy of global climate change. As teachers implemented the curriculum in their classrooms, we collected pre- and post-tests, classroom observations, video recordings, and post-implementation interviews with the teachers. Our analyses serve to document: 1) how students talk about HOW we know about climate change, 2) in what ways the curriculum and the teaching practices support this type of student talk, 3) how the quantity and quality of student talk leads to a greater understanding of both WHAT we know about climate change and HOW we know it. Through systematic classroom observations, we documented student engagement and interactions. In-depth analysis of video recordings revealed more about the nature of these interactions and how students talk with each other and the teacher about how we know. From pre- and post-tests of 756 middle school and high school students in 30 classrooms, we found statistically significant differences (t=-19.78, p<0.001) between total scores on the pre-test (68.1 % correct) and post-test (79.1% correct). At the classroom level, these data served to create portraits of classrooms where "how do we know talk" was prevalent and where teaching practices supported such talk. In these classrooms, students showed significant gains in both content knowledge and analytic skills. We argue that these students became climate literate and thus better equipped to critically distinguish between climate science and non-science they might encounter via the internet, the media, or other sources.

The Sunspot Record: 1826-1980

NASA Technical Reports Server (NTRS)

Hathaway, David H.

2014-01-01

The International Sunspot Number is used as a measure of the level of solar activity in many important studies. This includes studies of the effects of solar activity on climate change and on the generation of radioisotopes used to infer levels of solar activity going back thousands of years. Any systematic errors in the historical record of the sunspot number can profoundly alter the conclusions of these studies. There is substantial evidence that the currently accepted International Sunspot Numbers have been subjected to changes in the way the numbers are calculated and to changes in the weights given to observations of various observers. In this talk I will focus on the time period from 1826 to 1980 which covers principal observers Schwabe, Wolf, Wolfer, Brunner, and Waldmeier. Previous investigations have indicated problems associated with Schwabe's observations (1826 to 1867), the first decades of the Greenwich observations (1874 to about 1910), and the introduction of a different counting method by Waldmeier (1946-1980). I will examine the evidence for these problems and the possible solutions that might be used to provide improved estimates of the sunspot numbers and their errors over this time interval.

Making NASA Earth Observing System Satellite Data Accessible to the K-12 and Citizen Scientist Communities

NASA Technical Reports Server (NTRS)

Moore, Susan W.; Phelps, Carrie S.; Chambers, Lin H.

2004-01-01

The Atmospheric Sciences Data Center (ASDC) at NASA s Langley Research Center houses over 700 data sets related to Earth s radiation budget, clouds, aerosols and tropospheric chemistry. These data sets are produced to increase academic understanding of the natural and anthropogenic perturbations that influence global climate change. The Mentoring and inquirY using NASA Data on Atmospheric and earth science for Teachers and Amateurs (MY NASA DATA) project has been established to systematically support educational activities at all levels of formal and informal education by reducing these large data holdings to microsets that will be easily explored and understood by the K-12 and the amateur scientist communities

Paleokarst processes in the Eocene limestones of the Pyramids Plateau, Giza, Egypt

NASA Astrophysics Data System (ADS)

El Aref, M. M.; Refai, E.

The Eocene limestones of the Pyramids plateau are characterized by landforms of stepped terraced escarpment and karst ridges with isolated hills. The carbonate country rocks are also dominated by minor surface, surface to subsurface and subsurface solution features associated with karst products. The systematic field observations eludicate the denudation trend of the minor solution features and suggest the origin of the regional landscapes. The lithologic and structural characters of the limestone country rocks comprise the main factors controlling the surface and subsurface karst evolution. The development of the karst features and the associated sediments in the study area provides information on the paleohydrolic, chemical and climatic environments involved in the origin of the karstification.

Impact of TRMM and SSM/I-derived Precipitation and Moisture Data on the GEOS Global Analysis

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.

1999-01-01

Current global analyses contain significant errors in primary hydrological fields such as precipitation, evaporation, and related cloud and moisture in the tropics. The Data Assimilation Office at NASA's Goddard Space Flight Center has been exploring the use of space-based rainfall and total precipitable water (TPW) estimates to constrain these hydrological parameters in the Goddard Earth Observing System (GEOS) global data assimilation system. We present results showing that assimilating the 6-hour averaged rain rates and TPW estimates from the Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave/Imager (SSM/I) instruments improves not only the precipitation and moisture estimates but also reduce state-dependent systematic errors in key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation. The improved analysis also improves short-range forecasts beyond 1 day, but the impact is relatively modest compared with improvements in the time-averaged analysis. The study shows that, in the presence of biases and other errors of the forecast model, improving the short-range forecast is not necessarily prerequisite for improving the assimilation as a climate data set. The full impact of a given type of observation on the assimilated data set should not be measured solely in terms of forecast skills.

Earth System Models Underestimate Soil Carbon Diagnostic Times in Dry and Cold Regions.

NASA Astrophysics Data System (ADS)

Jing, W.; Xia, J.; Zhou, X.; Huang, K.; Huang, Y.; Jian, Z.; Jiang, L.; Xu, X.; Liang, J.; Wang, Y. P.; Luo, Y.

2017-12-01

Soils contain the largest organic carbon (C) reservoir in the Earth's surface and strongly modulate the terrestrial feedback to climate change. Large uncertainty exists in current Earth system models (ESMs) in simulating soil organic C (SOC) dynamics, calling for a systematic diagnosis on their performance based on observations. Here, we built a global database of SOC diagnostic time (i.e.,turnover times; τsoil) measured at 320 sites with four different approaches. We found that the estimated τsoil was comparable among approaches of 14C dating () (median with 25 and 75 percentiles), 13C shifts due to vegetation change () and the ratio of stock over flux (), but was shortest from laboratory incubation studies (). The state-of-the-art ESMs underestimated the τsoil in most biomes, even by >10 and >5 folds in cold and dry regions, respectively. Moreover,we identified clear negative dependences of τsoil on temperature and precipitation in both of the observational and modeling results. Compared with Community Land Model (version 4), the incorporation of soil vertical profile (CLM4.5) could substantially extend the τsoil of SOC. Our findings suggest the accuracy of climate-C cycle feedback in current ESMs could be enhanced by an improved understanding of SOC dynamics under the limited hydrothermal conditions.

Distributed modeling of ablation (1996–2011) and climate sensitivity on the glaciers of Taylor Valley, Antarctica

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

Hoffman, Matthew J.; Fountain, Andrew G.; Liston, Glen E.

Here, the McMurdo Dry Valleys of Antarctica host the coldest and driest ecosystem on Earth, which is acutely sensitive to the availability of water coming from glacial runoff. We modeled the spatial variability in ablation and assessed climate sensitivity of the glacier ablation zones using 16 years of meteorological and surface mass-balance observations collected in Taylor Valley. Sublimation was the primary form of mass loss over much of the ablation zones, except for near the termini where melt, primarily below the surface, dominated. Microclimates in ~10 m scale topographic basins generated melt rates up to ten times higher than overmore » smooth glacier surfaces. In contrast, the vertical terminal cliffs on the glaciers can have higher or lower melt rates than the horizontal surfaces due to differences in incoming solar radiation. The model systematically underpredicted ablation for the final 5 years studied, possibly due to an increase of windblown sediment. Surface mass-balance sensitivity to temperature was ~–0.02 m w.e. K –1, which is among the smallest magnitudes observed globally. We also identified a high sensitivity to ice albedo, with a decrease of 0.02 having similar effects as a 1 K increase in temperature, and a complex sensitivity to wind speed.« less

Connecting Snowmelt Runoff Timing Changes to Watershed Characteristics in California

NASA Astrophysics Data System (ADS)

Stewart, I. T.; Peterson, D. H.

2008-12-01

Shifts in the timing of snowmelt runoff are an expected consequence of climatic changes and have been observed throughout western North America for the past several decades. While the snowmelt runoff has in general come earlier, the magnitude, and sometimes direction, of streamflow timing trends has varied throughout the region in a manner that is not explained by the differences in location or gauge elevation alone. The gauge-to-gauge differences in the observed streamflow timing trends, which have not been systematically explored, are investigated in this study by linking the hydrologic response of a stream to the physical characteristics of the watershed above the gauge. To this end, the very recent trends in streamflow timing measures (such as the timing of the start of the spring snowmelt pulse, the timing of the center of mass for flow, the annual flow, and the timing of the day when maximum flow occurs) for approximately 60 snowmelt-dominated gauges in California were analyzed in conjunction with a GIS-based data base of the watershed characteristics (such as elevation distribution, slope, aspect, and vegetation) through the 2008 runoff season. The improved knowledge of how a watershed has reacted to recent climatic changes can aid in the development of future adaptive strategies in managing water resources in California.

Distributed modeling of ablation (1996–2011) and climate sensitivity on the glaciers of Taylor Valley, Antarctica

DOE PAGES

Hoffman, Matthew J.; Fountain, Andrew G.; Liston, Glen E.

2016-02-24

Here, the McMurdo Dry Valleys of Antarctica host the coldest and driest ecosystem on Earth, which is acutely sensitive to the availability of water coming from glacial runoff. We modeled the spatial variability in ablation and assessed climate sensitivity of the glacier ablation zones using 16 years of meteorological and surface mass-balance observations collected in Taylor Valley. Sublimation was the primary form of mass loss over much of the ablation zones, except for near the termini where melt, primarily below the surface, dominated. Microclimates in ~10 m scale topographic basins generated melt rates up to ten times higher than overmore » smooth glacier surfaces. In contrast, the vertical terminal cliffs on the glaciers can have higher or lower melt rates than the horizontal surfaces due to differences in incoming solar radiation. The model systematically underpredicted ablation for the final 5 years studied, possibly due to an increase of windblown sediment. Surface mass-balance sensitivity to temperature was ~–0.02 m w.e. K –1, which is among the smallest magnitudes observed globally. We also identified a high sensitivity to ice albedo, with a decrease of 0.02 having similar effects as a 1 K increase in temperature, and a complex sensitivity to wind speed.« less

Solar radiation and landscape evolution: co-evolution of topography, vegetation, and erosion rates in a semi-arid ecosystem

NASA Astrophysics Data System (ADS)

Istanbulluoglu, Erkan; Yetemen, Omer

2016-04-01

In this study CHILD landscape evolution model (LEM) is used to study the role of solar radiation on the co-evolution of landscape morphology, vegetation patterns, and erosion rates in a central New Mexico catchment. In the study site north facing slopes (NFS) are characterized by steep diffusion-dominated planar hillslopes covered by co-exiting juniper pine and grass vegetation. South facing slopes (SFS) are characterized by shallow slopes and covered by sparse shrub vegetation. Measured short-term and Holocene-averaged erosion rates show higher soil loss on SFS than NFS. In this study CHILD LEM is first confirmed with ecohydrologic field data and used to systematically examine the co-evolution of topography, vegetation pattern, and erosion rates. Aspect- and network-control are identified as the two main topographic drivers of soil moisture and vegetation organization on the landscape. Landscape-scale and long-term implications of solar radiation driven ecohdrologic patterns emerged in modeled landscape: NFS supported denser vegetation cover and became steeper and planar, while on SFS vegetation grew sparser and slopes declined with more fluvial activity. At the landscape scale, these differential erosion processes led to asymmetric development of catchment forms, consistent with regional observations. While the general patterns of vegetation and topography were reproduced by the model using a stationary representation of the current climate, the observed differential Holocene erosion rates were captured by the model only when cyclic climate is used. This suggests sensitivity of Holocene erosion rates to long-term climate fluctuations.

Modeling Elevation and Aspect Controls on Emerging Ecohydrologic Processes and Ecosystem Patterns Using the Component-based Landlab Framework

NASA Astrophysics Data System (ADS)

Nudurupati, S. S.; Istanbulluoglu, E.; Adams, J. M.; Hobley, D. E. J.; Gasparini, N. M.; Tucker, G. E.; Hutton, E. W. H.

2014-12-01

Topography plays a commanding role on the organization of ecohydrologic processes and resulting vegetation patterns. In southwestern United States, climate conditions lead to terrain aspect- and elevation-controlled ecosystems, with mesic north-facing and xeric south-facing vegetation types; and changes in biodiversity as a function of elevation from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations and ridge tops. These observed patterns have been attributed to differences in topography-mediated local soil moisture availability, micro-climatology, and life history processes of plants that control chances of plant establishment and survival. While ecohydrologic models represent local vegetation dynamics in sufficient detail up to sub-hourly time scales, plant life history and competition for space and resources has not been adequately represented in models. In this study we develop an ecohydrologic cellular automata model within the Landlab component-based modeling framework. This model couples local vegetation dynamics (biomass production, death) and plant establishment and competition processes for resources and space. This model is used to study the vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. Processes that lead to observed plant types across the landscape are examined by initializing the domain with randomly assigned plant types and systematically changing model parameters that couple plant response with soil moisture dynamics. Climate perturbation experiments are conducted to examine the plant response in space and time. Understanding the inherently transient ecohydrologic systems is critical to improve predictions of climate change impacts on ecosystems.

Recent climatic, cryospheric, and hydrological changes over the interior of western Canada: a synthesis and review

NASA Astrophysics Data System (ADS)

DeBeer, C. M.; Wheater, H. S.; Carey, S. K.; Chun, K. P.

2015-08-01

It is well-established that the Earth's climate system has warmed significantly over the past several decades, and in association there have been widespread changes in various other Earth system components. This has been especially prevalent in the cold regions of the northern mid to high-latitudes. Examples of these changes can be found within the western and northern interior of Canada, a region that exemplifies the scientific and societal issues faced in many other similar parts of the world, and where impacts have global-scale consequences. This region has been the geographic focus of a large amount of previous research on changing climatic, cryospheric, and hydrological Earth system components in recent decades, while current initiatives such as the Changing Cold Regions Network (CCRN) seek to further develop the understanding and diagnosis of this change and hence improve predictive capacity. This paper provides an integrated review of the observed changes in these Earth system components and a concise and up-to-date regional picture of some of the temporal trends over the interior of western Canada since the mid or late-20th century. The focus is on air temperature, precipitation, seasonal snow cover, mountain glaciers, permafrost, freshwater ice cover, and river discharge. Important long-term observational networks and datasets are described, and qualitative linkages among the changing components are highlighted. Systematic warming and significant changes to precipitation, snow and ice regimes are unambiguous. However, integrated effects on streamflow are complex. It is argued that further diagnosis is required before predictions of future change can be made with confidence.

Identifying causes of Western Pacific ITCZ drift in ECMWF System 4 hindcasts

NASA Astrophysics Data System (ADS)

Shonk, Jonathan K. P.; Guilyardi, Eric; Toniazzo, Thomas; Woolnough, Steven J.; Stockdale, Tim

2018-02-01

The development of systematic biases in climate models used in operational seasonal forecasting adversely affects the quality of forecasts they produce. In this study, we examine the initial evolution of systematic biases in the ECMWF System 4 forecast model, and isolate aspects of the model simulations that lead to the development of these biases. We focus on the tendency of the simulated intertropical convergence zone in the western equatorial Pacific to drift northwards by between 0.5° and 3° of latitude depending on season. Comparing observations with both fully coupled atmosphere-ocean hindcasts and atmosphere-only hindcasts (driven by observed sea-surface temperatures), we show that the northward drift is caused by a cooling of the sea-surface temperature on the Equator. The cooling is associated with anomalous easterly wind stress and excessive evaporation during the first twenty days of hindcast, both of which occur whether air-sea interactions are permitted or not. The easterly wind bias develops immediately after initialisation throughout the lower troposphere; a westerly bias develops in the upper troposphere after about 10 days of hindcast. At this point, the baroclinic structure of the wind bias suggests coupling with errors in convective heating, although the initial wind bias is barotropic in structure and appears to have an alternative origin.

Graptolite community responses to global climate change and the Late Ordovician mass extinction.

PubMed

Sheets, H David; Mitchell, Charles E; Melchin, Michael J; Loxton, Jason; Štorch, Petr; Carlucci, Kristi L; Hawkins, Andrew D

2016-07-26

Mass extinctions disrupt ecological communities. Although climate changes produce stress in ecological communities, few paleobiological studies have systematically addressed the impact of global climate changes on the fine details of community structure with a view to understanding how changes in community structure presage, or even cause, biodiversity decline during mass extinctions. Based on a novel Bayesian approach to biotope assessment, we present a study of changes in species abundance distribution patterns of macroplanktonic graptolite faunas (∼447-444 Ma) leading into the Late Ordovician mass extinction. Communities at two contrasting sites exhibit significant decreases in complexity and evenness as a consequence of the preferential decline in abundance of dysaerobic zone specialist species. The observed changes in community complexity and evenness commenced well before the dramatic population depletions that mark the tipping point of the extinction event. Initially, community changes tracked changes in the oceanic water masses, but these relations broke down during the onset of mass extinction. Environmental isotope and biomarker data suggest that sea surface temperature and nutrient cycling in the paleotropical oceans changed sharply during the latest Katian time, with consequent changes in the extent of the oxygen minimum zone and phytoplankton community composition. Although many impacted species persisted in ephemeral populations, increased extinction risk selectively depleted the diversity of paleotropical graptolite species during the latest Katian and early Hirnantian. The effects of long-term climate change on habitats can thus degrade populations in ways that cascade through communities, with effects that culminate in mass extinction.

Impact of Ambient Humidity on Child Health: A Systematic Review

PubMed Central

Gao, Jinghong; Sun, Yunzong; Lu, Yaogui; Li, Liping

2014-01-01

Background and Objectives Changes in relative humidity, along with other meteorological factors, accompany ongoing climate change and play a significant role in weather-related health outcomes, particularly among children. The purpose of this review is to improve our understanding of the relationship between ambient humidity and child health, and to propose directions for future research. Methods A comprehensive search of electronic databases (PubMed, Medline, Web of Science, ScienceDirect, OvidSP and EBSCO host) and review of reference lists, to supplement relevant studies, were conducted in March 2013. All identified records were selected based on explicit inclusion criteria. We extracted data from the included studies using a pre-designed data extraction form, and then performed a quality assessment. Various heterogeneities precluded a formal quantitative meta-analysis, therefore, evidence was compiled using descriptive summaries. Results Out of a total of 3797 identified records, 37 papers were selected for inclusion in this review. Among the 37 studies, 35% were focused on allergic diseases and 32% on respiratory system diseases. Quality assessment revealed 78% of the studies had reporting quality scores above 70%, and all findings demonstrated that ambient humidity generally plays an important role in the incidence and prevalence of climate-sensitive diseases among children. Conclusions With climate change, there is a significant impact of ambient humidity on child health, especially for climate-sensitive infectious diseases, diarrhoeal diseases, respiratory system diseases, and pediatric allergic diseases. However, some inconsistencies in the direction and magnitude of the effects are observed. PMID:25503413

Warming and Cooling: The Medieval Climate Anomaly in Africa and Arabia

NASA Astrophysics Data System (ADS)

Lüning, Sebastian; Gałka, Mariusz; Vahrenholt, Fritz

2017-11-01

The Medieval Climate Anomaly (MCA) is a well-recognized climate perturbation in many parts of the world, with a core period of 1000-1200 Common Era. Here we present a palaeotemperature synthesis for the MCA in Africa and Arabia, based on 44 published localities. The data sets have been thoroughly correlated and the MCA trends palaeoclimatologically mapped. The vast majority of available Afro-Arabian onshore sites suggest a warm MCA, with the exception of the southern Levant where the MCA appears to have been cold. MCA cooling has also been documented in many segments of the circum-Africa-Arabian upwelling systems, as a result of changes in the wind systems which were leading to an intensification of cold water upwelling. Offshore cores from outside upwelling systems mostly show warm MCA conditions. The most likely key drivers of the observed medieval climate change are solar forcing and ocean cycles. Conspicuous cold spikes during the earliest and latest MCA may help to discriminate between solar (Oort Minimum) and ocean cycle (Atlantic Multidecadal Oscillation, AMO) influence. Compared to its large share of nearly one quarter of the world's landmass, data from Africa and Arabia are significantly underrepresented in global temperature reconstructions of the past 2,000 years. Onshore data are still absent for most regions in Africa and Arabia, except for regional data clusters in Morocco, South Africa, the East African Rift, and the Levant coast. In order to reconstruct land palaeotemperatures more robustly over Africa and Arabia, a systematic research program is needed.

Graptolite community responses to global climate change and the Late Ordovician mass extinction

NASA Astrophysics Data System (ADS)

Sheets, H. David; Mitchell, Charles E.; Melchin, Michael J.; Loxton, Jason; Štorch, Petr; Carlucci, Kristi L.; Hawkins, Andrew D.

2016-07-01

Mass extinctions disrupt ecological communities. Although climate changes produce stress in ecological communities, few paleobiological studies have systematically addressed the impact of global climate changes on the fine details of community structure with a view to understanding how changes in community structure presage, or even cause, biodiversity decline during mass extinctions. Based on a novel Bayesian approach to biotope assessment, we present a study of changes in species abundance distribution patterns of macroplanktonic graptolite faunas (˜447-444 Ma) leading into the Late Ordovician mass extinction. Communities at two contrasting sites exhibit significant decreases in complexity and evenness as a consequence of the preferential decline in abundance of dysaerobic zone specialist species. The observed changes in community complexity and evenness commenced well before the dramatic population depletions that mark the tipping point of the extinction event. Initially, community changes tracked changes in the oceanic water masses, but these relations broke down during the onset of mass extinction. Environmental isotope and biomarker data suggest that sea surface temperature and nutrient cycling in the paleotropical oceans changed sharply during the latest Katian time, with consequent changes in the extent of the oxygen minimum zone and phytoplankton community composition. Although many impacted species persisted in ephemeral populations, increased extinction risk selectively depleted the diversity of paleotropical graptolite species during the latest Katian and early Hirnantian. The effects of long-term climate change on habitats can thus degrade populations in ways that cascade through communities, with effects that culminate in mass extinction.

The Social Impact of Climate

NASA Astrophysics Data System (ADS)

Hsiang, S. M.

2013-12-01

Managing climate change requires that we understand the social value of climate-related decisions. Rational decision-making demands that we weigh the potential benefits of climate-related investments against their costs. To date, it has been challenging to quantify the relative social benefit of living under different climatic conditions, so policy debates tend to focus on investment costs without considering their benefits. Here I will discuss challenges and advances in the measurement of climate's impact on society. By linking data and methods across physical and social sciences, we are beginning to understand when, where, and how climatic conditions have a causal impact on human wellbeing. I will present examples from this burgeoning interdisciplinary field that quantify the effect of temperature on macroeconomic performance, the effects of climate on human conflict, and the long-term health and economic impact of tropical cyclones. Each of these examples provide new insight into previously unknown benefits of various climate management strategies. I conclude by describing new efforts to systematically gather and compare findings from across the research community to support informed and rational climate management decisions.

The Portuguese Climate Portal

NASA Astrophysics Data System (ADS)

Gomes, Sandra; Deus, Ricardo; Nogueira, Miguel; Viterbo, Pedro; Miranda, Miguel; Antunes, Sílvia; Silva, Alvaro; Miranda, Pedro

2016-04-01

The Portuguese Local Warming Website (http://portaldoclima.pt) has been developed in order to support the society in Portugal in preparing for the adaptation to the ongoing and future effects of climate change. The climate portal provides systematic and easy access to authoritative scientific data ready to be used by a vast and diverse user community from different public and private sectors, key players and decision makers, but also to high school students, contributing to the increase in knowledge and awareness on climate change topics. A comprehensive set of regional climate variables and indicators are computed, explained and graphically presented. Variables and indicators were built in agreement with identified needs after consultation of the relevant social partners from different sectors, including agriculture, water resources, health, environment and energy and also in direct cooperation with the Portuguese National Strategy for Climate Change Adaptation (ENAAC) group. The visual interface allows the user to dynamically interact, explore, quickly analyze and compare, but also to download and import the data and graphics. The climate variables and indicators are computed from state-of-the-art regional climate model (RCM) simulations (e.g., CORDEX project), at high space-temporal detail, allowing to push the limits of the projections down to local administrative regions (NUTS3) and monthly or seasonal periods, promoting local adaptation strategies. The portal provides both historical data (observed and modelled for the 1971-2000 period) and future climate projections for different scenarios (modelled for the 2011-2100 period). A large effort was undertaken in order to quantify the impacts of the risk of extreme events, such as heavy rain and flooding, droughts, heat and cold waves, and fires. Furthermore the different climate scenarios and the ensemble of RCM models, with high temporal (daily) and spatial (~11km) detail, is taken advantage in order to quantify a plausible evolution of climate impacts and its uncertainties. Clear information on the data value and limitations is also provided. The portal is expected to become a reference tool for evaluation of impacts and vulnerabilities due to climate change, increased awareness and promotion of local adaptation and sustainable development in Portugal. The Portuguese Local Warming Website is part of the ADAPT programme, and is co-funded by the EEA financial mechanism and the Portuguese Carbon Fund.

A Paleoclimate Modeling Perspective on the Challenges to Quantifying Paleoelevation

NASA Astrophysics Data System (ADS)

Poulsen, C. J.; Aron, P.; Feng, R.; Fiorella, R.; Shen, H.; Skinner, C. B.

2016-12-01

Surface elevation is a fundamental characteristic of the land surface. Gradients in elevation associated with mountain ranges are a first order control on local and regional climate; weathering, erosion and nutrient transport; and the evolution and biodiversity of organisms. In addition, surface elevations are a proxy for the geodynamic processes that created them. Efforts to quantify paleoelevation have relied on reconstructions of mineralogical and fossil proxies that preserve environmental signals such as surface temperature, moist enthalpy, or surface water isotopic composition that have been observed to systematically vary with elevation. The challenge to estimating paleoelevation from proxies arises because the modern-day elevation dependence of these environmental parameters is not constant and has differed in the past in response to changes in both surface elevation and other climatic forcings, including greenhouse gas and orbital variations. For example, downward mixing of vapor that is isotopically enriched through troposphere warming under greenhouse forcing reduces the isotopic lapse rate. Without considering these factors, paleoelevation estimates for orogenic systems can be in error by hundreds of meters or more. Isotope-enabled climate models provide a tool for separating the climate response to these forcings into elevation and non-elevation components and for identifying the processes that alter the elevation dependence of environmental parameters. Our past and ongoing work has focused on the simulated climate response to surface uplift of the South American Andes, the North American Cordillera, and the Tibetan-Himalyan system during the Cenozoic, and its implication for interpreting proxy records from these regions. This work demonstrates that the climate response to uplift, and the implications for interpreting proxy records, varies tremendously by region. In this presentation, we synthesize climate responses to uplift across orogens, present new results examining the affect of orbital variations on elevation-dependent environmental parameters, and discuss the implications of our work for quantifying paleoelevations.

Effects of changes in climate variability and extremes on the exceedance of critical algal bloom thresholds

NASA Astrophysics Data System (ADS)

Hecht, J. S.; Zia, A.; Beckage, B.; Winter, J.; Schroth, A. W.; Bomblies, A.; Clemins, P. J.; Rizzo, D. M.

2017-12-01

Identifying critical thresholds associated with algal blooms in freshwater lakes is important for avoiding persistent eutrophic conditions and their undesirable ecological, recreational and drinking water impacts. Recent Integrated Assessment Model (IAM) and Bayesian network studies have demonstrated that future climatic changes could increase the duration and intensity of these blooms. Yet, few studies have systematically examined the sensitivity of algal blooms to projected changes in precipitation and temperature variability and extremes at storm-event to seasonal timescales. We employ an IAM, which couples downscaled Global Climate Model (GCM) output with hydrologic and water quality models, to examine the sensitivity of algal blooms in Lake Champlain's shallow Missisquoi Bay to potential future climate changes. We first identify a set of statistically downscaled GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) that reproduce recent historical daily temperature and precipitation observations well in the Lake Champlain basin. Then, we identify plausible covarying changes in the (i) mean and variance of seasonal precipitation and temperature distributions and (ii) frequency and magnitude of individual storm events. We assess the response of water quality indicators (e.g. chlorophyll a concentrations, Trophic State Index) and societal impacts to sequences of daily meteorological series generated from distributions that account for these covarying changes. We also discuss strategies for examining the sensitivity of bloom impacts to different weather sequences generated from a single set of precipitation and temperature distributions with a limited number of computationally intensive IAM simulations. We then evaluate the implications of modeling these changes in climate variability and extreme precipitation events for nutrient management. Finally, we consider the generalizability of our findings for water bodies with different physical and climatic characteristics and address the extent to which climate-driven alterations to terrestrial hydrologic processes, such as evapotranspiration and soil moisture storage, mediate changes to lake water quality.

10-year record of atmospheric composition in the high Himalayas: source, transport and impact

NASA Astrophysics Data System (ADS)

Bonasoni, Paolo; Laj, Paolo; Marinoni, Angela; Cristofanelli, Paolo; Maione, Michela; Putero, Davide; Calzolari, Francescopiero; Decesari, Stefano; Facchini, Maria Cristina; Fuzzi, Sandro; Gobbi, Gianpaolo; Sellegri, Karine; Verza, Gianpietro; Vuillermoz, Elisa; Arduini, Jgor

2016-04-01

South Asia represents a global "hot-spot" for air-quality and climate impacts. Since the end of the 20th Century, field experiments and satellite observations identified a thick layer of atmospheric pollutants extending from the Indian Ocean up to the atmosphere of the Himalayas. Since large amount of short-lived climate pollutants (SLCPs) - like atmospheric aerosol (in particular, the light-absorbing aerosol) and ozone - characterize this region, severe implications were recognized for population health, ecosystem integrity as well as regional climate impacts, especially for what concerns hydrological cycle, monsoon regimes and cryosphere. Since 2006, the Nepal Climate Observatory - Pyramid (NCO-P, 27.95N, 86.82 E, 5079 m a.s.l.), a global station of the WMO/GAW programme has been active in the eastern Nepal Himalaya, not far from the Mt. Everest. NCO-P is located away from large direct anthropogenic pollution sources. The closest major urban area is Kathmandu (200 km south-west from the measurement site). As being located along the Khumbu valley, the observations are representative of synoptic-scale and mountain thermal circulation, providing direct information about the vertical transport of pollutants/climate-altering compounds to the Himalayas and to the free troposphere. In the framework of international programmes (GAW/WMO, UNEP-ABC, AERONET) the following continuous measurement programmes have been carried out at NCO-P: surface ozone, aerosol size distribution (from 10 nm to 25 micron), total particle number, aerosol scattering and absorption coefficients, equivalent BC, PM1-PM10, AOD by sun-photometry, global solar radiation (SW and LW), meteorology. Long-term sampling programmes for the off-line determination of halogenated gases and aerosol chemistry have been also activated. The atmospheric observation records at NCO-P, now representing the longest time series available for the high Himalayas, provided the first direct evidences about the systematic occurrence of pollution transport and high rate of new particle formation events in this region. Here we provide an overview of the main scientific results obtained during these ten years of research. In particular, we will discuss the impact of atmospheric transport and monsoon variability on atmospheric composition by disentangling the role played by mountain breeze system and synoptic-scale transport. We will provide specific information about the role of stratospheric intrusions, long-range mineral dust transport and open biomass burning emissions in determining the variability of ozone, aerosol and equivalent black carbon concentrations. The effect of particle nucleation processes on aerosol number concentrations will be shown. Finally, we discuss the climatic impact of aerosols observed at NCO-P both in terms of direct atmospheric radiative forcing and black carbon deposition on Himalayan snow.

Model-data integration to improve the LPJmL dynamic global vegetation model

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno

2017-04-01

Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the simulated ecosystem dynamics which consequently changed the development of ecosystem carbon stocks and fluxes under future climate and CO2 change. In summary, our results demonstrate challenges and the potential of using model-data integration approaches to improve a dynamic global vegetation model.

Climate Observing Systems: Where are we and where do we need to be in the future

NASA Astrophysics Data System (ADS)

Baker, B.; Diamond, H. J.

2017-12-01

Climate research and monitoring requires an observational strategy that blends long-term, carefully calibrated measurements as well as short-term, focused process studies. The operation and implementation of operational climate observing networks and the provision of related climate services, both have a significant role to play in assisting the development of national climate adaptation policies and in facilitating national economic development. Climate observing systems will require a strong research element for a long time to come. This requires improved observations of the state variables and the ability to set them in a coherent physical (as well as a chemical and biological) framework with models. Climate research and monitoring requires an integrated strategy of land/ocean/atmosphere observations, including both in situ and remote sensing platforms, and modeling and analysis. It is clear that we still need more research and analysis on climate processes, sampling strategies, and processing algorithms.

Untangling the Impacts of Climate Change on Waterborne Diseases: a Systematic Review of Relationships between Diarrheal Diseases and Temperature, Rainfall, Flooding, and Drought.

PubMed

Levy, Karen; Woster, Andrew P; Goldstein, Rebecca S; Carlton, Elizabeth J

2016-05-17

Global climate change is expected to affect waterborne enteric diseases, yet to date there has been no comprehensive, systematic review of the epidemiological literature examining the relationship between meteorological conditions and diarrheal diseases. We searched PubMed, Embase, Web of Science, and the Cochrane Collection for studies describing the relationship between diarrheal diseases and four meteorological conditions that are expected to increase with climate change: ambient temperature, heavy rainfall, drought, and flooding. We synthesized key areas of agreement and evaluated the biological plausibility of these findings, drawing from a diverse, multidisciplinary evidence base. We identified 141 articles that met our inclusion criteria. Key areas of agreement include a positive association between ambient temperature and diarrheal diseases, with the exception of viral diarrhea and an increase in diarrheal disease following heavy rainfall and flooding events. Insufficient evidence was available to evaluate the effects of drought on diarrhea. There is evidence to support the biological plausibility of these associations, but publication bias is an ongoing concern. Future research evaluating whether interventions, such as improved water and sanitation access, modify risk would further our understanding of the potential impacts of climate change on diarrheal diseases and aid in the prioritization of adaptation measures.

Recent Observations of Increased Thinning of the Greenland Ice Sheet Measured by Aircraft GPS and Laser Altimetry

NASA Technical Reports Server (NTRS)

Krabill, William B.

2004-01-01

The Arctic Ice Mapping group (Project AIM) at the NASA Goddard Space Flight Center Wallops Flight Facility has been conducting systematic topographic surveys of the Greenland Ice Sheet (GIs) since 1993, using scanning airborne laser altimeters combined with Global Positioning System (GPS) technology onboard NASA's P-3 aircraft. Flight lines have covered all major ice drainage basins, with repeating surveys after a 5-year interval during the decade of the 90's. Analysis of this data documented significant thinning in many areas near the ice sheet margins and an overall negative mass balance of the GIS (Science, 2000). In 2001, 2002, and 2003 many of these flight lines were re-surveyed, providing evidence of continued or accelerated thinning in all observed areas around the margin of the GIs. Additionally, however, a highly-anomalous snowfall was observed between 2002 and 2003 in SE Greenland - perhaps an indicator of a shift in the regional climate?

Evaluation of hydrological cycle in the major European midlatitude river basins in the frame of the CORDEX project

NASA Astrophysics Data System (ADS)

Georgievski, Goran; Keuler, Klaus

2013-04-01

Water supply and its potential to increase social, economic and environmental risks are among the most critical challenges for the upcoming decades. Therefore, the assessment of the reliability of regional climate models (RCMs) to represent present-day hydrological balance of river basins is one of the most challenging tasks with high priority for climate modelling in order to estimate range of possible socio-economic impacts of the climate change. However, previous work in the frame of 4th IPCC AR and corresponding regional downscaling experiments (with focus on Europe and Danube river basin) showed that even the meteorological re-analyses provide unreliable data set for evaluations of climate model performance. Furthermore, large discrepancies among the RCMs are caused by internal model deficiencies (for example: systematic errors in dynamics, land-soil parameterizations, large-scale condensation and convection schemes), and in spite of higher resolution RCMs do not always improve much the results from GCMs, but even deteriorate it in some cases. All that has a consequence that capturing impact of climate change on hydrological cycle is not an easy task. Here we present state of the art of RCMs in the frame of the CORDEX project for Europe. First analysis shows again that even the up to date ERA-INTERIM re-analysis is not reliable for evaluation of hydrological cycle in major European midlatitude river basins (Seine, Rhine, Elbe, Oder, Vistula, Danube, Po, Rhone, Garonne and Ebro). Therefore, terrestrial water storage, a quasi observed parameter which is a combination of river discharge (from Global River Discharge Centre data set) and atmospheric moisture fluxes from ERA-INTERIM re-analysis, is used for verification. It shows qualitatively good agreement with COSMO-CLM (CCLM) regional climate simulation (abbreviated CCLM_eval) at 0.11 degrees horizontal resolution forced by ERA-INTERIM re-analysis. Furthermore, intercomparison of terrestrial water storage seasonal cycle averaged in Danube river basin for the ten years (1990-1999) overlapping period between CCLM historical experiment (abbreviated CCLM_hist), its forcing GCM (MPI-ESM-LR, here abbreviated MPI_hist) and CCLM_eval is performed. It reveals that CCLM_hist simulation is in better agreement with quasi observed terrestrial water storage than MPI_hist and CCLM_eval. This result seems promising for the assessment of impact of climate change on hydrological cycle. However, evaluation of the whole ensemble of regional climate downscaling experiments participated in CORDEX-Europe project would provide a more robust estimate.

Participation in the Mars Data Analysis Program: Analysis of cloud forms in Viking and Mariner 9 images

NASA Technical Reports Server (NTRS)

Gierasch, P.; Kahn, R. A.

1985-01-01

The first systematic account of the climate of Mars, based upon observations was produced. Cloud data were used to determine spatially and temporally varying near-surface wind direction, relative wind speed, static stability, and humidity conditions on a global scale. Existing models of meteorological processes were critically reexamined in light of the data, and more stringent constraints were set on global processes. Several discoveries were made, including the large extent and seasonal variability of the Mars equatorial Hadley cell, the failure of high latitude winds to reverse direction in early northern spring, the change in meridional wind component in southern midautum, and the almost constant cloud cover in the northern hemisphere, during spring and summer primarily by condensate clouds and in fall and winter by condensates and dust. The implications of these observations are discussed.

Strategic plant choices can alleviate climate change impacts: A review.

PubMed

Espeland, Erin K; Kettenring, Karin M

2018-09-15

Ecosystem-based adaptation (EbA) uses biodiversity and ecosystem services to reduce climate change impacts to local communities. Because plants can alleviate the abiotic and biotic stresses of climate change, purposeful plant choices could improve adaptation. However, there has been no systematic review of how plants can be applied to alleviate effects of climate change. Here we describe how plants can modify climate change effects by altering biological and physical processes. Plant effects range from increasing soil stabilization to reducing the impact of flooding and storm surges. Given the global scale of plant-related activities such as farming, landscaping, forestry, conservation, and restoration, plants can be selected strategically-i.e., planting and maintaining particular species with desired impacts-to simultaneously restore degraded ecosystems, conserve ecosystem function, and help alleviate effects of climate change. Plants are a tool for EbA that should be more broadly and strategically utilized. Copyright © 2018. Published by Elsevier Ltd.

The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. I - Results of decadal integrations

NASA Technical Reports Server (NTRS)

Phillips, T. J.; Semtner, A. J., Jr.

1984-01-01

Anomalies in ocean surface temperature have been identified as possible causes of variations in the climate of particular seasons or as a source of interannual climatic variability, and attempts have been made to forecast seasonal climate by using ocean temperatures as predictor variables. However, the seasonal atmospheric response to ocean temperature anomalies has not yet been systematically investigated with nonlinear models. The present investigation is concerned with ten-year integrations involving a model of intermediate complexity, the Held-Suarez climate model. The calculations have been performed to investigate the changes in seasonal climate which result from a fixed anomaly imposed on a seasonally varying, global ocean temperature field. Part I of the paper provides a report on the results of these decadal integrations. Attention is given to model properties, the experimental design, and the anomaly experiments.

Teleconnection Paths via Climate Network Direct Link Detection.

PubMed

Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

2015-12-31

Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales.

Wave-optics uncertainty propagation and regression-based bias model in GNSS radio occultation bending angle retrievals

NASA Astrophysics Data System (ADS)

Gorbunov, Michael E.; Kirchengast, Gottfried

2018-01-01

A new reference occultation processing system (rOPS) will include a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval chain with integrated uncertainty propagation. In this paper, we focus on wave-optics bending angle (BA) retrieval in the lower troposphere and introduce (1) an empirically estimated boundary layer bias (BLB) model then employed to reduce the systematic uncertainty of excess phases and bending angles in about the lowest 2 km of the troposphere and (2) the estimation of (residual) systematic uncertainties and their propagation together with random uncertainties from excess phase to bending angle profiles. Our BLB model describes the estimated bias of the excess phase transferred from the estimated bias of the bending angle, for which the model is built, informed by analyzing refractivity fluctuation statistics shown to induce such biases. The model is derived from regression analysis using a large ensemble of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) RO observations and concurrent European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields. It is formulated in terms of predictors and adaptive functions (powers and cross products of predictors), where we use six main predictors derived from observations: impact altitude, latitude, bending angle and its standard deviation, canonical transform (CT) amplitude, and its fluctuation index. Based on an ensemble of test days, independent of the days of data used for the regression analysis to establish the BLB model, we find the model very effective for bias reduction and capable of reducing bending angle and corresponding refractivity biases by about a factor of 5. The estimated residual systematic uncertainty, after the BLB profile subtraction, is lower bounded by the uncertainty from the (indirect) use of ECMWF analysis fields but is significantly lower than the systematic uncertainty without BLB correction. The systematic and random uncertainties are propagated from excess phase to bending angle profiles, using a perturbation approach and the wave-optical method recently introduced by Gorbunov and Kirchengast (2015), starting with estimated excess phase uncertainties. The results are encouraging and this uncertainty propagation approach combined with BLB correction enables a robust reduction and quantification of the uncertainties of excess phases and bending angles in the lower troposphere.

Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as "field" or "global" significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Monthly temperature climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

Abrupt Late Holocene Shift in Atmospheric Circulation Recorded by Mineral Dust in the Siple Dome Ice Core, Antarctica

NASA Astrophysics Data System (ADS)

Koffman, B. G.; Goldstein, S. L.; Kaplan, M. R.; Winckler, G.; Bory, A. J. M.; Biscaye, P.

2015-12-01

Atmospheric dust directly influences Earth's climate by altering the radiative balance and by depositing micronutrients in the surface ocean, affecting global biogeochemical cycling. In addition, mineral dust particles provide observational evidence constraining past atmospheric circulation patterns. Because dust can originate from both local and distant terrestrial sources, knowledge of dust provenance can substantially inform our understanding of past climate history, atmospheric transport pathways, and differences in aerosol characteristics between glacial and interglacial climate states. Dust provenance information from Antarctic ice cores has until now been limited to sites in East Antarctica. Here we present some of the first provenance data from West Antarctica. We use Sr-Nd isotopes to characterize dust extracted from late Holocene ice (~1000-1800 C.E.) from the Siple Dome ice core. The data form a tight array in Sr-Nd isotope space, with 87Sr/86Sr ranging between ~0.7087 and 0.7102, and ɛNd ranging between ~ -7 and -16. This combination is unique for Antarctica, with low Nd and low Sr isotope ratios compared to high-elevation East Antarctic sites, requiring a dust source from ancient (Archean to early Proterozoic) and unweathered continental crust, which mixes with young volcanic material. Both components are likely sourced from Antarctica. We also observe significant, systematic variability in Sr and Nd isotopic signatures through time, reflecting changes in the mixing ratio of these sources, and hypothesize that these changes are driven by shifts in circulation patterns. A large change occurs over about 10 years at ca. 1125 C.E. (ΔɛNd = +3 and Δ87Sr/86Sr = -0.0014). This shift coincides with changes in climate proxies in Southern Hemisphere paleoclimate records reflecting variability in the Westerlies. We therefore interpret the shift in dust provenance at Siple Dome to be related to larger-scale circulation changes. In general, the observed shifts in the particle source signatures indicate that dust transport pathways to and around the West Antarctic Ice Sheet are highly responsive to perturbations in atmospheric circulation, and can record rapid shifts in provenance.

Dynamic statistical optimization of GNSS radio occultation bending angles: advanced algorithm and performance analysis

NASA Astrophysics Data System (ADS)

Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Norman, R.; Yuan, Y. B.; Fritzer, J.; Schwaerz, M.; Zhang, K.

2015-08-01

We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS)-based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAllenging Minisatellite Payload (CHAMP) and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction of random errors (standard deviations) of optimized bending angles down to about half of their size or more; (2) reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; and (4) realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well-characterized and high-quality atmospheric profiles over the entire stratosphere.

Accounting for observational uncertainties in the evaluation of low latitude turbulent air-sea fluxes simulated in a suite of IPSL model versions

NASA Astrophysics Data System (ADS)

Servonnat, Jerome; Braconnot, Pascale; Gainusa-Bogdan, Alina

2015-04-01

Turbulent momentum and heat (sensible and latent) fluxes at the air-sea interface are key components of the whole energetic of the Earth's climate and their good representation in climate models is of prime importance. In this work, we use the methodology developed by Braconnot & Frankignoul (1993) to perform a Hotelling T2 test on spatio-temporal fields (annual cycles). This statistic provides a quantitative measure accounting for an estimate of the observational uncertainty for the evaluation of low-latitude turbulent air-sea fluxes in a suite of IPSL model versions. The spread within the observational ensemble of turbulent flux data products assembled by Gainusa-Bogdan et al (submitted) is used as an estimate of the observational uncertainty for the different turbulent fluxes. The methodology holds on a selection of a small number of dominating variability patterns (EOFs) that are common to both the model and the observations for the comparison. Consequently it focuses on the large-scale variability patterns and avoids the possibly noisy smaller scales. The results show that different versions of the IPSL couple model share common large scale model biases, but also that there the skill on sea surface temperature is not necessarily directly related to the skill in the representation of the different turbulent fluxes. Despite the large error bars on the observations the test clearly distinguish the different merits of the different model version. The analyses of the common EOF patterns and related time series provide guidance on the major differences with the observations. This work is a first attempt to use such statistic on the evaluation of the spatio-temporal variability of the turbulent fluxes, accounting for an observational uncertainty, and represents an efficient tool for systematic evaluation of simulated air-seafluxes, considering both the fluxes and the related atmospheric variables. References Braconnot, P., and C. Frankignoul (1993), Testing Model Simulations of the Thermocline Depth Variability in the Tropical Atlantic from 1982 through 1984, J. Phys. Oceanogr., 23(4), 626-647 Gainusa-Bogdan A., Braconnot P. and Servonnat J. (submitted), Using an ensemble data set of turbulent air-sea fluxes to evaluate the IPSL climate model in tropical regions, Journal of Geophysical Research Atmosphere, 2014JD022985

Systematic land climate and evapotranspiration biases in CMIP5 simulations.

PubMed

Mueller, B; Seneviratne, S I

2014-01-16

[1] Land climate is important for human population since it affects inhabited areas. Here we evaluate the realism of simulated evapotranspiration (ET), precipitation, and temperature in the CMIP5 multimodel ensemble on continental areas. For ET, a newly compiled synthesis data set prepared within the Global Energy and Water Cycle Experiment-sponsored LandFlux-EVAL project is used. The results reveal systematic ET biases in the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations, with an overestimation in most regions, especially in Europe, Africa, China, Australia, Western North America, and part of the Amazon region. The global average overestimation amounts to 0.17 mm/d. This bias is more pronounced than in the previous CMIP3 ensemble (overestimation of 0.09 mm/d). Consistent with the ET overestimation, precipitation is also overestimated relative to existing reference data sets. We suggest that the identified biases in ET can explain respective systematic biases in temperature in many of the considered regions. The biases additionally display a seasonal dependence and are generally of opposite sign (ET underestimation and temperature overestimation) in boreal summer (June-August).

Benchmarking sensitivity of biophysical processes to leaf area changes in land surface models

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Duveiller, Gregory; Georgievski, Goran; Li, Wei; Robestson, Eddy; Kautz, Markus; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

2017-04-01

Land surface models (LSM) are widely applied as supporting tools for policy-relevant assessment of climate change and its impact on terrestrial ecosystems, yet knowledge of their performance skills in representing the sensitivity of biophysical processes to changes in vegetation density is still limited. This is particularly relevant in light of the substantial impacts on regional climate associated with the changes in leaf area index (LAI) following the observed global greening. Benchmarking LSMs on the sensitivity of the simulated processes to vegetation density is essential to reduce their uncertainty and improve the representation of these effects. Here we present a novel benchmark system to assess model capacity in reproducing land surface-atmosphere energy exchanges modulated by vegetation density. Through a collaborative effort of different modeling groups, a consistent set of land surface energy fluxes and LAI dynamics has been generated from multiple LSMs, including JSBACH, JULES, ORCHIDEE, CLM4.5 and LPJ-GUESS. Relationships of interannual variations of modeled surface fluxes to LAI changes have been analyzed at global scale across different climatological gradients and compared with satellite-based products. A set of scoring metrics has been used to assess the overall model performances and a detailed analysis in the climate space has been provided to diagnose possible model errors associated to background conditions. Results have enabled us to identify model-specific strengths and deficiencies. An overall best performing model does not emerge from the analyses. However, the comparison with other models that work better under certain metrics and conditions indicates that improvements are expected to be potentially achievable. A general amplification of the biophysical processes mediated by vegetation is found across the different land surface schemes. Grasslands are characterized by an underestimated year-to-year variability of LAI in cold climates, ultimately affecting the amount of absorbed radiation. In addition patterns of simulated turbulent fluxes appear opposite to observations. Such systematic errors shed light on the current partial understanding of some of the mechanisms controlling the surface energy balance. In contrast forests appear reasonably well represented with respect to the interactions between LAI and turbulent fluxes across most climatological gradients, while for net radiation this is only true for warm climates. These proven strengths increase the confidence on how certain processes are simulated in LSMs. The model capacity to mimic the vegetation-biophysics interplay has been tested over the real scenario of greening that occurred in the last 30 years. We found that the modeled trends in surface heat fluxes associated with the long-term changes in leaf area could vary largely from those observed, with different discrepancies across models and climate zones. Our findings help to identify knowledge gaps and improve model representation of the sensitivity of biophysical processes to changes in leaf area density. In particular, comparing models and observations over a wide range of climate and vegetation conditions, as analyzed here, allowed capturing non-linearity of system responses that may emerge more frequently in future climate scenarios.

CMIP5 land surface models systematically underestimate inter-annual variability of net ecosystem exchange in semi-arid southwestern North America.

NASA Astrophysics Data System (ADS)

MacBean, N.; Scott, R. L.; Biederman, J. A.; Vuichard, N.; Hudson, A.; Barnes, M.; Fox, A. M.; Smith, W. K.; Peylin, P. P.; Maignan, F.; Moore, D. J.

2017-12-01

Recent studies based on analysis of atmospheric CO2 inversions, satellite data and terrestrial biosphere model simulations have suggested that semi-arid ecosystems play a dominant role in the interannual variability and long-term trend in the global carbon sink. These studies have largely cited the response of vegetation activity to changing moisture availability as the primary mechanism of variability. However, some land surface models (LSMs) used in these studies have performed poorly in comparison to satellite-based observations of vegetation dynamics in semi-arid regions. Further analysis is therefore needed to ensure semi-arid carbon cycle processes are well represented in global scale LSMs before we can fully establish their contribution to the global carbon cycle. In this study, we evaluated annual net ecosystem exchange (NEE) simulated by CMIP5 land surface models using observations from 20 Ameriflux sites across semi-arid southwestern North America. We found that CMIP5 models systematically underestimate the magnitude and sign of NEE inter-annual variability; therefore, the true role of semi-arid regions in the global carbon cycle may be even more important than previously thought. To diagnose the factors responsible for this bias, we used the ORCHIDEE LSM to test different climate forcing data, prescribed vegetation fractions and model structures. Climate and prescribed vegetation do contribute to uncertainty in annual NEE simulations, but the bias is primarily caused by incorrect timing and magnitude of peak gross carbon fluxes. Modifications to the hydrology scheme improved simulations of soil moisture in comparison to data. This in turn improved the seasonal cycle of carbon uptake due to a more realistic limitation on photosynthesis during water stress. However, the peak fluxes are still too low, and phenology is poorly represented for desert shrubs and grasses. We provide suggestions on model developments needed to tackle these issues in the future.

Thermal alteration of soil organic matter properties: a systematic study to infer response of Sierra Nevada climosequence soils to forest fires

NASA Astrophysics Data System (ADS)

Araya, Samuel N.; Fogel, Marilyn L.; Asefaw Berhe, Asmeret

2017-02-01

Fire is a major driver of soil organic matter (SOM) dynamics, and contemporary global climate change is changing global fire regimes. We conducted laboratory heating experiments on soils from five locations across the western Sierra Nevada climosequence to investigate thermal alteration of SOM properties and determine temperature thresholds for major shifts in SOM properties. Topsoils (0 to 5 cm depth) were exposed to a range of temperatures that are expected during prescribed and wild fires (150, 250, 350, 450, 550, and 650 °C). With increase in temperature, we found that the concentrations of carbon (C) and nitrogen (N) decreased in a similar pattern among all five soils that varied considerably in their original SOM concentrations and mineralogies. Soils were separated into discrete size classes by dry sieving. The C and N concentrations in the larger aggregate size fractions (2-0.25 mm) decreased with an increase in temperature, so that at 450 °C the remaining C and N were almost entirely associated with the smaller aggregate size fractions ( < 0.25 mm). We observed a general trend of 13C enrichment with temperature increase. There was also 15N enrichment with temperature increase, followed by 15N depletion when temperature increased beyond 350 °C. For all the measured variables, the largest physical, chemical, elemental, and isotopic changes occurred at the mid-intensity fire temperatures, i.e., 350 and 450 °C. The magnitude of the observed changes in SOM composition and distribution in three aggregate size classes, as well as the temperature thresholds for critical changes in physical and chemical properties of soils (such as specific surface area, pH, cation exchange capacity), suggest that transformation and loss of SOM are the principal responses in heated soils. Findings from this systematic investigation of soil and SOM response to heating are critical for predicting how soils are likely to be affected by future climate and fire regimes.

Impacts of nitrogen addition on plant biodiversity in mountain grasslands depend on dose, application duration and climate: a systematic review.

PubMed

Humbert, Jean-Yves; Dwyer, John M; Andrey, Aline; Arlettaz, Raphaël

2016-01-01

Although the influence of nitrogen (N) addition on grassland plant communities has been widely studied, it is still unclear whether observed patterns and underlying mechanisms are constant across biomes. In this systematic review, we use meta-analysis and metaregression to investigate the influence of N addition (here referring mostly to fertilization) upon the biodiversity of temperate mountain grasslands (including montane, subalpine and alpine zones). Forty-two studies met our criteria of inclusion, resulting in 134 measures of effect size. The main general responses of mountain grasslands to N addition were increases in phytomass and reductions in plant species richness, as observed in lowland grasslands. More specifically, the analysis reveals that negative effects on species richness were exacerbated by dose (ha(-1) year(-1) ) and duration of N application (years) in an additive manner. Thus, sustained application of low to moderate levels of N over time had effects similar to short-term application of high N doses. The climatic context also played an important role: the overall effects of N addition on plant species richness and diversity (Shannon index) were less pronounced in mountain grasslands experiencing cool rather than warm summers. Furthermore, the relative negative effect of N addition on species richness was more pronounced in managed communities and was strongly negatively related to N-induced increases in phytomass, that is the greater the phytomass response to N addition, the greater the decline in richness. Altogether, this review not only establishes that plant biodiversity of mountain grasslands is negatively affected by N addition, but also demonstrates that several local management and abiotic factors interact with N addition to drive plant community changes. This synthesis yields essential information for a more sustainable management of mountain grasslands, emphasizing the importance of preserving and restoring grasslands with both low agricultural N application and limited exposure to N atmospheric deposition. © 2015 John Wiley & Sons Ltd.

An Algorithm to Generate Deep-Layer Temperatures from Microwave Satellite Observations for the Purpose of Monitoring Climate Change. Revised

NASA Technical Reports Server (NTRS)

Goldberg, Mitchell D.; Fleming, Henry E.

1994-01-01

An algorithm for generating deep-layer mean temperatures from satellite-observed microwave observations is presented. Unlike traditional temperature retrieval methods, this algorithm does not require a first guess temperature of the ambient atmosphere. By eliminating the first guess a potentially systematic source of error has been removed. The algorithm is expected to yield long-term records that are suitable for detecting small changes in climate. The atmospheric contribution to the deep-layer mean temperature is given by the averaging kernel. The algorithm computes the coefficients that will best approximate a desired averaging kernel from a linear combination of the satellite radiometer's weighting functions. The coefficients are then applied to the measurements to yield the deep-layer mean temperature. Three constraints were used in deriving the algorithm: (1) the sum of the coefficients must be one, (2) the noise of the product is minimized, and (3) the shape of the approximated averaging kernel is well-behaved. Note that a trade-off between constraints 2 and 3 is unavoidable. The algorithm can also be used to combine measurements from a future sensor (i.e., the 20-channel Advanced Microwave Sounding Unit (AMSU)) to yield the same averaging kernel as that based on an earlier sensor (i.e., the 4-channel Microwave Sounding Unit (MSU)). This will allow a time series of deep-layer mean temperatures based on MSU measurements to be continued with AMSU measurements. The AMSU is expected to replace the MSU in 1996.

Predictors and Outcomes of Mealtime Emotional Climate in Families With Preschoolers.

PubMed

Saltzman, Jaclyn A; Bost, Kelly K; Musaad, Salma M A; Fiese, Barbara H; Wiley, Angela R

2018-03-01

Mealtime emotional climate (MEC) is related to parent feeding and mental health, and possibly to child food consumption. However, MEC has been inconsistently assessed with a variety of coding schemes and self-report instruments, and has not been examined longitudinally. This study aims to characterize MEC systematically using an observational, count-based coding scheme; identify whether parent feeding or mental health predict MEC; and examine whether MEC predicts child food consumption and weight. A subsample of parents (n = 74) recruited from a larger study completed questionnaires when children were about 37 months, participated in a home visit to videotape a mealtime when children were about 41 months, and completed questionnaires again when children were about 51 months old. Maternal and child positive and negative emotions were coded from videotaped mealtimes. Observational data were submitted to cluster analyses, to identify dyads with similar emotion expression patterns, or MEC. Logistic regression was used to identify predictors of MEC, and Analysis of Covariance was used to examine differences between MEC groups. Dyads were characterized as either Positive Expressers (high positive, low negative emotion) or All Expressers (similar positive and negative emotion). Increased food involvement feeding practices were related to decreased likelihood of being an All Expresser. Positive Expressers reported that their children ate more healthy food, compared with All Expressers. Observed MEC is driven by maternal emotion, and may predict child food consumption. Food involvement may promote positive MEC. Improving MEC may increase child consumption of healthy foods.

Patterns and biases in climate change research on amphibians and reptiles: a systematic review.

PubMed

Winter, Maiken; Fiedler, Wolfgang; Hochachka, Wesley M; Koehncke, Arnulf; Meiri, Shai; De la Riva, Ignacio

2016-09-01

Climate change probably has severe impacts on animal populations, but demonstrating a causal link can be difficult because of potential influences by additional factors. Assessing global impacts of climate change effects may also be hampered by narrow taxonomic and geographical research foci. We review studies on the effects of climate change on populations of amphibians and reptiles to assess climate change effects and potential biases associated with the body of work that has been conducted within the last decade. We use data from 104 studies regarding the effect of climate on 313 species, from 464 species-study combinations. Climate change effects were reported in 65% of studies. Climate change was identified as causing population declines or range restrictions in half of the cases. The probability of identifying an effect of climate change varied among regions, taxa and research methods. Climatic effects were equally prevalent in studies exclusively investigating climate factors (more than 50% of studies) and in studies including additional factors, thus bolstering confidence in the results of studies exclusively examining effects of climate change. Our analyses reveal biases with respect to geography, taxonomy and research question, making global conclusions impossible. Additional research should focus on under-represented regions, taxa and questions. Conservation and climate policy should consider the documented harm climate change causes reptiles and amphibians.

Global Warming Denial: The Human Brain on Extremes

NASA Astrophysics Data System (ADS)

Marrouch, N.; Johnson, B. T.; Slawinska, J. M.

2016-12-01

Future assessments of climate change rely on multi-model intercomparisons, and projections of the extreme events frequency are of particular interest as associated with significant economic costs and social threats. Notably, systematically simulated increases in the number of extreme weather events agree well with observational data over the last decade. At the same time, as the climate grows more volatile, widespread denial of climate change and its anthropocentric causes continues to proliferate (based on nationally representative U.S. polls). Simultaneous increases in both high-impact exposure and its denial is in stark contrast with our knowledge of socio-natural dynamics and its models. Disentangling this paradox requires an understanding of the origins of global warming denial at an individual level, and how subsequently it propagates across social networks of many scales, shaping global policies. However, as the real world and its dynamical models are complex (high-dimensional and coupled), separating the particular feedback of interest remains a challenge. Here, we demonstrate this feedback in a controlled experiment, where increasing unpredictability using helplessness-training paradigms induces changes in global warming denial, and the endorsement of conservative ideology. We explain these results in the context of evolutionary theory framing self-deception and denial as remnants of evolutionary processes that shaped and facilitated the survival of the human species. Further we link these findings to changes in neural and higher-level cognitive processes in response to unpredictable stimuli. We argue that climate change denial is an example of an extreme belief system that carries the potential to threaten the wellbeing of both humans and other species alike. It is therefore crucial to better quantify climate denial using social informatics tools that provide the means to improve its representations in coupled socio-geophysical models to mitigate its effects on global and local policies.

Herbarium specimens can reveal impacts of climate change on plant phenology; a review of methods and applications.

PubMed

Jones, Casey A; Daehler, Curtis C

2018-01-01

Studies in plant phenology have provided some of the best evidence for large-scale responses to recent climate change. Over the last decade, more than thirty studies have used herbarium specimens to analyze changes in flowering phenology over time, although studies from tropical environments are thus far generally lacking. In this review, we summarize the approaches and applications used to date. Reproductive plant phenology has primarily been analyzed using two summary statistics, the mean flowering day of year and first-flowering day of year, but mean flowering day has proven to be a more robust statistic. Two types of regression models have been applied to test for associations between flowering, temperature and time: flowering day regressed on year and flowering day regressed on temperature. Most studies analyzed the effect of temperature by averaging temperatures from three months prior to the date of flowering. On average, published studies have used 55 herbarium specimens per species to characterize changes in phenology over time, but in many cases fewer specimens were used. Geospatial grid data are increasingly being used for determining average temperatures at herbarium specimen collection locations, allowing testing for finer scale correspondence between phenology and climate. Multiple studies have shown that inferences from herbarium specimen data are comparable to findings from systematically collected field observations. Understanding phenological responses to climate change is a crucial step towards recognizing implications for higher trophic levels and large-scale ecosystem processes. As herbaria are increasingly being digitized worldwide, more data are becoming available for future studies. As temperatures continue to rise globally, herbarium specimens are expected to become an increasingly important resource for analyzing plant responses to climate change.

Multi-objective optimization for generating a weighted multi-model ensemble

NASA Astrophysics Data System (ADS)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic ensemble mean and may provide reliable future projections.

Error assessment of biogeochemical models by lower bound methods (NOMMA-1.0)

NASA Astrophysics Data System (ADS)

Sauerland, Volkmar; Löptien, Ulrike; Leonhard, Claudine; Oschlies, Andreas; Srivastav, Anand

2018-03-01

Biogeochemical models, capturing the major feedbacks of the pelagic ecosystem of the world ocean, are today often embedded into Earth system models which are increasingly used for decision making regarding climate policies. These models contain poorly constrained parameters (e.g., maximum phytoplankton growth rate), which are typically adjusted until the model shows reasonable behavior. Systematic approaches determine these parameters by minimizing the misfit between the model and observational data. In most common model approaches, however, the underlying functions mimicking the biogeochemical processes are nonlinear and non-convex. Thus, systematic optimization algorithms are likely to get trapped in local minima and might lead to non-optimal results. To judge the quality of an obtained parameter estimate, we propose determining a preferably large lower bound for the global optimum that is relatively easy to obtain and that will help to assess the quality of an optimum, generated by an optimization algorithm. Due to the unavoidable noise component in all observations, such a lower bound is typically larger than zero. We suggest deriving such lower bounds based on typical properties of biogeochemical models (e.g., a limited number of extremes and a bounded time derivative). We illustrate the applicability of the method with two real-world examples. The first example uses real-world observations of the Baltic Sea in a box model setup. The second example considers a three-dimensional coupled ocean circulation model in combination with satellite chlorophyll a.

Mind the gap in SEA: An institutional perspective on why assessment of synergies amongst climate change mitigation, adaptation and other policy areas are missing

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

Vammen Larsen, Sanne, E-mail: sannevl@plan.aau.dk; Kornov, Lone, E-mail: lonek@plan.aau.dk; Wejs, Anja, E-mail: wejs@plan.aau.dk

2012-02-15

This article takes its point of departure in two approaches to integrating climate change into Strategic Environmental Assessment (SEA): Mitigation and adaptation, and in the fact that these, as well as the synergies between them and other policy areas, are needed as part of an integrated assessment and policy response. First, the article makes a review of how positive and negative synergies between a) climate change mitigation and adaptation and b) climate change and other environmental concerns are integrated into Danish SEA practice. Then, the article discusses the implications of not addressing synergies. Finally, the article explores institutional explanations asmore » to why synergies are not addressed in SEA practice. A document analysis of 149 Danish SEA reports shows that only one report comprises the assessment of synergies between mitigation and adaptation, whilst 9,4% of the reports assess the synergies between climate change and other environmental concerns. The consequences of separation are both the risk of trade-offs and missed opportunities for enhancing positive synergies. In order to propose explanations for the lacking integration, the institutional background is analysed and discussed, mainly based on Scott's theory of institutions. The institutional analysis highlights a regulatory element, since the assessment of climate change synergies is underpinned by legislation, but not by guidance. This means that great focus is on normative elements such as the local interpretation of legislation and of climate change mitigation and adaptation. The analysis also focuses on how the fragmentation of the organisation in which climate change and SEA are embedded has bearings on both normative and cultural-cognitive elements. This makes the assessment of synergies challenging. The evidence gathered and presented in the article points to a need for developing the SEA process and methodology in Denmark with the aim to include climate change in the assessments in a more systematic and integrated manner. - Highlights: Black-Right-Pointing-Pointer Synergies between climate change mitigation, adaptation and other environmental concerns are not addressed in Danish SEA. Black-Right-Pointing-Pointer Institutional explanations relate to organisational set-ups and understandings of climate change as a new planning issue. Black-Right-Pointing-Pointer The paper points to a need for developing SEA to include climate change in a more systematic and integrated manner.« less

Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations

NASA Astrophysics Data System (ADS)

Lindsay, R.; Schweiger, A.

2014-08-01

Sea ice thickness is a fundamental climate state variable that provides an integrated measure of changes in the high-latitude energy balance. However, observations of ice thickness have been sparse in time and space making the construction of observation-based time series difficult. Moreover, different groups use a variety of methods and processing procedures to measure ice thickness and each observational source likely has different and poorly characterized measurement and sampling biases. Observational sources include upward looking sonars mounted on submarines or moorings, electromagnetic sensors on helicopters or aircraft, and lidar or radar altimeters on airplanes or satellites. Here we use a curve-fitting approach to evaluate the systematic differences between eight different observation systems in the Arctic Basin. The approach determines the large-scale spatial and temporal variability of the ice thickness as well as the mean differences between the observation systems using over 3000 estimates of the ice thickness. The thickness estimates are measured over spatial scales of approximately 50 km or time scales of 1 month and the primary time period analyzed is 2000-2013 when the modern mix of observations is available. Good agreement is found between five of the systems, within 0.15 m, while systematic differences of up to 0.5 m are found for three others compared to the five. The trend in annual mean ice thickness over the Arctic Basin is -0.58 ± 0.07 m decade-1 over the period 2000-2013, while the annual mean ice thickness for the central Arctic Basin alone (the SCICEX Box) has decreased from 3.45 m in 1975 to 1.11 m in 2013, a 68% reduction. This is nearly double the 36% decline reported by an earlier study. These results provide additional direct observational confirmation of substantial sea ice losses found in model analyses.

Information and communication technology and climate change adaptation: Evidence from selected mining companies in South Africa

PubMed Central

Nhamo, Godwell

2016-01-01

The mining sector is a significant contributor to the gross domestic product of many global economies. Given the increasing trends in climate-induced disasters and the growing desire to find lasting solutions, information and communication technology (ICT) has been introduced into the climate change adaptation mix. Climate change-induced extreme weather events such as flooding, drought, excessive fog, and cyclones have compounded the environmental challenges faced by the mining sector. This article presents the adoption of ICT innovation as part of the adaptation strategies towards reducing the mining sector’s vulnerability and exposure to climate change disaster risks. Document analysis and systematic literature review were adopted as the methodology. Findings from the study reflect how ICT intervention orchestrated changes in communication patterns which are tailored towards the reduction in climate change vulnerability and exposure. The research concludes with a proposition that ICT intervention must be part of the bigger and ongoing climate change adaptation agenda in the mining sector.

Chemical weathering as a mechanism for the climatic control of bedrock river incision

NASA Astrophysics Data System (ADS)

Murphy, Brendan P.; Johnson, Joel P. L.; Gasparini, Nicole M.; Sklar, Leonard S.

2016-04-01

Feedbacks between climate, erosion and tectonics influence the rates of chemical weathering reactions, which can consume atmospheric CO2 and modulate global climate. However, quantitative predictions for the coupling of these feedbacks are limited because the specific mechanisms by which climate controls erosion are poorly understood. Here we show that climate-dependent chemical weathering controls the erodibility of bedrock-floored rivers across a rainfall gradient on the Big Island of Hawai‘i. Field data demonstrate that the physical strength of bedrock in streambeds varies with the degree of chemical weathering, which increases systematically with local rainfall rate. We find that incorporating the quantified relationships between local rainfall and erodibility into a commonly used river incision model is necessary to predict the rates and patterns of downcutting of these rivers. In contrast to using only precipitation-dependent river discharge to explain the climatic control of bedrock river incision, the mechanism of chemical weathering can explain strong coupling between local climate and river incision.

Integrating fossils, phylogenies, and niche models into biogeography to reveal ancient evolutionary history: the case of Hypericum (hypericaceae).

PubMed

Meseguer, Andrea S; Lobo, Jorge M; Ree, Richard; Beerling, David J; Sanmartín, Isabel

2015-03-01

In disciplines such as macroevolution that are not amenable to experimentation, scientists usually rely on current observations to test hypotheses about historical events, assuming that "the present is the key to the past." Biogeographers, for example, used this assumption to reconstruct ancestral ranges from the distribution of extant species. Yet, under scenarios of high extinction rates, the biodiversity we observe today might not be representative of the historical diversity and this could result in incorrect biogeographic reconstructions. Here, we introduce a new approach to incorporate into biogeographic inference the temporal, spatial, and environmental information provided by the fossil record, as a direct evidence of the extinct biodiversity fraction. First, inferences of ancestral ranges for those nodes in the phylogeny calibrated with the fossil record are constrained to include the geographic distribution of the fossil. Second, we use fossil distribution and past climate data to reconstruct the climatic preferences and potential distribution of ancestral lineages over time, and use this information to build a biogeographic model that takes into account "ecological connectivity" through time. To show the power of this approach, we reconstruct the biogeographic history of the large angiosperm genus Hypericum, which has a fossil record extending back to the Early Cenozoic. Unlike previous reconstructions based on extant species distributions, our results reveal that Hypericum stem lineages were already distributed in the Holarctic before diversification of its crown-group, and that the geographic distribution of the genus has been relatively stable throughout the climatic oscillations of the Cenozoic. Geographical movement was mediated by the existence of climatic corridors, like Beringia, whereas the equatorial tropical belt acted as a climatic barrier, preventing Hypericum lineages to reach the southern temperate regions. Our study shows that an integrative approach to historical biogeography-that combines sources of evidence as diverse as paleontology, ecology, and phylogenetics-could help us obtain more accurate reconstructions of ancient evolutionary history. It also reveals the confounding effect different rates of extinction across regions have in biogeography, sometimes leading to ancestral areas being erroneously inferred as recent colonization events. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Diffusion impact on atmospheric moisture transport

NASA Astrophysics Data System (ADS)

Moseley, C.; Haerter, J.; Göttel, H.; Hagemann, S.; Jacob, D.

2009-04-01

To ensure numerical stability, many global and regional climate models employ numerical diffusion to dampen short wavelength modes. Terrain following sigma diffusion is known to cause unphysical effects near the surface in orographically structured regions. They can be reduced by applying z-diffusion on geopotential height levels. We investigate the effect of the diffusion scheme on atmospheric moisture transport and precipitation formation at different resolutions in the European region. With respect to a better understanding of diffusion in current and future grid-space global models, current day regional models may serve as the appropriate tool for studies of the impact of diffusion schemes: Results can easily be constrained to a small test region and checked against reliable observations, which often are unavailable on a global scale. Special attention is drawn to the Alps - a region of strong topographic gradients and good observational coverage. Our study is further motivated by the appearance of the "summer drying problem" in South Eastern Europe. This too warm and too dry simulation of climate is common to many regional climate models and also to some global climate models, and remains a permanent unsolved problem in the community. We perform a systematic comparison of the two diffusion-schemes with respect to the hydrological cycle. In particular, we investigate how local meteorological quantities - such as the atmospheric moisture in the region east of the Alps - depend on the spatial model resolution. Higher model resolution would lead to a more accurate representation of the topography and entail larger gradients in the Alps. This could lead to consecutively stronger transport of moisture along the slopes in the case of sigma-diffusion with subsequent orographic precipitation, whereas the effect could be qualitatively different in the case of z-diffusion. For our study, we analyse a sequence of simulations of the regional climate model REMO employing the different diffusion methods over Europe. For these simulations, REMO was forced at the lateral boundaries with ERA40 reanalysis data for a five year period. For our higher resolution simulations we employ the double nesting technique.

Progress on observation of cryospheric components and climate-related studies in China

NASA Astrophysics Data System (ADS)

Xiao, Cunde; Qin, Dahe; Yao, Tandong; Ding, Yongjian; Liu, Shiyin; Zhao, Lin; Liu, Yujie

2008-03-01

Systematic studies on the cryosphere in China started in the late 1950s. Significant achievements have been made by continuous investigation of glacier inventories, frozen ground observations, paleo-climate analyses of ice cores, process studies and the modeling of cryopsheric/atmospheric interactions. The general facts and understanding of these changes include: (1) Solid precipitation, including the number of days with frost and hail storms, shows a decreasing tendency over the past half century. (2) In most areas glaciers are retreating or have completely vanished (>80%), some glaciers are still advancing (5%-20% depending upon time period). The annual glacial melt water has been increasing since the 1980s. This increased supply of melt water to river runoff in Northwest China is about a 10%-13%. (3) The long-term variability of snow cover in western China is characterized by a large inter-annual variation superimposed on a small increasing trend. Snow cover variability in the Qinghai-Xizang Plateau (QXP) is influenced by the Indian monsoon, and conversely impacts monsoon onset and strength and eventually the drought and flood events in middle-low reaches of Yangtze River. (4) Frozen ground, including permafrost, is decaying both in QXP and in Northeast China. The most significant changes occurred in the regions with thickest seasonal frozen ground (SFG), i.e., inland QXP, then northeastern and northwestern QXP. The cold season air temperature is the main factor controlling SFG change. The increase of ground surface temperatures is more significant than air temperature. (5) The sea ice coverage over the Bohai Sea and Yellow Sea has deceased since the 1980s. (6) River ice duration and ice thickness is also decreasing in northern China. In 2001, the Chinese National Committee of World Climate Research Program/Climate and Cyosphere (WCRP/CliC) (CNC-CliC) was organized to strengthen research on climate and cryosphere in China. Future monitoring of the cryosphere in China will be enhanced both in spatial coverage and through the use of new techniques. Interactions between atmosphere/cryosphere/ hydrosphere/land-surface will be assessed to improve our understanding of the mechanisms of cryospheric change.

A Systematic Review of Global Drivers of Ant Elevational Diversity

PubMed Central

Szewczyk, Tim; McCain, Christy M.

2016-01-01

Ant diversity shows a variety of patterns across elevational gradients, though the patterns and drivers have not been evaluated comprehensively. In this systematic review and reanalysis, we use published data on ant elevational diversity to detail the observed patterns and to test the predictions and interactions of four major diversity hypotheses: thermal energy, the mid-domain effect, area, and the elevational climate model. Of sixty-seven published datasets from the literature, only those with standardized, comprehensive sampling were used. Datasets included both local and regional ant diversity and spanned 80° in latitude across six biogeographical provinces. We used a combination of simulations, linear regressions, and non-parametric statistics to test multiple quantitative predictions of each hypothesis. We used an environmentally and geometrically constrained model as well as multiple regression to test their interactions. Ant diversity showed three distinct patterns across elevations: most common were hump-shaped mid-elevation peaks in diversity, followed by low-elevation plateaus and monotonic decreases in the number of ant species. The elevational climate model, which proposes that temperature and precipitation jointly drive diversity, and area were partially supported as independent drivers. Thermal energy and the mid-domain effect were not supported as primary drivers of ant diversity globally. The interaction models supported the influence of multiple drivers, though not a consistent set. In contrast to many vertebrate taxa, global ant elevational diversity patterns appear more complex, with the best environmental model contingent on precipitation levels. Differences in ecology and natural history among taxa may be crucial to the processes influencing broad-scale diversity patterns. PMID:27175999

Monsoon climate response in Indian teak (Tectona grandis L.f.) along a transect from coast to inland

NASA Astrophysics Data System (ADS)

Sengupta, Saikat; Borgaonkar, Hemant; Joy, Reji Mariya; Ram, Somaru

2017-11-01

Indian monsoon (June-September) and post monsoon (October-November) rainfall show a distinct trend from coast to inland primarily due to moisture availability. However, the response of this synoptic-scale variation of rainfall amount to annual ring growth of Indian teak has not been studied systematically yet. The study is important as (1) ring width of Indian teak is considered as a reliable proxy for studying monsoon climate variability in multi-centennial time scale and (2) observed meteorological data show systematic changes in rainfall variation from coast to inland since last three decades. Towards this, we present here tree-ring width data from two locations—Thatibanda (1747-1979) and Nagzira (1728-2000) and use similar published data from two other locations—Allapalli (1866-1897) and Edugurapalli (1827-2000). The locations fall along a southeast northwest transect from south east Indian coast to inland. Monthly mean data from nearest observatories show an increasing trend in monsoon rainfall and a pronounced decreasing trend in post monsoon rainfall towards inland. Ring width data show moderately positive response to monsoon rainfall and negative response to summer (March-May) temperature for all stations suggesting moisture deficit in hot summer and intense precipitation in monsoon affect ring growth pattern in different ways. Ring width indices also exhibit significantly positive response with post monsoon rainfall at coastal location. The response gradually reduces towards inland. This preliminary study, thus, suggests that Indian teak has a potential to capture signals of the synoptic variation of post monsoon rainfall from coast to inland.

Does what you know matter? Investigating the relationship between mental models of climate change and pro-environmental behaviors

NASA Astrophysics Data System (ADS)

Davis, R.

2013-12-01

The purpose of this study is to test the conjecture that environmentally sustainable decisions and behaviors are related to individuals' conceptions of the natural world, in this case climate change; individuals' attitudes towards climate change; and the situations in which these decisions are made. The nature of mental models is an ongoing subject of disagreement. Some argue that mental models are coherent theories, much like scientific theories, that individuals employ systematically when reasoning about the world (Gopnik & Meltzoff, 1998). Others maintain that mental models are cobbled together from fragmented collections of ideas that are only loosely connected and context dependent (Disessa, 1988; Minstrell, 2000). It is likely that individuals sometimes reason about complex phenomena using systematic mental models and at other times reason using knowledge that is organized in fragmented pieces (Steedle & Shavelson, 2009). Thus, in measuring mental models of complex environmental systems, such as climate change, the assumption of systematicity may not be justified. Individuals may apply certain chains of reasoning in some contexts but not in others. The current study hypothesizes that an accurate mental model of climate change enables an individual to make effective evaluative judgments of environmental behavior options. The more an individual's mental model resembles that of an expert, the more consistent, accurate and automatic these judgments become. However, an accurate mental model is not sufficient to change environmental behavior. Real decisions and behaviors are products of a person-situation interaction: an interplay between psychosocial factors (such as knowledge and attitudes) and the situation in which the decision is made. This study investigates the relationship between both psychosocial and situational factors for climate change decisions. Data was collected from 436 adult participants through an online survey. The survey was comprised of demographic questions; three discreet instruments measuring (1) mental models of climate change, (2) attitudes and beliefs about climate change, and (3) self-reported behaviors; and an experimental intervention, followed by a behavioral intention question. Latent class analysis (LCA) and item-response theory (IRT) will be employed to analyze multiple-choice responses to the mental model survey to create groupings of individuals assumed to hold similar mental of climate change. A principal component analysis (PCA) using oblique rotation was employed to identify five scales (Chronbach's alpha > 0.80) within the attitude/belief instrument. Total and sub-scale scores were also calculated for self-reported behaviors. The relationships between mental models, attitudes and behaviors will be analyzed using multiple regression models. This work presents not only the development and validation of three novel instruments for accurately and efficiently measuring mental models, attitudes, and self-reported behaviors, but also provides insight into the types of mental models individuals hold. Understanding how climate change is conceptualized and how such knowledge influences attitudes and behaviors gives educators tools for guiding students towards more expert understandings while also enabling environmentalists to craft more effective messages.

IPCC reasons for concern regarding climate change risks

NASA Astrophysics Data System (ADS)

O'Neill, Brian C.; Oppenheimer, Michael; Warren, Rachel; Hallegatte, Stephane; Kopp, Robert E.; Pörtner, Hans O.; Scholes, Robert; Birkmann, Joern; Foden, Wendy; Licker, Rachel; Mach, Katharine J.; Marbaix, Phillippe; Mastrandrea, Michael D.; Price, Jeff; Takahashi, Kiyoshi; van Ypersele, Jean-Pascal; Yohe, Gary

2017-01-01

The reasons for concern framework communicates scientific understanding about risks in relation to varying levels of climate change. The framework, now a cornerstone of the IPCC assessments, aggregates global risks into five categories as a function of global mean temperature change. We review the framework's conceptual basis and the risk judgments made in the most recent IPCC report, confirming those judgments in most cases in the light of more recent literature and identifying their limitations. We point to extensions of the framework that offer complementary climate change metrics to global mean temperature change and better account for possible changes in social and ecological system vulnerability. Further research should systematically evaluate risks under alternative scenarios of future climatic and societal conditions.

Public Health Adaptation to Climate Change in OECD Countries

PubMed Central

Austin, Stephanie E.; Biesbroek, Robbert; Berrang-Ford, Lea; Ford, James D.; Parker, Stephen; Fleury, Manon D.

2016-01-01

Climate change is a major challenge facing public health. National governments play a key role in public health adaptation to climate change, but there are competing views on what responsibilities and obligations this will—or should—include in different nations. This study aims to: (1) examine how national-level public health adaptation is occurring in Organization for Economic Cooperation and Development (OECD) countries; (2) examine the roles national governments are taking in public health adaptation; and (3) critically appraise three key governance dimensions of national-level health adaptation—cross-sectoral collaboration, vertical coordination and national health adaptation planning—and identify practical examples suited to different contexts. We systematically reviewed publicly available public health adaptation to climate change documents and webpages by national governments in ten OECD countries using systematic web searches, assessment of self-reporting, and content analysis. Our findings suggest national governments are primarily addressing infectious disease and heat-related risks posed by climate change, typically emphasizing capacity building or information-based groundwork initiatives. We find national governments are taking a variety of approaches to public health adaptation to climate change that do not follow expected convergence and divergence by governance structure. We discuss practical options for incorporating cross-sectoral collaboration, vertical coordination and national health adaptation planning into a variety of contexts and identify leaders national governments can look to to inform their public health adaptation planning. Following the adoption of the Paris Agreement and subsequent increased momentum for adaptation, research tracking adaptation is needed to define what health adaptation looks like in practice, reveal insights that can be taken up across states and sectors, and ensure policy orientated learning. PMID:27618074

Mulit Criteria - Application on Climate Change Adaptation and Biofuel Cultivation on Contaminated Land

NASA Astrophysics Data System (ADS)

Andersson-Sköld, Yvonne; Suer, Pascal; Bergman, Ramona; Helgesson, Helena

2010-05-01

A decision support tool/method has been developed to systematically include sustainability at an early stage in planning issues. Sustainability was subdivided into human health, environmental impacts, resources, and social and economic impacts. Health, environmental and resources impacts were based on the Swedish environmental objectives, life cycle assessment (LCA) impact categories, and contaminated soil guidelines. The resulting impact indicators were climate change - global warming potential, large scale and local air quality, water and soil quality, landscape, energy, materials, wellbeing/welfare, direct financial costs, social economic aspects, and flexi-bility. The method offers an iterative discussion framework that is systematic, condensed and yet a simplistic way of describing consequences of climate change and related adaptation measures including economic, social and environmental aspects. Application of the tool to biofuel cultivation on contaminated soil indicated that traditional soil remediation may have higher social and economical benefits but be less suitable from a health, environment, and resources perspective. The tool has further been applied in municipalities on climate change impacts and adaptation measures. Re-sults from the application in tree municipalities will be presented: Gothenburg City, Lidköping and Arvika. In Gothenburg and Lidköping the major impact of climate change is increase in sea water level (North Sea and Lake Vänern respectively) combined with extreme weather conditions. According to regional climate change scenarios Arvika is located in one of the worst affected areas in Sweden with respect to increase of intensive rainfall and extreme flows. The adaptation measures investigated at the three locations include doing nothing, different constructions and planning. The results are based on previous risk identification investigations, flood and land slide maps and interviews with civil servants in the three municipalities.

OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project

NASA Astrophysics Data System (ADS)

Griffies, Stephen M.; Danabasoglu, Gokhan; Durack, Paul J.; Adcroft, Alistair J.; Balaji, V.; Böning, Claus W.; Chassignet, Eric P.; Curchitser, Enrique; Deshayes, Julie; Drange, Helge; Fox-Kemper, Baylor; Gleckler, Peter J.; Gregory, Jonathan M.; Haak, Helmuth; Hallberg, Robert W.; Heimbach, Patrick; Hewitt, Helene T.; Holland, David M.; Ilyina, Tatiana; Jungclaus, Johann H.; Komuro, Yoshiki; Krasting, John P.; Large, William G.; Marsland, Simon J.; Masina, Simona; McDougall, Trevor J.; Nurser, A. J. George; Orr, James C.; Pirani, Anna; Qiao, Fangli; Stouffer, Ronald J.; Taylor, Karl E.; Treguier, Anne Marie; Tsujino, Hiroyuki; Uotila, Petteri; Valdivieso, Maria; Wang, Qiang; Winton, Michael; Yeager, Stephen G.

2016-09-01

The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs.OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations.

Temperature-related morbidity and mortality in Sub-Saharan Africa: A systematic review of the empirical evidence.

PubMed

Amegah, A Kofi; Rezza, Giovanni; Jaakkola, Jouni J K

2016-05-01

Sub-Saharan Africa (SSA) contributes very little to overall climate change and yet it is estimated to bear the highest burden of climate change, with 34% of the global DALYs attributable to the effects of climate change found in SSA. With the exception of vector-borne diseases, particularly malaria, there is very limited research on human health effects of climate change in SSA, in spite of growing awareness of the region's vulnerability to climate change. Our objective is to systematically review all studies investigating temperature variability and non-vector borne morbidity and mortality in SSA to establish the state and quality of available evidence, identify gaps in knowledge, and propose future research priorities. PubMed, Ovid Medline and Scopus were searched from their inception to the end of December 2014. We modified the GRADE guidelines to rate the quality of the body of evidence. Of 6745 studies screened, 23 studies satisfied the inclusion criteria. Moderate evidence exists to associate temperature variability with cholera outbreaks, cardiovascular disease hospitalization and deaths, and all-cause deaths in the region. The quality of evidence on child undernutrition is low, and for diarrhea occurrence, meningitis, Ebola, asthma and respiratory diseases, and skin diseases, very low. The evidence base is somehow weakened by the limited number of studies uncovered, methodological limitations of the studies, and notable inconsistencies in the study findings. Further research with robust study designs and standardized analytical methods is thus needed to produce more credible evidence base to inform climate change preparedness plans and public health policies for improved adaptive capacity in SSA. Investment in meteorological services, and strengthening of health information systems is also required to guarantee timely, up-to-date and reliable data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Public Health Adaptation to Climate Change in OECD Countries.

PubMed

Austin, Stephanie E; Biesbroek, Robbert; Berrang-Ford, Lea; Ford, James D; Parker, Stephen; Fleury, Manon D

2016-09-07

Climate change is a major challenge facing public health. National governments play a key role in public health adaptation to climate change, but there are competing views on what responsibilities and obligations this will-or should-include in different nations. This study aims to: (1) examine how national-level public health adaptation is occurring in Organization for Economic Cooperation and Development (OECD) countries; (2) examine the roles national governments are taking in public health adaptation; and (3) critically appraise three key governance dimensions of national-level health adaptation-cross-sectoral collaboration, vertical coordination and national health adaptation planning-and identify practical examples suited to different contexts. We systematically reviewed publicly available public health adaptation to climate change documents and webpages by national governments in ten OECD countries using systematic web searches, assessment of self-reporting, and content analysis. Our findings suggest national governments are primarily addressing infectious disease and heat-related risks posed by climate change, typically emphasizing capacity building or information-based groundwork initiatives. We find national governments are taking a variety of approaches to public health adaptation to climate change that do not follow expected convergence and divergence by governance structure. We discuss practical options for incorporating cross-sectoral collaboration, vertical coordination and national health adaptation planning into a variety of contexts and identify leaders national governments can look to to inform their public health adaptation planning. Following the adoption of the Paris Agreement and subsequent increased momentum for adaptation, research tracking adaptation is needed to define what health adaptation looks like in practice, reveal insights that can be taken up across states and sectors, and ensure policy orientated learning.

Assessment of upper tropospheric and stratospheric water vapor and ozone in reanalyses as part of S-RIP

NASA Astrophysics Data System (ADS)

Davis, Sean M.; Hegglin, Michaela I.; Fujiwara, Masatomo; Dragani, Rossana; Harada, Yayoi; Kobayashi, Chiaki; Long, Craig; Manney, Gloria L.; Nash, Eric R.; Potter, Gerald L.; Tegtmeier, Susann; Wang, Tao; Wargan, Krzysztof; Wright, Jonathon S.

2017-10-01

Reanalysis data sets are widely used to understand atmospheric processes and past variability, and are often used to stand in as "observations" for comparisons with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately and consistently these species are represented in existing global reanalyses. In this paper, we present the results of WV and O3 intercomparisons that have been performed as part of the SPARC (Stratosphere-troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The comparisons cover a range of timescales and evaluate both inter-reanalysis and observation-reanalysis differences. We also provide a systematic documentation of the treatment of WV and O3 in current reanalyses to aid future research and guide the interpretation of differences amongst reanalysis fields.The assimilation of total column ozone (TCO) observations in newer reanalyses results in realistic representations of TCO in reanalyses except when data coverage is lacking, such as during polar night. The vertical distribution of ozone is also relatively well represented in the stratosphere in reanalyses, particularly given the relatively weak constraints on ozone vertical structure provided by most assimilated observations and the simplistic representations of ozone photochemical processes in most of the reanalysis forecast models. However, significant biases in the vertical distribution of ozone are found in the upper troposphere and lower stratosphere in all reanalyses.In contrast to O3, reanalysis estimates of stratospheric WV are not directly constrained by assimilated data. Observations of atmospheric humidity are typically used only in the troposphere, below a specified vertical level at or near the tropopause. The fidelity of reanalysis stratospheric WV products is therefore mainly dependent on the reanalyses' representation of the physical drivers that influence stratospheric WV, such as temperatures in the tropical tropopause layer, methane oxidation, and the stratospheric overturning circulation. The lack of assimilated observations and known deficiencies in the representation of stratospheric transport in reanalyses result in much poorer agreement amongst observational and reanalysis estimates of stratospheric WV. Hence, stratospheric WV products from the current generation of reanalyses should generally not be used in scientific studies.

Humidity-regulated dormancy onset in the Fabaceae: a conceptual model and its ecological implications for the Australian wattle Acacia saligna.

PubMed

Tozer, Mark G; Ooi, Mark K J

2014-09-01

Seed dormancy enhances fitness by preventing seeds from germinating when the probability of seedling survival and recruitment is low. The onset of physical dormancy is sensitive to humidity during ripening; however, the implications of this mechanism for seed bank dynamics have not been quantified. This study proposes a model that describes how humidity-regulated dormancy onset may control the accumulation of a dormant seed bank, and seed experiments are conducted to calibrate the model for an Australian Fabaceae, Acacia saligna. The model is used to investigate the impact of climate on seed dormancy and to forecast the ecological implications of human-induced climate change. The relationship between relative humidity and dormancy onset was quantified under laboratory conditions by exposing freshly matured non-dormant seeds to constant humidity levels for fixed durations. The model was field-calibrated by measuring the response of seeds exposed to naturally fluctuating humidity. The model was applied to 3-hourly records of humidity spanning the period 1972-2007 in order to estimate both temporal variability in dormancy and spatial variability attributable to climatic differences among populations. Climate change models were used to project future changes in dormancy onset. A sigmoidal relationship exists between dormancy and humidity under both laboratory and field conditions. Seeds ripened under field conditions became dormant following very short exposure to low humidity (<20 %). Prolonged exposure at higher humidity did not increase dormancy significantly. It is predicted that populations growing in a temperate climate produce 33-55 % fewer dormant seeds than those in a Mediterranean climate; however, dormancy in temperate populations is predicted to increase as a result of climate change. Humidity-regulated dormancy onset may explain observed variation in physical dormancy. The model offers a systematic approach to modelling this variation in population studies. Forecast changes in climate have the potential to alter the seed bank dynamics of species with physical dormancy regulated by this mechanism, with implications for their capacity to delay germination and exploit windows for recruitment. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Humidity-regulated dormancy onset in the Fabaceae: a conceptual model and its ecological implications for the Australian wattle Acacia saligna

PubMed Central

Tozer, Mark G.; Ooi, Mark K. J.

2014-01-01

Background and aims Seed dormancy enhances fitness by preventing seeds from germinating when the probability of seedling survival and recruitment is low. The onset of physical dormancy is sensitive to humidity during ripening; however, the implications of this mechanism for seed bank dynamics have not been quantified. This study proposes a model that describes how humidity-regulated dormancy onset may control the accumulation of a dormant seed bank, and seed experiments are conducted to calibrate the model for an Australian Fabaceae, Acacia saligna. The model is used to investigate the impact of climate on seed dormancy and to forecast the ecological implications of human-induced climate change. Methods The relationship between relative humidity and dormancy onset was quantified under laboratory conditions by exposing freshly matured non-dormant seeds to constant humidity levels for fixed durations. The model was field-calibrated by measuring the response of seeds exposed to naturally fluctuating humidity. The model was applied to 3-hourly records of humidity spanning the period 1972–2007 in order to estimate both temporal variability in dormancy and spatial variability attributable to climatic differences among populations. Climate change models were used to project future changes in dormancy onset. Key Results A sigmoidal relationship exists between dormancy and humidity under both laboratory and field conditions. Seeds ripened under field conditions became dormant following very short exposure to low humidity (<20 %). Prolonged exposure at higher humidity did not increase dormancy significantly. It is predicted that populations growing in a temperate climate produce 33–55 % fewer dormant seeds than those in a Mediterranean climate; however, dormancy in temperate populations is predicted to increase as a result of climate change. Conclusions Humidity-regulated dormancy onset may explain observed variation in physical dormancy. The model offers a systematic approach to modelling this variation in population studies. Forecast changes in climate have the potential to alter the seed bank dynamics of species with physical dormancy regulated by this mechanism, with implications for their capacity to delay germination and exploit windows for recruitment. PMID:25015069

Quantifying uncertainty in climate change science through empirical information theory.

PubMed

Majda, Andrew J; Gershgorin, Boris

2010-08-24

Quantifying the uncertainty for the present climate and the predictions of climate change in the suite of imperfect Atmosphere Ocean Science (AOS) computer models is a central issue in climate change science. Here, a systematic approach to these issues with firm mathematical underpinning is developed through empirical information theory. An information metric to quantify AOS model errors in the climate is proposed here which incorporates both coarse-grained mean model errors as well as covariance ratios in a transformation invariant fashion. The subtle behavior of model errors with this information metric is quantified in an instructive statistically exactly solvable test model with direct relevance to climate change science including the prototype behavior of tracer gases such as CO(2). Formulas for identifying the most sensitive climate change directions using statistics of the present climate or an AOS model approximation are developed here; these formulas just involve finding the eigenvector associated with the largest eigenvalue of a quadratic form computed through suitable unperturbed climate statistics. These climate change concepts are illustrated on a statistically exactly solvable one-dimensional stochastic model with relevance for low frequency variability of the atmosphere. Viable algorithms for implementation of these concepts are discussed throughout the paper.

An overview of patient safety climate in the VA.

PubMed

Hartmann, Christine W; Rosen, Amy K; Meterko, Mark; Shokeen, Priti; Zhao, Shibei; Singer, Sara; Falwell, Alyson; Gaba, David M

2008-08-01

To assess variation in safety climate across VA hospitals nationally. Data were collected from employees at 30 VA hospitals over a 6-month period using the Patient Safety Climate in Healthcare Organizations survey. We sampled 100 percent of senior managers and physicians and a random 10 percent of other employees. At 10 randomly selected hospitals, we sampled an additional 100 percent of employees working in units with intrinsically higher hazards (high-hazard units [HHUs]). Data were collected using an anonymous survey design. We received 4,547 responses (49 percent response rate). The percent problematic response--lower percent reflecting higher levels of patient safety climate--ranged from 12.0-23.7 percent across hospitals (mean=17.5 percent). Differences in safety climate emerged by management level, clinician status, and workgroup. Supervisors and front-line staff reported lower levels of safety climate than senior managers; clinician responses reflected lower levels of safety climate than those of nonclinicians; and responses of employees in HHUs reflected lower levels of safety climate than those of workers in other areas. This is the first systematic study of patient safety climate in VA hospitals. Findings indicate an overall positive safety climate across the VA, but there is room for improvement.

An Analysis of the Climate Data Initiative's Data Collection

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Bugbee, K.

2015-12-01

The Climate Data Initiative (CDI) is a broad multi-agency effort of the U.S. government that seeks to leverage the extensive existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship to support national climate-change preparedness. The CDI project is a systematic effort to manually curate and share openly available climate data from various federal agencies. To date, the CDI has curated seven themes, or topics, relevant to climate change resiliency. These themes include Coastal Flooding, Food Resilience, Water, Ecosystem Vulnerability, Human Health, Energy Infrastructure, and Transportation. Each theme was curated by subject matter experts who selected datasets relevant to the topic at hand. An analysis of the entire Climate Data Initiative data collection and the data curated for each theme offers insights into which datasets are considered most relevant in addressing climate resiliency. Other aspects of the data collection will be examined including which datasets were the most visited or popular and which datasets were the most sought after for curation by the theme teams. Results from the analysis of the CDI collection will be presented in this talk.

Uncertainty in simulating wheat yields under climate change

NASA Astrophysics Data System (ADS)

Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P. J.; Rötter, R. P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P. K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Williams, J. R.; Wolf, J.

2013-09-01

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

Modeling natural wetlands: A new global framework built on wetland observations

NASA Astrophysics Data System (ADS)

Matthews, E.; Romanski, J.; Olefeldt, D.

2015-12-01

Natural wetlands are the world's largest methane (CH4) source, and their distribution and CH4 fluxes are sensitive to interannual and longer-term climate variations. Wetland distributions used in wetland-CH4 models diverge widely, and these geographic differences contribute substantially to large variations in magnitude, seasonality and distribution of modeled methane fluxes. Modeling wetland type and distribution—closely tied to simulating CH4 emissions—is a high priority, particularly for studies of wetlands and CH4 dynamics under past and future climates. Methane-wetland models either prescribe or simulate methane-producing areas (aka wetlands) and both approaches result in predictable over- and under-estimates. 1) Monthly satellite-derived inundation data include flooded areas that are not wetlands (e.g., lakes, reservoirs, and rivers), and do not identify non-flooded wetlands. 2) Models simulating methane-producing areas overwhelmingly rely on modeled soil moisture, systematically over-estimating total global area, with regional over- and under-estimates, while schemes to model soil-moisture typically cannot account for positive water tables (i.e., flooding). Interestingly, while these distinct hydrological approaches to identify wetlands are complementary, merging them does not provide critical data needed to model wetlands for methane studies. We present a new integrated framework for modeling wetlands, and ultimately their methane emissions, that exploits the extensive body of data and information on wetlands. The foundation of the approach is an existing global gridded data set comprising all and only wetlands, including vegetation information. This data set is augmented with data inter alia on climate, inundation dynamics, soil type and soil carbon, permafrost, active-layer depth, growth form, and species composition. We investigate this enhanced wetland data set to identify which variables best explain occurrence and characteristics of observed wetland ecosystems. The novelty of the new approach is that it starts from what we know about wetlands, builds ecosystem-specific models from these observations, and avoids known biases in current hydrology-based approaches to wetland definition in methane models.

Synchrony of forest responses to climate from the aspect of tree mortality in South Korea

NASA Astrophysics Data System (ADS)

Kim, M.; Lee, W. K.; Piao, D.; Choi, G. M.; Gang, H. U.

2016-12-01

Mortality is a key process in forest-stand dynamics. However, tree mortality is not well understood, particularly in relation to climatic factors. The objectives of this study were to: (i) determine the patterns of maximum stem number (MSN) per ha over dominant tree height from 5-year remeasurements of the permanent sample plots for temperate forests [Red pine (Pinus densiflora), Japanese larch (Larix kaempferi), Korean pine (Pinus koraiensis), Chinese cork oak (Quercus variabilis), and Mongolian oak (Quercus mongolica)] using Sterba's theory and Korean National Forest Inventory (NFI) data, (ii) develop a stand-level mortality (self-thinning) model using the MSN curve, and (iii) assess the impact of temperature on tree mortality in semi-variogram and linear regression models. The MSN curve represents the upper range of observed stem numbers per ha. The mortality model and validation statistic reveal significant differences between the observed data and the model predictions (R2 = 0.55-0.81), and no obvious dependencies or patterns that indicate systematic trends between the residuals and the independent variable. However, spatial autocorrelation was detected from residuals of coniferous species (Red pine, Japanese larch and Korean pine), but not of oak species (Chinese cork oak and Mongolian oak). Based on linear regression from residuals, we found that the mortality of coniferous forests tended to increase when the annual mean temperature increased. Conversely, oak mortality nonsignificantly decreased with increasing temperature. These findings indicate that enhanced tree mortality due to rising temperatures in response to climate change is possible, especially in coniferous forests, and are expected to contribute to policy decisions to support and forest management practices.

Global Land Product Validation Protocols: An Initiative of the CEOS Working Group on Calibration and Validation to Evaluate Satellite-derived Essential Climate Variables

NASA Astrophysics Data System (ADS)

Guillevic, P. C.; Nickeson, J. E.; Roman, M. O.; camacho De Coca, F.; Wang, Z.; Schaepman-Strub, G.

2016-12-01

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.

Weighting climate model projections using observational constraints.

PubMed

Gillett, Nathan P

2015-11-13

Projected climate change integrates the net response to multiple climate feedbacks. Whereas existing long-term climate change projections are typically based on unweighted individual climate model simulations, as observed climate change intensifies it is increasingly becoming possible to constrain the net response to feedbacks and hence projected warming directly from observed climate change. One approach scales simulated future warming based on a fit to observations over the historical period, but this approach is only accurate for near-term projections and for scenarios of continuously increasing radiative forcing. For this reason, the recent Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) included such observationally constrained projections in its assessment of warming to 2035, but used raw model projections of longer term warming to 2100. Here a simple approach to weighting model projections based on an observational constraint is proposed which does not assume a linear relationship between past and future changes. This approach is used to weight model projections of warming in 2081-2100 relative to 1986-2005 under the Representative Concentration Pathway 4.5 forcing scenario, based on an observationally constrained estimate of the Transient Climate Response derived from a detection and attribution analysis. The resulting observationally constrained 5-95% warming range of 0.8-2.5 K is somewhat lower than the unweighted range of 1.1-2.6 K reported in the IPCC AR5. © 2015 The Authors.

Conservation threats due to human-caused increases in fire frequency in Mediterranean-climate ecosystems.

PubMed

Syphard, Alexandra D; Radeloff, Volker C; Hawbaker, Todd J; Stewart, Susan I

2009-06-01

Periodic wildfire is an important natural process in Mediterranean-climate ecosystems, but increasing fire recurrence threatens the fragile ecology of these regions. Because most fires are human-caused, we investigated how human population patterns affect fire frequency. Prior research in California suggests the relationship between population density and fire frequency is not linear. There are few human ignitions in areas with low population density, so fire frequency is low. As population density increases, human ignitions and fire frequency also increase, but beyond a density threshold, the relationship becomes negative as fuels become sparser and fire suppression resources are concentrated. We tested whether this hypothesis also applies to the other Mediterranean-climate ecosystems of the world. We used global satellite databases of population, fire activity, and land cover to evaluate the spatial relationship between humans and fire in the world's five Mediterranean-climate ecosystems. Both the mean and median population densities were consistently and substantially higher in areas with than without fire, but fire again peaked at intermediate population densities, which suggests that the spatial relationship is complex and nonlinear. Some land-cover types burned more frequently than expected, but no systematic differences were observed across the five regions. The consistent association between higher population densities and fire suggests that regardless of differences between land-cover types, natural fire regimes, or overall population, the presence of people in Mediterranean-climate regions strongly affects the frequency of fires; thus, population growth in areas now sparsely settled presents a conservation concern. Considering the sensitivity of plant species to repeated burning and the global conservation significance of Mediterranean-climate ecosystems, conservation planning needs to consider the human influence on fire frequency. Fine-scale spatial analysis of relationships between people and fire may help identify areas where increases in fire frequency will threaten ecologically valuable areas. ©2009 Society for Conservation Biology.

Assessing response of sediment load variation to climate change and human activities with six different approaches.

PubMed

Zhao, Guangju; Mu, Xingmin; Jiao, Juying; Gao, Peng; Sun, Wenyi; Li, Erhui; Wei, Yanhong; Huang, Jiacong

2018-05-23

Understanding the relative contributions of climate change and human activities to variations in sediment load is of great importance for regional soil, and river basin management. Considerable studies have investigated spatial-temporal variation of sediment load within the Loess Plateau; however, contradictory findings exist among methods used. This study systematically reviewed six quantitative methods: simple linear regression, double mass curve, sediment identity factor analysis, dam-sedimentation based method, the Sediment Delivery Distributed (SEDD) model, and the Soil Water Assessment Tool (SWAT) model. The calculation procedures and merits for each method were systematically explained. A case study in the Huangfuchuan watershed on the northern Loess Plateau has been undertaken. The results showed that sediment load had been reduced by 70.5% during the changing period from 1990 to 2012 compared to that of the baseline period from 1955 to 1989. Human activities accounted for an average of 93.6 ± 4.1% of the total decline in sediment load, whereas climate change contributed 6.4 ± 4.1%. Five methods produced similar estimates, but the linear regression yielded relatively different results. The results of this study provide a good reference for assessing the effects of climate change and human activities on sediment load variation by using different methods. Copyright © 2018. Published by Elsevier B.V.

Final Report on Hierarchical Coupled Modeling and Prediction of Regional Climate Change in the Atlantic Sector

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

Saravanan, Ramalingam

2011-10-30

During the course of this project, we have accomplished the following: a) Carried out studies of climate changes in the past using a hierarchy of intermediate coupled models (Chang et al., 2008; Wan et al 2009; Wen et al., 2010a,b) b) Completed the development of a Coupled Regional Climate Model (CRCM; Patricola et al., 2011a,b) c) Carried out studies testing hypotheses testing the origin of systematic errors in the CRCM (Patricola et al., 2011a,b) d) Carried out studies of the impact of air-sea interaction on hurricanes, in the context of barrier layer interactions (Balaguru et al)

Valuing Climate Change Impacts on Human Health: Empirical Evidence from the Literature

PubMed Central

Markandya, Anil; Chiabai, Aline

2009-01-01

There is a broad consensus that climate change will increase the costs arising from diseases such as malaria and diarrhea and, furthermore, that the largest increases will be in developing countries. One of the problems is the lack of studies measuring these costs systematically and in detail. This paper critically reviews a number of studies about the costs of planned adaptation in the health context, and compares current health expenditures with MDGs which are felt to be inadequate when considering climate change impacts. The analysis serves also as a critical investigation of the methodologies used and aims at identifying research weaknesses and gaps. PMID:19440414

Climate Benchmark Missions: CLARREO

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Young, David F.

2010-01-01

CLARREO (Climate Absolute Radiance and Refractivity Observatory) is one of the four Tier 1 missions recommended by the recent NRC decadal survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to rigorously observe climate change on decade time scales and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO mission accomplishes this critical objective through highly accurate and SI traceable decadal change observations sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. The same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. The CLARREO breakthrough in decadal climate change observations is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. These accuracy levels are determined both by the projected decadal changes as well as by the background natural variability that such signals must be detected against. The accuracy for decadal change traceability to SI standards includes uncertainties of calibration, sampling, and analysis methods. Unlike most other missions, all of the CLARREO requirements are judged not by instantaneous accuracy, but instead by accuracy in large time/space scale average decadal changes. Given the focus on decadal climate change, the NRC Decadal Survey concluded that the single most critical issue for decadal change observations was their lack of accuracy and low confidence in observing the small but critical climate change signals. CLARREO is the recommended attack on this challenge, and builds on the last decade of climate observation advances in the Earth Observing System as well as metrological advances at NIST (National Institute of Standards and Technology) and other standards laboratories.

Planetary boundary layer as an essential component of the earth's climate system

NASA Astrophysics Data System (ADS)

Davy, Richard; Esau, Igor

2015-04-01

Following the traditional engineering approach proposed by Prandtl, the turbulent planetary boundary layers (PBLs) are considered in the climate science as complex, non-linear, essential but nevertheless subordinated components of the earth's climate system. Correspondingly, the temperature variations, dT - a popular and practically important measure of the climate variability, are seen as the system's response to the external heat forcing, Q, e.g. in the energy balance model of the type dT=Q/C (1). The moderation of this response by non-linear feedbacks embedded in the effective heat capacity, C, are to a large degree overlooked. The effective heat capacity is globally determined by the depth of the ocean mixed layer (on multi-decadal and longer time scales) but regionally, over the continents, C is much smaller and determined (on decadal time scales) by the depth, h, of the PBL. The present understanding of the climatological features of turbulent boundary layers is set by the works of Frankignoul & Hasselmann (1976) and Manabe & Stauffer (1980). The former explained how large-scale climate anomalies could be generated in the case of a large C (in the sea surface temperature) by the delta-correlated stochastic forcing (white noise). The latter demonstrated that the climate response to a given forcing is moderated by the depth, h, so that in the shallow PBL the signal should be significantly amplified. At present there are more than 3000 publications (ISI Web of Knowledge) which detail this understanding but the physical mechanisms, which control the boundary layer depth, and statistical relationships between the turbulent and climatological measures remain either unexplored or incorrectly attributed. In order to identify the climatic role of the PBL, the relationships between the PBL depth, h, - as the integral measure of the turbulent processes and micro-circulations due to the surface heterogeneity - and the climatic variability (variations and trends) of temperature have to be established. These relationships are necessary to complete the model (1) where the relationships between temperature variability, dT, and heat forcing, Q, are intensively studied. We demonstrate that the statistical dependences between dT and h becomes the primary factor in controlling the climate features of the earth's climate system when h is shallow (less than about 500 m). Such conditions are found in the cold (with negative surface heat balance on average) and dry (with large-scale air subsidence) climates. To get those climates and their variations correct, the climate models must be able to reproduce the shallow stably-stratified PBL. We show that the present-day CMIP-5 models are systematically and strongly biased towards producing deeper PBLs (between 20-50% deeper than observed) in this part of the parameter space which leads to large errors (around 15 K) and a damped variability of the surface temperatures under these conditions. More generally, this bias indicates that the models represent the earth's cooling processes incorrectly, which may be a part of the puzzle of the observed "hiatus" (or pause) in global warming. Frankignoul, C. & K. Hasselmann, 1977: Stochastic climate models. Part 2, Application to sea-surface temperature anomalies and thermocline variability, Tellus, 29, 289-305. Manabe, S. & R. Stouffer, 1980: Sensitivity of a Global Climate Model to an increase of CO2 concentration in the atmosphere, Journal of Geophysical Research, 85(C10): 5529-5554.

Systematic errors in Monsoon simulation: importance of the equatorial Indian Ocean processes

NASA Astrophysics Data System (ADS)

Annamalai, H.; Taguchi, B.; McCreary, J. P., Jr.; Nagura, M.; Miyama, T.

2015-12-01

H. Annamalai1, B. Taguchi2, J.P. McCreary1, J. Hafner1, M. Nagura2, and T. Miyama2 International Pacific Research Center, University of Hawaii, USA Application Laboratory, JAMSTEC, Japan In climate models, simulating the monsoon precipitation climatology remains a grand challenge. Compared to CMIP3, the multi-model-mean (MMM) errors for Asian-Australian monsoon (AAM) precipitation climatology in CMIP5, relative to GPCP observations, have shown little improvement. One of the implications is that uncertainties in the future projections of time-mean changes to AAM rainfall may not have reduced from CMIP3 to CMIP5. Despite dedicated efforts by the modeling community, the progress in monsoon modeling is rather slow. This leads us to wonder: Has the scientific community reached a "plateau" in modeling mean monsoon precipitation? Our focus here is to better understanding of the coupled air-sea interactions, and moist processes that govern the precipitation characteristics over the tropical Indian Ocean where large-scale errors persist. A series idealized coupled model experiments are performed to test the hypothesis that errors in the coupled processes along the equatorial Indian Ocean during inter-monsoon seasons could potentially influence systematic errors during the monsoon season. Moist static energy budget diagnostics has been performed to identify the leading moist and radiative processes that account for the large-scale errors in the simulated precipitation. As a way forward, we propose three coordinated efforts, and they are: (i) idealized coupled model experiments; (ii) process-based diagnostics and (iii) direct observations to constrain model physics. We will argue that a systematic and coordinated approach in the identification of the various interactive processes that shape the precipitation basic state needs to be carried out, and high-quality observations over the data sparse monsoon region are needed to validate models and further improve model physics.

Snow cover volumes dynamic monitoring during melting season using high topographic accuracy approach for a Lebanese high plateau witness sinkhole

NASA Astrophysics Data System (ADS)

Abou Chakra, Charbel; Somma, Janine; Elali, Taha; Drapeau, Laurent

2017-04-01

Climate change and its negative impact on water resource is well described. For countries like Lebanon, undergoing major population's rise and already decreasing precipitations issues, effective water resources management is crucial. Their continuous and systematic monitoring overs long period of time is therefore an important activity to investigate drought risk scenarios for the Lebanese territory. Snow cover on Lebanese mountains is the most important water resources reserve. Consequently, systematic observation of snow cover dynamic plays a major role in order to support hydrologic research with accurate data on snow cover volumes over the melting season. For the last 20 years few studies have been conducted for Lebanese snow cover. They were focusing on estimating the snow cover surface using remote sensing and terrestrial measurement without obtaining accurate maps for the sampled locations. Indeed, estimations of both snow cover area and volumes are difficult due to snow accumulation very high variability and Lebanese mountains chains slopes topographic heterogeneity. Therefore, the snow cover relief measurement in its three-dimensional aspect and its Digital Elevation Model computation is essential to estimate snow cover volume. Despite the need to cover the all lebanese territory, we favored experimental terrestrial topographic site approaches due to high resolution satellite imagery cost, its limited accessibility and its acquisition restrictions. It is also most challenging to modelise snow cover at national scale. We therefore, selected a representative witness sinkhole located at Ouyoun el Siman to undertake systematic and continuous observations based on topographic approach using a total station. After four years of continuous observations, we acknowledged the relation between snow melt rate, date of total melting and neighboring springs discharges. Consequently, we are able to forecast, early in the season, dates of total snowmelt and springs low water flows which are essentially feeded by snowmelt water. Simulations were ran, predicting the snow level between two sampled dates, they provided promising result for national scale extrapolation.

Mapping the Decadal Spatio-temporal Variation of Social Vulnerability to Hydro-climatic Extremes over India

NASA Astrophysics Data System (ADS)

H, V.; Karmakar, S.; Ghosh, S.

2015-12-01

Human induced global warming is unequivocal and observational studies shows that, this has led to increase in the intensity and frequency of hydro-climatic extremes, most importantly precipitation extreme, heat waves and drought; and also is expected to be increased in the future. The occurrence of these extremes have a devastating effects on nation's economy and on societal well-being. Previous studies on India provided the evidences of significant changes in the precipitation extreme from pre- to post-1950, with huge spatial heterogeneity; and projections of heat waves indicated that significant part of India will experience heat stress conditions in the future. Under these circumstance, it is necessary to develop a nation-wide social vulnerability map to scrutinize the adequacy of existing emergency management. Yet there has been no systematic past efforts on mapping social vulnerability to hydro-climatic extremes at nation-wide for India. Therefore, immediate efforts are required to quantify the social vulnerability, particularly developing country like India, where major transformations in demographic characteristics and development patterns are evident during past decades. In the present study, we perform a comprehensive spatio-temporal social vulnerability analysis by considering multiple sensitive indicators for three decades (1990-2010) which identifies the hot-spots, with higher vulnerability to hydro-climatic extremes. The population datasets are procured from Census of India and the meteorological datasets are obtained from India Meteorological Department (IMD). The study derives interesting results on decadal changes of spatial distribution of risk, considering social vulnerability and hazard to extremes.

Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

NASA Astrophysics Data System (ADS)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

Assessing uncertainty in high-resolution spatial climate data across the US Northeast.

PubMed

Bishop, Daniel A; Beier, Colin M

2013-01-01

Local and regional-scale knowledge of climate change is needed to model ecosystem responses, assess vulnerabilities and devise effective adaptation strategies. High-resolution gridded historical climate (GHC) products address this need, but come with multiple sources of uncertainty that are typically not well understood by data users. To better understand this uncertainty in a region with a complex climatology, we conducted a ground-truthing analysis of two 4 km GHC temperature products (PRISM and NRCC) for the US Northeast using 51 Cooperative Network (COOP) weather stations utilized by both GHC products. We estimated GHC prediction error for monthly temperature means and trends (1980-2009) across the US Northeast and evaluated any landscape effects (e.g., elevation, distance from coast) on those prediction errors. Results indicated that station-based prediction errors for the two GHC products were similar in magnitude, but on average, the NRCC product predicted cooler than observed temperature means and trends, while PRISM was cooler for means and warmer for trends. We found no evidence for systematic sources of uncertainty across the US Northeast, although errors were largest at high elevations. Errors in the coarse-scale (4 km) digital elevation models used by each product were correlated with temperature prediction errors, more so for NRCC than PRISM. In summary, uncertainty in spatial climate data has many sources and we recommend that data users develop an understanding of uncertainty at the appropriate scales for their purposes. To this end, we demonstrate a simple method for utilizing weather stations to assess local GHC uncertainty and inform decisions among alternative GHC products.

A systematic review of ecological attributes that confer resilience to climate change in environmental restoration

PubMed Central

Timpane-Padgham, Britta L.

2017-01-01

Ecological restoration is widely practiced as a means of rehabilitating ecosystems and habitats that have been degraded or impaired through human use or other causes. Restoration practices now are confronted by climate change, which has the potential to influence long-term restoration outcomes. Concepts and attributes from the resilience literature can help improve restoration and monitoring efforts under changing climate conditions. We systematically examined the published literature on ecological resilience to identify biological, chemical, and physical attributes that confer resilience to climate change. We identified 45 attributes explicitly related to climate change and classified them as individual- (9), population- (6), community- (7), ecosystem- (7), or process-level attributes (16). Individual studies defined resilience as resistance to change or recovery from disturbance, and only a few studies explicitly included both concepts in their definition of resilience. We found that individual and population attributes generally are suited to species- or habitat-specific restoration actions and applicable at the population scale. Community attributes are better suited to habitat-specific restoration at the site scale, or system-wide restoration at the ecosystem scale. Ecosystem and process attributes vary considerably in their type and applicability. We summarize these relationships in a decision support table and provide three example applications to illustrate how these classifications can be used to prioritize climate change resilience attributes for specific restoration actions. We suggest that (1) including resilience as an explicit planning objective could increase the success of restoration projects, (2) considering the ecological context and focal scale of a restoration action is essential in choosing appropriate resilience attributes, and (3) certain ecological attributes, such as diversity and connectivity, are more commonly considered to confer resilience because they apply to a wide variety of species and ecosystems. We propose that identifying sources of ecological resilience is a critical step in restoring ecosystems in a changing climate. PMID:28301560

A systematic review of ecological attributes that confer resilience to climate change in environmental restoration.

PubMed

Timpane-Padgham, Britta L; Beechie, Tim; Klinger, Terrie

2017-01-01

Ecological restoration is widely practiced as a means of rehabilitating ecosystems and habitats that have been degraded or impaired through human use or other causes. Restoration practices now are confronted by climate change, which has the potential to influence long-term restoration outcomes. Concepts and attributes from the resilience literature can help improve restoration and monitoring efforts under changing climate conditions. We systematically examined the published literature on ecological resilience to identify biological, chemical, and physical attributes that confer resilience to climate change. We identified 45 attributes explicitly related to climate change and classified them as individual- (9), population- (6), community- (7), ecosystem- (7), or process-level attributes (16). Individual studies defined resilience as resistance to change or recovery from disturbance, and only a few studies explicitly included both concepts in their definition of resilience. We found that individual and population attributes generally are suited to species- or habitat-specific restoration actions and applicable at the population scale. Community attributes are better suited to habitat-specific restoration at the site scale, or system-wide restoration at the ecosystem scale. Ecosystem and process attributes vary considerably in their type and applicability. We summarize these relationships in a decision support table and provide three example applications to illustrate how these classifications can be used to prioritize climate change resilience attributes for specific restoration actions. We suggest that (1) including resilience as an explicit planning objective could increase the success of restoration projects, (2) considering the ecological context and focal scale of a restoration action is essential in choosing appropriate resilience attributes, and (3) certain ecological attributes, such as diversity and connectivity, are more commonly considered to confer resilience because they apply to a wide variety of species and ecosystems. We propose that identifying sources of ecological resilience is a critical step in restoring ecosystems in a changing climate.

Climate Change Adaptation in the Western U.S.: the Case for Dynamic Rule Curves in Water Resources Management

NASA Astrophysics Data System (ADS)

Lee, S.; Hamlet, A. F.; Burges, S. J.

2008-12-01

Climate change in the Western U.S. will bring systematic hydrologic changes affecting many water resources systems. Successful adaptation to these changes, which will be ongoing through the 21st century, will require the 'rebalancing' of competing system objectives such as water supply, flood control, hydropower production, and environmental services in response to hydrologic (and other) changes. Although fixed operating policies for the operation of reservoirs has been a traditional approach to water management in the 20th century, the rapid pace of projected climate shifts (~0.5 F per decade), and the prohibitive costs of recursive policy intervention to mitigate impacts, suggest that more sophisticated approaches will be needed to cope with climate change on a long term basis. The use of 'dynamic rule curves' is an approach that maintains some of the key characteristics of current water management practice (reservoir rule curves) while avoiding many of the fundamental drawbacks of traditional water resources management strategies in a non-stationary climate. In this approach, water resources systems are optimized for each operational period using ensemble streamflow and/or water demand forecasts. The ensemble of optimized reservoir storage traces are then analyzed to produce a set of unique reservoir rule curves for each operational period reflecting the current state of the system. The potential advantage of this approach is that hydrologic changes associated with climate change (such as systematically warmer temperatures) can be captured explicitly in operational hydrologic forecasts, which would in turn inform the optimized reservoir management solutions, creating water resources systems that are largely 'self tending' as the climate system evolves. Furthermore, as hydrologic forecasting systems improve (e.g. in response to improved ENSO forecasting or other scientific advances), so does the performance of reservoir operations. An example of the approach is given for flood control in the Columbia River basin.

Estimating the relative contributions of human withdrawals and climate variability to changes in groundwater

NASA Astrophysics Data System (ADS)

Swenson, S. C.; Lawrence, D. M.

2014-12-01

Estimating the relative contributions of human withdrawals and climate variability to changes in groundwater is a challenging task at present. One method that has been used recently is a model-data synthesis combining GRACE total water storage estimates with simulated water storage estimates from land surface models. In this method, water storage changes due to natural climate variations simulated by a model are removed from total water storage changes observed by GRACE; the residual is then interpreted as anthropogenic groundwater change. If the modeled water storage estimate contains systematic errors, these errors will also be present in the residual groundwater estimate. For example, simulations performed with the Community Land Model (CLM; the land component of the Community Earth System Model) generally show a weak (as much as 50% smaller) seasonal cycle of water storage in semi-arid regions when compared to GRACE satellite water storage estimates. This bias propagates into GRACE-CLM anthropogenic groundwater change estimates, which then exhibit unphysical seasonal variability. The CLM bias can be traced to the parameterization of soil evaporative resistance. Incorporating a new soil resistance parameterization in CLM greatly reduces the seasonal bias with respect to GRACE. In this study, we compare the improved CLM water storage estimates to GRACE and discuss the implications for estimates of anthropogenic groundwater withdrawal, showing examples for the Middle East and Southwestern United States.

Assessing Hydrological and Energy Budgets in Amazonia through Regional Downscaling, and Comparisons with Global Reanalysis Products

NASA Astrophysics Data System (ADS)

Nunes, A.; Ivanov, V. Y.

2014-12-01

Although current global reanalyses provide reasonably accurate large-scale features of the atmosphere, systematic errors are still found in the hydrological and energy budgets of such products. In the tropics, precipitation is particularly challenging to model, which is also adversely affected by the scarcity of hydrometeorological datasets in the region. With the goal of producing downscaled analyses that are appropriate for a climate assessment at regional scales, a regional spectral model has used a combination of precipitation assimilation with scale-selective bias correction. The latter is similar to the spectral nudging technique, which prevents the departure of the regional model's internal states from the large-scale forcing. The target area in this study is the Amazon region, where large errors are detected in reanalysis precipitation. To generate the downscaled analysis, the regional climate model used NCEP/DOE R2 global reanalysis as the initial and lateral boundary conditions, and assimilated NOAA's Climate Prediction Center (CPC) MORPHed precipitation (CMORPH), available at 0.25-degree resolution, every 3 hours. The regional model's precipitation was successfully brought closer to the observations, in comparison to the NCEP global reanalysis products, as a result of the impact of a precipitation assimilation scheme on cumulus-convection parameterization, and improved boundary forcing achieved through a new version of scale-selective bias correction. Water and energy budget terms were also evaluated against global reanalyses and other datasets.

Patterns and biases in climate change research on amphibians and reptiles: a systematic review

PubMed Central

2016-01-01

Climate change probably has severe impacts on animal populations, but demonstrating a causal link can be difficult because of potential influences by additional factors. Assessing global impacts of climate change effects may also be hampered by narrow taxonomic and geographical research foci. We review studies on the effects of climate change on populations of amphibians and reptiles to assess climate change effects and potential biases associated with the body of work that has been conducted within the last decade. We use data from 104 studies regarding the effect of climate on 313 species, from 464 species–study combinations. Climate change effects were reported in 65% of studies. Climate change was identified as causing population declines or range restrictions in half of the cases. The probability of identifying an effect of climate change varied among regions, taxa and research methods. Climatic effects were equally prevalent in studies exclusively investigating climate factors (more than 50% of studies) and in studies including additional factors, thus bolstering confidence in the results of studies exclusively examining effects of climate change. Our analyses reveal biases with respect to geography, taxonomy and research question, making global conclusions impossible. Additional research should focus on under-represented regions, taxa and questions. Conservation and climate policy should consider the documented harm climate change causes reptiles and amphibians. PMID:27703684

Variance analysis of forecasted streamflow maxima in a wet temperate climate

NASA Astrophysics Data System (ADS)

Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

2018-05-01

Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

Contributions of changes in climatology and perturbation and the resulting nonlinearity to regional climate change.

PubMed

Adachi, Sachiho A; Nishizawa, Seiya; Yoshida, Ryuji; Yamaura, Tsuyoshi; Ando, Kazuto; Yashiro, Hisashi; Kajikawa, Yoshiyuki; Tomita, Hirofumi

2017-12-20

Future changes in large-scale climatology and perturbation may have different impacts on regional climate change. It is important to understand the impacts of climatology and perturbation in terms of both thermodynamic and dynamic changes. Although many studies have investigated the influence of climatology changes on regional climate, the significance of perturbation changes is still debated. The nonlinear effect of these two changes is also unknown. We propose a systematic procedure that extracts the influences of three factors: changes in climatology, changes in perturbation and the resulting nonlinear effect. We then demonstrate the usefulness of the procedure, applying it to future changes in precipitation. All three factors have the same degree of influence, especially for extreme rainfall events. Thus, regional climate assessments should consider not only the climatology change but also the perturbation change and their nonlinearity. This procedure can advance interpretations of future regional climates.

Climate Impacts on Tropospheric Ozone and Hydroxyl

NASA Technical Reports Server (NTRS)

Shindell, Drew T.; Bell, N.; Faluvegi, G.

2003-01-01

Climate change may influence tropospheric ozone and OH via several main pathways: (1) altering chemistry via temperature and humidity changes, (2) changing ozone and precursor sources via surface emissions, stratosphere-troposphere exchange, and light- ning, and (3) affecting trace gas sinks via the hydrological cycle and dry deposition. We report results from a set of coupled chemistry-climate model simulations designed to systematically study these effects. We compare the various effects with one another and with past and projected future changes in anthropogenic and natural emissions of ozone precursors. We find that white the overall impact of climate on ozone is probably small compared to emission changes, some significant seasonal and regional effects are apparent. The global effect on hydroxyl is quite large, however, similar in size to the effect of emission changes. Additionally, we show that many of the chemistry-climate links that are not yet adequately modeled are potentially important.

Sea Surface Temperature of the mid-Piacenzian Ocean: A Data-Model Comparison

PubMed Central

Dowsett, Harry J.; Foley, Kevin M.; Stoll, Danielle K.; Chandler, Mark A.; Sohl, Linda E.; Bentsen, Mats; Otto-Bliesner, Bette L.; Bragg, Fran J.; Chan, Wing-Le; Contoux, Camille; Dolan, Aisling M.; Haywood, Alan M.; Jonas, Jeff A.; Jost, Anne; Kamae, Youichi; Lohmann, Gerrit; Lunt, Daniel J.; Nisancioglu, Kerim H.; Abe-Ouchi, Ayako; Ramstein, Gilles; Riesselman, Christina R.; Robinson, Marci M.; Rosenbloom, Nan A.; Salzmann, Ulrich; Stepanek, Christian; Strother, Stephanie L.; Ueda, Hiroaki; Yan, Qing; Zhang, Zhongshi

2013-01-01

The mid-Piacenzian climate represents the most geologically recent interval of long-term average warmth relative to the last million years, and shares similarities with the climate projected for the end of the 21st century. As such, it represents a natural experiment from which we can gain insight into potential climate change impacts, enabling more informed policy decisions for mitigation and adaptation. Here, we present the first systematic comparison of Pliocene sea surface temperature (SST) between an ensemble of eight climate model simulations produced as part of PlioMIP (Pliocene Model Intercomparison Project) with the PRISM (Pliocene Research, Interpretation and Synoptic Mapping) Project mean annual SST field. Our results highlight key regional and dynamic situations where there is discord between the palaeoenvironmental reconstruction and the climate model simulations. These differences have led to improved strategies for both experimental design and temporal refinement of the palaeoenvironmental reconstruction. PMID:23774736

Community-level climate change vulnerability research: trends, progress, and future directions

NASA Astrophysics Data System (ADS)

McDowell, Graham; Ford, James; Jones, Julie

2016-03-01

This study systematically identifies, characterizes, and critically evaluates community-level climate change vulnerability assessments published over the last 25 years (n = 274). We find that while the field has advanced considerably in terms of conceptual framing and methodological approaches, key shortcomings remain in how vulnerability is being studied at the community-level. We argue that vulnerability research needs to more critically engage with the following: methods for evaluating future vulnerability, the relevance of vulnerability research for decision-making, interdependencies between social and ecological systems, attention to researcher / subject power dynamics, critical interpretation of key terms, and consideration of the potentially positive opportunities presented by a changing climate. Addressing these research needs is necessary for generating knowledge that supports climate-affected communities in navigating the challenges and opportunities ahead.

Remote Sensing and halocene Vegetation: History of Global Change

NASA Technical Reports Server (NTRS)

D'Antoni, Hector L.; Schaebitz, Frank

1995-01-01

Predictions of the future evolution of the earth's atmospheric chemistry and its impact on global circulation patterns are based on Global Climate Models (GCMs) that integrate the complex interactions of the biosphere, atmosphere and the oceans. Most of the available records of climate and environment are short-term records (from decades to a few hundred years) with convolved information of real trends and short-term fluctuations. GCMs must be tested beyond the short-term record of climate and environment to insure that predictions are based on trends and therefore are appropriate to support long term policy making. Unfortunately different parts of the world, weather stations are scattered, records extend over a period of only few years, and there are no systematic climate records for large portions of the globe.

Simulation of modern climate with the new version of the INM RAS climate model

NASA Astrophysics Data System (ADS)

Volodin, E. M.; Mortikov, E. V.; Kostrykin, S. V.; Galin, V. Ya.; Lykosov, V. N.; Gritsun, A. S.; Diansky, N. A.; Gusev, A. V.; Yakovlev, N. G.

2017-03-01

The INMCM5.0 numerical model of the Earth's climate system is presented, which is an evolution from the previous version, INMCM4.0. A higher vertical resolution for the stratosphere is applied in the atmospheric block. Also, we raised the upper boundary of the calculating area, added the aerosol block, modified parameterization of clouds and condensation, and increased the horizontal resolution in the ocean block. The program implementation of the model was also updated. We consider the simulation of the current climate using the new version of the model. Attention is focused on reducing systematic errors as compared to the previous version, reproducing phenomena that could not be simulated correctly in the previous version, and modeling the problems that remain unresolved.

The association between neighbourhoods and educational achievement, a systematic review and meta-analysis.

PubMed

Nieuwenhuis, Jaap; Hooimeijer, Pieter

2016-01-01

Many studies have examined the effects of neighbourhoods on educational outcomes. The results of these studies are often conflicting, even if the same independent variables (such as poverty, educational climate, social disorganisation, or ethnic composition) are used. A systematic meta-analysis may help to resolve this lack of external validity. We identified 5516 articles from which we selected 88 that met all of the inclusion criteria. Using meta-regression, we found that the relation between neighbourhoods and individual educational outcomes is a function of neighbourhood poverty, the neighbourhood's educational climate, the proportion of ethnic/migrant groups, and social disorganisation in the neighbourhood. The variance in the findings from different studies can partly be explained by the sampling design and the type of model used in each study. More important is the use of control variables (school, family SES, and parenting variables) in explaining the variation in the strength of neighbourhood effects.

Quantifying climatic controls on river network topology across scales

NASA Astrophysics Data System (ADS)

Ranjbar Moshfeghi, S.; Hooshyar, M.; Wang, D.; Singh, A.

2017-12-01

Branching structure of river networks is an important topologic and geomorphologic feature that depends on several factors (e.g. climate, tectonic). However, mechanisms that cause these drainage patterns in river networks are poorly understood. In this study, we investigate the effects of varying climatic forcing on river network topology and geomorphology. For this, we select 20 catchments across the United States with different long-term climatic conditions quantified by climate aridity index (AI), defined here as the ratio of mean annual potential evaporation (Ep) to precipitation (P), capturing variation in runoff and vegetation cover. The river networks of these catchments are extracted, using a curvature-based method, from high-resolution (1 m) digital elevation models and several metrics such as drainage density, branching angle, and width functions are computed. We also use a multiscale-entropy-based approach to quantify the topologic irregularity and structural richness of these river networks. Our results reveal systematic impacts of climate forcing on the structure of river networks.

Designing a new cropping system for high productivity and sustainable water usage under climate change

NASA Astrophysics Data System (ADS)

Meng, Qingfeng; Wang, Hongfei; Yan, Peng; Pan, Junxiao; Lu, Dianjun; Cui, Zhenling; Zhang, Fusuo; Chen, Xinping

2017-02-01

The food supply is being increasingly challenged by climate change and water scarcity. However, incremental changes in traditional cropping systems have achieved only limited success in meeting these multiple challenges. In this study, we applied a systematic approach, using model simulation and data from two groups of field studies conducted in the North China Plain, to develop a new cropping system that improves yield and uses water in a sustainable manner. Due to significant warming, we identified a double-maize (M-M; Zea mays L.) cropping system that replaced the traditional winter wheat (Triticum aestivum L.) -summer maize system. The M-M system improved yield by 14-31% compared with the conventionally managed wheat-maize system, and achieved similar yield compared with the incrementally adapted wheat-maize system with the optimized cultivars, planting dates, planting density and water management. More importantly, water usage was lower in the M-M system than in the wheat-maize system, and the rate of water usage was sustainable (net groundwater usage was ≤150 mm yr-1). Our study indicated that systematic assessment of adaptation and cropping system scale have great potential to address the multiple food supply challenges under changing climatic conditions.

Evolution, biogeography, and systematics of Puriana: evolution and speciation in Ostracoda, III.

USGS Publications Warehouse

Cronin, T. M.

1987-01-01

Three types of geographic isolation - land barriers, deep water barriers, and climatic barriers - resulted in three distinct evolutionary responses in Neogene and Quaternary species of the epineritic ostracode genus Puriana. Through systematic, paleobiogeographic, and morphologic study of several hundred fossil and Recent populations from the eastern Pacific, western Atlantic, Gulf of Mexico, and the Caribbean, the phylogeny of the genus and the geography of speciation events were determined. Isolation of large populations by the Isthumus of Panama during the Pliocene did not lead to lineage splitting in species known to have existed before the Isthmus formed. Conversely, the establishment of small isolated populations on Caribbean islands by passive dispersal mechanisms frequently led to the evolution of new species or subspecies. Climatic changes along the southeastern United States during the Pliocene also catalyzed possible parapatric speciation as populations that immigrated to the northeastern periphery of the genus' range split to form new species. The results provide evidence that evolutionary models describing the influence of abiotic events on patterns of evolution and speciation can be tested using properly selected tectonic and climatic events and fossil groups amenable to species-level analysis. Two new species, P. bajaensis and P. paikensis, are described. -Author

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

DOE PAGES

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; ...

2017-01-01

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6.

NASA Technical Reports Server (NTRS)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Helene; Douville, Herve; Good, Peter; Kay, Jennifer E.;

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

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

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less

Bridging long proxy data time series and instrumental observation in the Virtual Institute of Integrated Climate and Landscape Evolution Analyses - ICLEA

NASA Astrophysics Data System (ADS)

Schwab, Markus J.; Brauer, Achim; Błaszkiewicz, Mirosław; Raab, Thomas; Wilmking, Martin

2015-04-01

Understanding causes and effects of present-day climate change on landscapes and the human habitat faces two main challenges, (i) too short time series of instrumental observation that do not cover the full range of variability since mechanisms of climate change and landscape evolution work on different time scales, which often not susceptible to human perception, and, (ii) distinct regional differences due to the location with respect to oceanic/continental climatic influences, the geological underground, and the history and intensity of anthropogenic land-use. Both challenges are central for the ICLEA research strategy and demand a high degree of interdisciplinary. In particular, the need to link observations and measurements of ongoing changes with information from the past taken from natural archives requires joint work of scientists with very different time perspectives. On the one hand, scientists that work at geological time scales of thousands and more years and, on the other hand, those observing and investigating recent processes at short time scales. The GFZ, Greifswald University and the Brandenburg University of Technology together with their partner the Polish Academy of Sciences strive for focusing their research capacities and expertise in ICLEA. ICLEA offers young researchers an interdisciplinary and structured education and promote their early independence through coaching and mentoring. Postdoctoral rotation positions at the ICLEA partner institutions ensure mobility of young researchers and promote dissemination of information and expertise between disciplines. Training, Research and Analytical workshops between research partners of the ICLEA virtual institute are another important measure to qualify young researchers. The long-term mission of the Virtual Institute is to provide a substantiated data basis for sustained environmental maintenance based on a profound process understanding at all relevant time scales. Aim is to explore processes of climate and landscape evolution in an historical cultural landscape extending from northeastern Germany into northwestern Poland. The northern-central European lowlands will be facilitated as a natural laboratory providing an ideal case for utilizing a systematic and holistic approach. In ICLEA five complementary work packages (WP) are established according to the key research aspects. WP 1 focused on monitoring mainly hydrology and soil moisture as well as meteorological parameters. WP 2 is linking present day and future monitoring data with the most recent past through analyzing satellite images. This WP will further provide larger spatial scales. WP 3-5 focus on different natural archives to obtain a broad variety of high quality proxy data. Tree rings provide sub-seasonal data for the last centuries up to few millennia, varved lake sediments cover the entire research time interval at seasonal to decadal resolution and palaeosoils and geomorphological features also cover the entire period but not continuously and with lower resolution. Complementary information, like climate, tree ecophysiological and limnological data etc., are provided by cooperation with associated partners. Further information about ICLEA: www.iclea.de

Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models

USGS Publications Warehouse

Romañach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.

2014-01-01

Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

Centennial-scale Holocene climate variations amplified by Antarctic Ice Sheet discharge

NASA Astrophysics Data System (ADS)

Bakker, Pepijn; Clark, Peter U.; Golledge, Nicholas R.; Schmittner, Andreas; Weber, Michael E.

2017-01-01

Proxy-based indicators of past climate change show that current global climate models systematically underestimate Holocene-epoch climate variability on centennial to multi-millennial timescales, with the mismatch increasing for longer periods. Proposed explanations for the discrepancy include ocean-atmosphere coupling that is too weak in models, insufficient energy cascades from smaller to larger spatial and temporal scales, or that global climate models do not consider slow climate feedbacks related to the carbon cycle or interactions between ice sheets and climate. Such interactions, however, are known to have strongly affected centennial- to orbital-scale climate variability during past glaciations, and are likely to be important in future climate change. Here we show that fluctuations in Antarctic Ice Sheet discharge caused by relatively small changes in subsurface ocean temperature can amplify multi-centennial climate variability regionally and globally, suggesting that a dynamic Antarctic Ice Sheet may have driven climate fluctuations during the Holocene. We analysed high-temporal-resolution records of iceberg-rafted debris derived from the Antarctic Ice Sheet, and performed both high-spatial-resolution ice-sheet modelling of the Antarctic Ice Sheet and multi-millennial global climate model simulations. Ice-sheet responses to decadal-scale ocean forcing appear to be less important, possibly indicating that the future response of the Antarctic Ice Sheet will be governed more by long-term anthropogenic warming combined with multi-centennial natural variability than by annual or decadal climate oscillations.

The Phenological Network of Catalonia: an historical perspective

NASA Astrophysics Data System (ADS)

Busto, Montserrat; Cunillera, Jordi; de Yzaguirre, Xavier

2017-04-01

The Meteorological Service of Catalonia (SMC) began systematic phenological observation in 1932. Forty-four observers registered the phenophases of 45 plant species, the first or last sighting of six bird species and the first sighting of one species of butterfly. The study First results of phenological observation in Catalonia was published in 1936, showing the different behaviour of the vegetal species and birds according to geographical location. The SMC worked against the military fascist uprising during the Spanish Civil War (1936-1939). Therefore, once the war was finished, the organisation was quickly closed by the Franco dictatorship and the National Meteorological Service became the official institution in Spain. This organization created the Spanish Phenological Network in 1943 following similar standards to the former Catalan network. The reintroduction of democracy and the return of the Catalan self-government structures (1977) allowed the re-foundation of the SMC in 1996. The Climatology Department needed phenological data to complement the study of climatic indicators and realised the fragile situation of phenology observations in Catalonia, with very few operational series. Following a preliminary analysis of the different systems of recording and saving data, the Phenological network of Catalonia (Fenocat) was re-established in 2013. Fenocat is an active partner of the Pan European Phenology Database (PEP725) that uses BBCH-scale coding and the USA National Phenology Network observation system. It is an example of citizen science. As at December 2016, Fenocat had recorded more than 450,000 data. The extension of summer climatic conditions in the Western Mediterranean region has resulted in repetition of phenopases in the same year, such as the second flowering of the holm oak (Quercus ilex), almond tree (Prunus dulcis) and sweet cherry tree (Prunus avium), or the delay in the departure data of the swallow (Hirundo rustica) and hoopoe (Upupa epops). Fenocat technicians are also involved in data rescue initiatives that allow the study of historical phenological series. The La Serra d'Almos (near Tarragona) phenological series is an example that shows the life cycle trends for plants and birds observed since 1971. The Phenological Network of Catalonia has marked a turning point in the recording of the rhythms of nature in Catalonia and works to preserve sensitive information for the study of climate change in the fragile Mediterranean ecosystem.

Climate Observations from Space

NASA Astrophysics Data System (ADS)

Briggs, Stephen

2016-07-01

The latest Global Climate Observing System (GCOS) Status Report on global climate observations, delivered to the UNFCCC COP21 in November 2016, showed how satellite data are critical for observations relating to climate. Of the 50 Essential Climate Variables (ECVs) identified by GCOS as necessary for understanding climate change, about half are derived only from satellite data while half of the remainder have a significant input from satellites. Hence data from Earth observing satellite systems are now a fundamental requirement for understanding the climate system and for managing the consequences of climate change. Following the Paris Agreement of COP21 this need is only greater. Not only will satellites have to continue to provide data for modelling and predicting climate change but also for a much wider range of actions relating to climate. These include better information on loss and damage, resilience, improved adaptation to change, and on mitigation including information on greenhouse gas emissions. In addition there is an emerging need for indicators of the risks associated with future climate change which need to be better quantified, allowing policy makers both to understand what decisions need to be taken, and to see the consequences of their actions. The presentation will set out some of the ways in which satellite data are important in all aspects of understanding, managing and predicting climate change and how they may be used to support future decisions by those responsible for policy related to managing climate change and its consequences.

Quantifying the clear-sky bias of satellite-derived infrared LST

NASA Astrophysics Data System (ADS)

Ermida, S. L.; Trigo, I. F.; DaCamara, C.

2017-12-01

Land surface temperature (LST) is one of the most relevant parameters when addressing the physical processes that take place at the surface of the Earth. Satellite data are particularly appropriate for measuring LST over the globe with high temporal resolution. Remote-sensed LST estimation from space-borne sensors has been systematically performed over the Globe for nearly 3 decades and geostationary LST climate data records are now available. The retrieval of LST from satellite observations generally relies on measurements in the thermal infrared (IR) window. Although there is a large number of IR sensors on-board geostationary satellites and polar orbiters suitable for LST retrievals with different temporal and spatial resolutions, the use of IR observations limits LST estimates to clear sky conditions. As a consequence, climate studies based on IR LST are likely to be affected by the restriction of LST data to cloudless conditions. However, such "clear sky bias" has never been quantified and, therefore, the actual impact of relying only on clear sky data is still to be determined. On the other hand, an "all-weather" global LST database may be set up based on passive microwave (MW) measurements which are much less affected by clouds. An 8-year record of all-weather MW LST is here used to quantify the clear-sky bias of IR LST at global scale based on MW observations performed by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) onboard NASA's Aqua satellite. Selection of clear-sky and cloudy pixels is based on information derived from measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the same satellite.

Association of climatic factors with infectious diseases in the Arctic and subarctic region – a systematic review

PubMed Central

Hedlund, Christina; Blomstedt, Yulia; Schumann, Barbara

2014-01-01

Background The Arctic and subarctic area are likely to be highly affected by climate change, with possible impacts on human health due to effects on food security and infectious diseases. Objectives To investigate the evidence for an association between climatic factors and infectious diseases, and to identify the most climate-sensitive diseases and vulnerable populations in the Arctic and subarctic region. Methods A systematic review was conducted. A search was made in PubMed, with the last update in May 2013. Inclusion criteria included human cases of infectious disease as outcome, climate or weather factor as exposure, and Arctic or subarctic areas as study origin. Narrative reviews, case reports, and projection studies were excluded. Abstracts and selected full texts were read and evaluated by two independent readers. A data collection sheet and an adjusted version of the SIGN methodology checklist were used to assess the quality grade of each article. Results In total, 1953 abstracts were initially found, of which finally 29 articles were included. Almost half of the studies were carried out in Canada (n=14), the rest from Sweden (n=6), Finland (n=4), Norway (n=2), Russia (n=2), and Alaska, US (n=1). Articles were analyzed by disease group: food- and waterborne diseases, vector-borne diseases, airborne viral- and airborne bacterial diseases. Strong evidence was found in our review for an association between climatic factors and food- and waterborne diseases. The scientific evidence for a link between climate and specific vector- and rodent-borne diseases was weak due to that only a few diseases being addressed in more than one publication, although several articles were of very high quality. Air temperature and humidity seem to be important climatic factors to investigate further for viral- and bacterial airborne diseases, but from our results no conclusion about a causal relationship could be drawn. Conclusions More studies of high quality are needed to investigate the adverse health impacts of weather and climatic factors in the Arctic and subarctic region. No studies from Greenland or Iceland were found, and only a few from Siberia and Alaska. Disease and syndromic surveillance should be part of climate change adaptation measures in the Arctic and subarctic regions, with monitoring of extreme weather events known to pose a risk for certain infectious diseases implemented at the community level. PMID:24990685

Association of climatic factors with infectious diseases in the Arctic and subarctic region--a systematic review.

PubMed

Hedlund, Christina; Blomstedt, Yulia; Schumann, Barbara

2014-01-01

The Arctic and subarctic area are likely to be highly affected by climate change, with possible impacts on human health due to effects on food security and infectious diseases. To investigate the evidence for an association between climatic factors and infectious diseases, and to identify the most climate-sensitive diseases and vulnerable populations in the Arctic and subarctic region. A systematic review was conducted. A search was made in PubMed, with the last update in May 2013. Inclusion criteria included human cases of infectious disease as outcome, climate or weather factor as exposure, and Arctic or subarctic areas as study origin. Narrative reviews, case reports, and projection studies were excluded. Abstracts and selected full texts were read and evaluated by two independent readers. A data collection sheet and an adjusted version of the SIGN methodology checklist were used to assess the quality grade of each article. In total, 1953 abstracts were initially found, of which finally 29 articles were included. Almost half of the studies were carried out in Canada (n=14), the rest from Sweden (n=6), Finland (n=4), Norway (n=2), Russia (n=2), and Alaska, US (n=1). Articles were analyzed by disease group: food- and waterborne diseases, vector-borne diseases, airborne viral- and airborne bacterial diseases. Strong evidence was found in our review for an association between climatic factors and food- and waterborne diseases. The scientific evidence for a link between climate and specific vector- and rodent-borne diseases was weak due to that only a few diseases being addressed in more than one publication, although several articles were of very high quality. Air temperature and humidity seem to be important climatic factors to investigate further for viral- and bacterial airborne diseases, but from our results no conclusion about a causal relationship could be drawn. More studies of high quality are needed to investigate the adverse health impacts of weather and climatic factors in the Arctic and subarctic region. No studies from Greenland or Iceland were found, and only a few from Siberia and Alaska. Disease and syndromic surveillance should be part of climate change adaptation measures in the Arctic and subarctic regions, with monitoring of extreme weather events known to pose a risk for certain infectious diseases implemented at the community level.

Toward a Global Horizontal and Vertical Elastic Load Deformation Model Derived from GRACE and GNSS Station Position Time Series

NASA Astrophysics Data System (ADS)

Chanard, Kristel; Fleitout, Luce; Calais, Eric; Rebischung, Paul; Avouac, Jean-Philippe

2018-04-01

We model surface displacements induced by variations in continental water, atmospheric pressure, and nontidal oceanic loading, derived from the Gravity Recovery and Climate Experiment (GRACE) for spherical harmonic degrees two and higher. As they are not observable by GRACE, we use at first the degree-1 spherical harmonic coefficients from Swenson et al. (2008, https://doi.org/10.1029/2007JB005338). We compare the predicted displacements with the position time series of 689 globally distributed continuous Global Navigation Satellite System (GNSS) stations. While GNSS vertical displacements are well explained by the model at a global scale, horizontal displacements are systematically underpredicted and out of phase with GNSS station position time series. We then reestimate the degree 1 deformation field from a comparison between our GRACE-derived model, with no a priori degree 1 loads, and the GNSS observations. We show that this approach reconciles GRACE-derived loading displacements and GNSS station position time series at a global scale, particularly in the horizontal components. Assuming that they reflect surface loading deformation only, our degree-1 estimates can be translated into geocenter motion time series. We also address and assess the impact of systematic errors in GNSS station position time series at the Global Positioning System (GPS) draconitic period and its harmonics on the comparison between GNSS and GRACE-derived annual displacements. Our results confirm that surface mass redistributions observed by GRACE, combined with an elastic spherical and layered Earth model, can be used to provide first-order corrections for loading deformation observed in both horizontal and vertical components of GNSS station position time series.

A quantitative evaluation of the public response to climate engineering

NASA Astrophysics Data System (ADS)

Wright, Malcolm J.; Teagle, Damon A. H.; Feetham, Pamela M.

2014-02-01

Atmospheric greenhouse gas concentrations continue to increase, with CO2 passing 400 parts per million in May 2013. To avoid severe climate change and the attendant economic and social dislocation, existing energy efficiency and emissions control initiatives may need support from some form of climate engineering. As climate engineering will be controversial, there is a pressing need to inform the public and understand their concerns before policy decisions are taken. So far, engagement has been exploratory, small-scale or technique-specific. We depart from past research to draw on the associative methods used by corporations to evaluate brands. A systematic, quantitative and comparative approach for evaluating public reaction to climate engineering is developed. Its application reveals that the overall public evaluation of climate engineering is negative. Where there are positive associations they favour carbon dioxide removal (CDR) over solar radiation management (SRM) techniques. Therefore, as SRM techniques become more widely known they are more likely to elicit negative reactions. Two climate engineering techniques, enhanced weathering and cloud brightening, have indistinct concept images and so are less likely to draw public attention than other CDR or SRM techniques.

A systematic review of the literature reveals trends and gaps in integrated pest management studies conducted in the United States.

PubMed

Young, Stephen L

2017-08-01

Integrated pest management (IPM) is a broad-based approach for addressing pests that negatively affect human and environmental health and economic profitability. Weeds, insects and disease-causing pathogens (diseases) are the pests most often associated with IPM. A systematic review, widely used in other scientific disciplines, was employed to determine the most commonly studied IPM topics and summarize the reasons for these trends and the gaps. In a field synopsis of the literature, 1679 relevant published papers were identified and categorized into one of the following five broad areas: IPM and organic (organic), climate change and pests (climate), rural and urban IPM (rural and urban), next-generation education (education) and advanced production systems (technology). Papers were examined in greater detail for at least one of the three main pests in a systematic review. A majority (85%) of IPM papers have been in the area of rural and urban IPM, primarily addressing agriculture (78%). Professionals, landowners and the general public were the focus of a majority (95%) of IPM papers on education. Technology is an increasing area of focus in the literature. Over the past 40 years, IPM papers have primarily (75%) addressed insects and been limited mostly to rural and urban settings. Climate change, technology and education specific to pest management studies are increasingly being published and will help broaden the focus that could result in increased adoption and development of IPM. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Test of the Constancy - Velocity Hypothesis: Navy Unit Functioning and Performance over 12 Years.

DTIC Science & Technology

1988-01-31

purpose of the United States Government. 17 COSATI CODES 18 SUEJECT T’ERMS C rinue an rev se f necess iy1 f da eao ms een- listment1111 Rate, Change of...38 Velocity, Climate Change , and Upgrade Rate 41 Joint Effects of Culture/Climate and Velocity 43 Conclusions about the Role Played by Velocity 44...which (a) examined change in organizational systems over time, (b) systematically tested different methodological approaches to organizational

Systematic errors in the simulation of the Asian summer monsoon: the role of rainfall variability on a range of time and space scales

NASA Astrophysics Data System (ADS)

Martin, Gill; Levine, Richard; Klingaman, Nicholas; Bush, Stephanie; Turner, Andrew; Woolnough, Steven

2015-04-01

Despite considerable efforts worldwide to improve model simulations of the Asian summer monsoon, significant biases still remain in climatological seasonal mean rainfall distribution, timing of the onset, and northward and eastward extent of the monsoon domain (Sperber et al., 2013). Many modelling studies have shown sensitivity to convection and boundary layer parameterization, cloud microphysics and land surface properties, as well as model resolution. Here we examine the problems in representing short-timescale rainfall variability (related to convection parameterization), problems in representing synoptic-scale systems such as monsoon depressions (related to model resolution), and the relationship of each of these with longer-term systematic biases. Analysis of the spatial distribution of rainfall intensity on a range of timescales ranging from ~30 minutes to daily, in the MetUM and in observations (where available), highlights how rainfall biases in the South Asian monsoon region on different timescales in different regions can be achieved in models through a combination of the incorrect frequency and/or intensity of rainfall. Over the Indian land area, the typical dry bias is related to sub-daily rainfall events being too infrequent, despite being too intense when they occur. In contrast, the wet bias regions over the equatorial Indian Ocean are mainly related to too frequent occurrence of lower-than-observed 3-hourly rainfall accumulations which result in too frequent occurrence of higher-than-observed daily rainfall accumulations. This analysis sheds light on the model deficiencies behind the climatological seasonal mean rainfall biases that many models exhibit in this region. Changing physical parameterizations alters this behaviour, with associated adjustments in the climatological rainfall distribution, although the latter is not always improved (Bush et al., 2014). This suggests a more complex interaction between the diabatic heating and the large-scale circulation than is indicated by the intensity and frequency of rainfall alone. Monsoon depressions and low pressure systems are important contributors to monsoon rainfall over central and northern India, areas where MetUM climate simulations typically show deficient monsoon rainfall. Analysis of MetUM climate simulations at resolutions ranging from N96 (~135km) to N512 (~25km) suggests that at lower resolution the numbers and intensities of monsoon depressions and low pressure systems and their associated rainfall are very low compared with re-analyses/observations. We show that there are substantial increases with horizontal resolution, but resolution is not the only factor. Idealised simulations, either using nudged atmospheric winds or initialised coupled hindcasts, which improve (strengthen) the mean state monsoon and cyclonic circulation over the Indian peninsula, also result in a substantial increase in monsoon depressions and associated rainfall. This suggests that a more realistic representation of monsoon depressions is possible even at lower resolution if the larger-scale systematic error pattern in the monsoon is improved.

Effects of climate change on temperature and salinity in the Yaquina Estuary, Oregon - September 2011

EPA Science Inventory

Since the Millennium Ecosystem Assessment (2005), numerous proposals regarding how to apply ecosystem services concepts in defined, systematic ways to support standards, accounting and assessment of ecosystems services have been made.

Climate impacts on human livelihoods: where uncertainty matters in projections of water availability

NASA Astrophysics Data System (ADS)

Lissner, T. K.; Reusser, D. E.; Schewe, J.; Lakes, T.; Kropp, J. P.

2014-03-01

Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target-measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models as well as greenhouse gas scenarios are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure Adequate Human livelihood conditions for wEll-being And Development (AHEAD). Based on a transdisciplinary sample of influential concepts addressing human well-being, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows identifying and differentiating uncertainty of climate and impact model projections. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions - and where it is not. The results indicate that in many countries today, livelihood conditions are compromised by water scarcity. However, more often, AHEAD fulfilment is limited through other elements. Moreover, the analysis shows that for 44 out of 111 countries, the water-specific uncertainty ranges are outside relevant thresholds for AHEAD, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy-decisions.

Climate impacts on human livelihoods: where uncertainty matters in projections of water availability

NASA Astrophysics Data System (ADS)

Lissner, T. K.; Reusser, D. E.; Schewe, J.; Lakes, T.; Kropp, J. P.

2014-10-01

Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models, as well as greenhouse gas scenarios, are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure what is referred to here as AHEAD (Adequate Human livelihood conditions for wEll-being And Development). Based on a trans-disciplinary sample of concepts addressing human well-being and livelihoods, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows for the uncertainty of climate and impact model projections to be identified and differentiated. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions - and where it is not. The results indicate that livelihood conditions are compromised by water scarcity in 34 countries. However, more often, AHEAD fulfilment is limited through other elements. The analysis shows that the water-specific uncertainty ranges of the model output are outside relevant thresholds for AHEAD for 65 out of 111 countries, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. In 46 of the countries in the analysis, water-specific uncertainty is relevant to AHEAD. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy decisions.

Future Climate CO2 Levels Mitigate Stress Impact on Plants: Increased Defense or Decreased Challenge?

PubMed Central

AbdElgawad, Hamada; Zinta, Gaurav; Beemster, Gerrit T. S.; Janssens, Ivan A.; Asard, Han

2016-01-01

Elevated atmospheric CO2 can stimulate plant growth by providing additional C (fertilization effect), and is observed to mitigate abiotic stress impact. Although, the mechanisms underlying the stress mitigating effect are not yet clear, increased antioxidant defenses, have been held primarily responsible (antioxidant hypothesis). A systematic literature analysis, including “all” papers [Web of Science (WoS)-cited], addressing elevated CO2 effects on abiotic stress responses and antioxidants (105 papers), confirms the frequent occurrence of the stress mitigation effect. However, it also demonstrates that, in stress conditions, elevated CO2 is reported to increase antioxidants, only in about 22% of the observations (e.g., for polyphenols, peroxidases, superoxide dismutase, monodehydroascorbate reductase). In most observations, under stress and elevated CO2 the levels of key antioxidants and antioxidant enzymes are reported to remain unchanged (50%, e.g., ascorbate peroxidase, catalase, ascorbate), or even decreased (28%, e.g., glutathione peroxidase). Moreover, increases in antioxidants are not specific for a species group, growth facility, or stress type. It seems therefore unlikely that increased antioxidant defense is the major mechanism underlying CO2-mediated stress impact mitigation. Alternative processes, probably decreasing the oxidative challenge by reducing ROS production (e.g., photorespiration), are therefore likely to play important roles in elevated CO2 (relaxation hypothesis). Such parameters are however rarely investigated in connection with abiotic stress relief. Understanding the effect of elevated CO2 on plant growth and stress responses is imperative to understand the impact of climate changes on plant productivity. PMID:27200030

Climate change and dengue: a critical and systematic review of quantitative modelling approaches

PubMed Central

2014-01-01

Background Many studies have found associations between climatic conditions and dengue transmission. However, there is a debate about the future impacts of climate change on dengue transmission. This paper reviewed epidemiological evidence on the relationship between climate and dengue with a focus on quantitative methods for assessing the potential impacts of climate change on global dengue transmission. Methods A literature search was conducted in October 2012, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search focused on peer-reviewed journal articles published in English from January 1991 through October 2012. Results Sixteen studies met the inclusion criteria and most studies showed that the transmission of dengue is highly sensitive to climatic conditions, especially temperature, rainfall and relative humidity. Studies on the potential impacts of climate change on dengue indicate increased climatic suitability for transmission and an expansion of the geographic regions at risk during this century. A variety of quantitative modelling approaches were used in the studies. Several key methodological issues and current knowledge gaps were identified through this review. Conclusions It is important to assemble spatio-temporal patterns of dengue transmission compatible with long-term data on climate and other socio-ecological changes and this would advance projections of dengue risks associated with climate change. PMID:24669859

Probabilistic seasonal Forecasts to deterministic Farm Leve Decisions: Innovative Approach

NASA Astrophysics Data System (ADS)

Mwangi, M. W.

2015-12-01

Climate change and vulnerability are major challenges in ensuring household food security. Climate information services have the potential to cushion rural households from extreme climate risks. However, most the probabilistic nature of climate information products is not easily understood by majority of smallholder farmers. Despite the probabilistic nature, climate information have proved to be a valuable climate risk adaptation strategy at the farm level. This calls for innovative ways to help farmers understand and apply climate information services to inform their farm level decisions. The study endeavored to co-design and test appropriate innovation systems for climate information services uptake and scale up necessary for achieving climate risk development. In addition it also determined the conditions necessary to support the effective performance of the proposed innovation system. Data and information sources included systematic literature review, secondary sources, government statistics, focused group discussions, household surveys and semi-structured interviews. Data wasanalyzed using both quantitative and qualitative data analysis techniques. Quantitative data was analyzed using the Statistical Package for Social Sciences (SPSS) software. Qualitative data was analyzed using qualitative techniques, which involved establishing the categories and themes, relationships/patterns and conclusions in line with the study objectives. Sustainable livelihood, reduced household poverty and climate change resilience were the impact that resulted from the study.

ICLEA - The Virtual Institute of Integrated Climate and Landscape Evolution Analyses

NASA Astrophysics Data System (ADS)

Schwab, Markus J.; Brauer, Achim; Błaszkiewicz, Mirosław; Blume, Theresa; Itzerott, Sibylle; Raab, Thomas; Wilmking, Martin; Iclea Team

2016-04-01

In the Virtual Institute ICLEA we view on past changes as natural experiments as a guidebook for better anticipation of future changes and their impacts. Since the natural evolution became increasingly superimposed by human impacts since the Neolithic we include an in-depth discussion of impacts of climate and environment change on societies and vice versa. The partner focusing their research capacities and expertise in ICLEA and offers young researchers an interdisciplinary and structured education and promote their early independence through coaching and mentoring. Training, Research and Analytical workshops between research partners of ICLEA are an important measure to qualify young researchers. Understanding causes and effects of present-day climate change on landscapes and the human habitat faces two main challenges, (I) too short time series of instrumental observation that do not cover the full range of variability since mechanisms of climate change and landscape evolution work on different time scales, which often not susceptible to human perception, and, (II) distinct regional differences due to the location with respect to oceanic/continental climatic influences, the geological underground, and the history and intensity of anthropogenic land-use. Both challenges are central for the ICLEA research strategy and demand a high degree of interdisciplinary. In particular, the need to link observations and measurements of ongoing changes with information from the past taken from natural archives requires joint work of scientists with very different time perspectives. On the one hand, scientists that work at geological time scales of thousands and more years and, on the other hand, those observing and investigating recent processes at short time scales. The long-term mission of the Virtual Institute is to provide a substantiated data basis for sustained environmental maintenance based on a profound process understanding at all relevant time scales. Aim is to explore processes of climate and landscape evolution in an historical cultural landscape extending from northeastern Germany into northwestern Poland. The northern-central European lowlands will be facilitated as a natural laboratory providing an ideal case for utilizing a systematic and holistic approach. Five complementary work packages (WP) are established according to the key research aspects: WP 1 focused on monitoring mainly hydrology and soil moisture as well as meteorological parameters. WP 2 is linking present day and future monitoring data with the most recent past through analyzing satellite images. This WP will further provide larger spatial scales. WP 3-5 are focused on different natural archives to obtain a broad variety of high quality proxy data. Tree rings provide sub-seasonal data for the last centuries up to few millennia, varved lake sediments cover the entire research time interval at seasonal to decadal resolution and palaeosoils and geomorphological features also cover the entire period but not continuously and with lower resolution. Complementary information, like climate, tree ecophysiological and limnological data etc., are provided by cooperation with associated partners. Further information about ICLEA: www.iclea.de

Methodological challenges to bridge the gap between regional climate and hydrology models

NASA Astrophysics Data System (ADS)

Bozhinova, Denica; José Gómez-Navarro, Juan; Raible, Christoph; Felder, Guido

2017-04-01

The frequency and severity of floods worldwide, together with their impacts, are expected to increase under climate change scenarios. It is therefore very important to gain insight into the physical mechanisms responsible for such events in order to constrain the associated uncertainties. Model simulations of the climate and hydrological processes are important tools that can provide insight in the underlying physical processes and thus enable an accurate assessment of the risks. Coupled together, they can provide a physically consistent picture that allows to assess the phenomenon in a comprehensive way. However, climate and hydrological models work at different temporal and spatial scales, so there are a number of methodological challenges that need to be carefully addressed. An important issue pertains the presence of biases in the simulation of precipitation. Climate models in general, and Regional Climate models (RCMs) in particular, are affected by a number of systematic biases that limit their reliability. In many studies, prominently the assessment of changes due to climate change, such biases are minimised by applying the so-called delta approach, which focuses on changes disregarding absolute values that are more affected by biases. However, this approach is not suitable in this scenario, as the absolute value of precipitation, rather than the change, is fed into the hydrological model. Therefore, bias has to be previously removed, being this a complex matter where various methodologies have been proposed. In this study, we apply and discuss the advantages and caveats of two different methodologies that correct the simulated precipitation to minimise differences with respect an observational dataset: a linear fit (FIT) of the accumulated distributions and Quantile Mapping (QM). The target region is Switzerland, and therefore the observational dataset is provided by MeteoSwiss. The RCM is the Weather Research and Forecasting model (WRF), driven at the boundaries by the Community Earth System Model (CESM). The raw simulation driven by CESM exhibit prominent biases that stand out in the evolution of the annual cycle and demonstrate that the correction of biases is mandatory in this type of studies, rather than a minor correction that might be neglected. The simulation spans the period 1976 - 2005, although the application of the correction is carried out on a daily basis. Both methods lead to a corrected field of precipitation that respects the temporal evolution of the simulated precipitation, at the same time that mimics the distribution of precipitation according to the one in the observations. Due to the nature of the two methodologies, there are important differences between the products of both corrections, that lead to dataset with different properties. FIT is generally more accurate regarding the reproduction of the tails of the distribution, i.e. extreme events, whereas the nature of QM renders it a general-purpose correction whose skill is equally distributed across the full distribution of precipitation, including central values.

Performance modeling for A-SCOPE: a space-borne lidar measuring atmospheric CO2

NASA Astrophysics Data System (ADS)

Caron, Jérôme; Durand, Yannig; Bezy, Jean-Loup; Meynart, Roland

2009-09-01

A-SCOPE (Advanced Space Carbon and Climate Observation of Planet Earth) has been one of the six candidates for the third cycle of the Earth Explorer Core missions, selected by the European Space Agency (ESA) for assessment studies. Earth Explorer missions focus on the science and research aspects of ESA's Living Planet Programme. A-SCOPE mission aims at observing atmospheric CO2 for a better understanding of the carbon cycle. Knowledge about the spatial distribution of sources and sinks of CO2 with unprecedented accuracy will provide urgently needed information about the global carbon cycle. A-SCOPE mission encompasses a new approach to observe the Earth from space based on an IPDA (Integrated Path Differential Absorption) Lidar. Based on the known principle of a differential measurement technique, the IPDA lidar relies on the measurement of the laser echoes reflected by hard targets as the ground or the top of the vegetation. Such a time-gated technique is a promising way to overcome the sources of systematic errors inherent to passive missions. To be fully exploited, it however translates into stringent instrument requirements and requires a dedicated performance assessment. In this paper, the A-SCOPE instrument concept is first presented, with the aim of summarizing some important outcomes from the industrial assessment studies. After a discussion of the mission requirements and measurement principles, an overview is given about the instrument architecture. Then the instrument performance is reported, together with a detailed discussion about sources of systematic errors, which pose the strongest technical challenges.

Mechanisms of elevation-dependent warming over complex terrain in high-resolution simulations of regional climate change

NASA Astrophysics Data System (ADS)

Minder, J. R.; Letcher, T.; Liu, C.

2016-12-01

Numerous observational and modeling studies have suggested that over mountainous terrain certain elevations can experience systematically enhanced rates of near-surface climate warming relative to the surrounding region, a phenomenon referred to as elevation-dependent warming (EDW). In many of these studies high-elevation locations were found to experience the fastest warming rates. A variety of physical mechanisms for EDW have been proposed but there is no consensus as to the dominant cause. We examine EDW in regional climate model (RCM) simulations with very high horizontal resolution (4-km horizontal grid). The simulation domain centers on the Rocky Mountains and intermountain west of the United States. Climate change simulations are conducted using the "pseudo global warming" framework to focus on the regional response to large-scale thermodynamic and radiative climate changes representative of mid-century anthropogenic global climate change. Substantial EDW is found in these simulations. Warming varies with elevation by up to 1°C depending on the season considered. The structure of EDW is only weakly sensitive to variations in horizontal grid spacing ranging from 4 to 36 km. The snow-albedo feedback (SAF) plays a major role in causing the simulated EDW. The elevation band of maximum warming varies seasonally, mostly following the margin of the seasonal snowpack where snow cover and albedo reductions are maximized under climate warming. Additional simulations where the SAF is artificially suppressed demonstrate that EDW variations of up to 0.6°C can be attributed to the SAF. Simulations with a suppressed SAF still exhibit EDW variations up to 0.8°C that must be explained by other mechanisms. This remaining EDW shows a near linear increase in warming with elevation in most months and does not appear to be inherited from the profile of large-scale free-tropospheric warming. Simple theoretical calculations suggest that the non-linear dependence of surface emission on temperature offers one promising mechanism. The role of water vapor and cloud feedbacks are also considered as alternative mechanisms.

Educational and Scientific Applications of Climate Model Diagnostic Analyzer

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Zhang, J.; Bao, Q.

2016-12-01

Climate Model Diagnostic Analyzer (CMDA) is a web-based information system designed for the climate modeling and model analysis community to analyze climate data from models and observations. CMDA provides tools to diagnostically analyze climate data for model validation and improvement, and to systematically manage analysis provenance for sharing results with other investigators. CMDA utilizes cloud computing resources, multi-threading computing, machine-learning algorithms, web service technologies, and provenance-supporting technologies to address technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. As CMDA infrastructure and technology have matured, we have developed the educational and scientific applications of CMDA. Educationally, CMDA supported the summer school of the JPL Center for Climate Sciences for three years since 2014. In the summer school, the students work on group research projects where CMDA provide datasets and analysis tools. Each student is assigned to a virtual machine with CMDA installed in Amazon Web Services. A provenance management system for CMDA is developed to keep track of students' usages of CMDA, and to recommend datasets and analysis tools for their research topic. The provenance system also allows students to revisit their analysis results and share them with their group. Scientifically, we have developed several science use cases of CMDA covering various topics, datasets, and analysis types. Each use case developed is described and listed in terms of a scientific goal, datasets used, the analysis tools used, scientific results discovered from the use case, an analysis result such as output plots and data files, and a link to the exact analysis service call with all the input arguments filled. For example, one science use case is the evaluation of NCAR CAM5 model with MODIS total cloud fraction. The analysis service used is Difference Plot Service of Two Variables, and the datasets used are NCAR CAM total cloud fraction and MODIS total cloud fraction. The scientific highlight of the use case is that the CAM5 model overall does a fairly decent job at simulating total cloud cover, though simulates too few clouds especially near and offshore of the eastern ocean basins where low clouds are dominant.

Remote sensing of ocean surface currents: a review of what is being observed and what is being assimilated

NASA Astrophysics Data System (ADS)

Isern-Fontanet, Jordi; Ballabrera-Poy, Joaquim; Turiel, Antonio; García-Ladona, Emilio

2017-10-01

Ocean currents play a key role in Earth's climate - they impact almost any process taking place in the ocean and are of major importance for navigation and human activities at sea. Nevertheless, their observation and forecasting are still difficult. First, no observing system is able to provide direct measurements of global ocean currents on synoptic scales. Consequently, it has been necessary to use sea surface height and sea surface temperature measurements and refer to dynamical frameworks to derive the velocity field. Second, the assimilation of the velocity field into numerical models of ocean circulation is difficult mainly due to lack of data. Recent experiments that assimilate coastal-based radar data have shown that ocean currents will contribute to increasing the forecast skill of surface currents, but require application in multidata assimilation approaches to better identify the thermohaline structure of the ocean. In this paper we review the current knowledge in these fields and provide a global and systematic view of the technologies to retrieve ocean velocities in the upper ocean and the available approaches to assimilate this information into ocean models.

The effects of climate downscaling technique and observational data set on modeled ecological responses

Treesearch

Afshin Pourmokhtarian; Charles T. Driscoll; John L. Campbell; Katharine Hayhoe; Anne M. K. Stoner

2016-01-01

Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training...

How does climate change cause extinction?

PubMed Central

Cahill, Abigail E.; Aiello-Lammens, Matthew E.; Fisher-Reid, M. Caitlin; Hua, Xia; Karanewsky, Caitlin J.; Yeong Ryu, Hae; Sbeglia, Gena C.; Spagnolo, Fabrizio; Waldron, John B.; Warsi, Omar; Wiens, John J.

2013-01-01

Anthropogenic climate change is predicted to be a major cause of species extinctions in the next 100 years. But what will actually cause these extinctions? For example, will it be limited physiological tolerance to high temperatures, changing biotic interactions or other factors? Here, we systematically review the proximate causes of climate-change related extinctions and their empirical support. We find 136 case studies of climatic impacts that are potentially relevant to this topic. However, only seven identified proximate causes of demonstrated local extinctions due to anthropogenic climate change. Among these seven studies, the proximate causes vary widely. Surprisingly, none show a straightforward relationship between local extinction and limited tolerances to high temperature. Instead, many studies implicate species interactions as an important proximate cause, especially decreases in food availability. We find very similar patterns in studies showing decreases in abundance associated with climate change, and in those studies showing impacts of climatic oscillations. Collectively, these results highlight our disturbingly limited knowledge of this crucial issue but also support the idea that changing species interactions are an important cause of documented population declines and extinctions related to climate change. Finally, we briefly outline general research strategies for identifying these proximate causes in future studies. PMID:23075836

Invertebrates, ecosystem services and climate change.

PubMed

Prather, Chelse M; Pelini, Shannon L; Laws, Angela; Rivest, Emily; Woltz, Megan; Bloch, Christopher P; Del Toro, Israel; Ho, Chuan-Kai; Kominoski, John; Newbold, T A Scott; Parsons, Sheena; Joern, A

2013-05-01

The sustainability of ecosystem services depends on a firm understanding of both how organisms provide these services to humans and how these organisms will be altered with a changing climate. Unquestionably a dominant feature of most ecosystems, invertebrates affect many ecosystem services and are also highly responsive to climate change. However, there is still a basic lack of understanding of the direct and indirect paths by which invertebrates influence ecosystem services, as well as how climate change will affect those ecosystem services by altering invertebrate populations. This indicates a lack of communication and collaboration among scientists researching ecosystem services and climate change effects on invertebrates, and land managers and researchers from other disciplines, which becomes obvious when systematically reviewing the literature relevant to invertebrates, ecosystem services, and climate change. To address this issue, we review how invertebrates respond to climate change. We then review how invertebrates both positively and negatively influence ecosystem services. Lastly, we provide some critical future directions for research needs, and suggest ways in which managers, scientists and other researchers may collaborate to tackle the complex issue of sustaining invertebrate-mediated services under a changing climate. © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society.

Uncertainty in Simulating Wheat Yields Under Climate Change

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.;

How does climate change cause extinction?

PubMed

Cahill, Abigail E; Aiello-Lammens, Matthew E; Fisher-Reid, M Caitlin; Hua, Xia; Karanewsky, Caitlin J; Ryu, Hae Yeong; Sbeglia, Gena C; Spagnolo, Fabrizio; Waldron, John B; Warsi, Omar; Wiens, John J

2013-01-07

Anthropogenic climate change is predicted to be a major cause of species extinctions in the next 100 years. But what will actually cause these extinctions? For example, will it be limited physiological tolerance to high temperatures, changing biotic interactions or other factors? Here, we systematically review the proximate causes of climate-change related extinctions and their empirical support. We find 136 case studies of climatic impacts that are potentially relevant to this topic. However, only seven identified proximate causes of demonstrated local extinctions due to anthropogenic climate change. Among these seven studies, the proximate causes vary widely. Surprisingly, none show a straightforward relationship between local extinction and limited tolerances to high temperature. Instead, many studies implicate species interactions as an important proximate cause, especially decreases in food availability. We find very similar patterns in studies showing decreases in abundance associated with climate change, and in those studies showing impacts of climatic oscillations. Collectively, these results highlight our disturbingly limited knowledge of this crucial issue but also support the idea that changing species interactions are an important cause of documented population declines and extinctions related to climate change. Finally, we briefly outline general research strategies for identifying these proximate causes in future studies.

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

DOE PAGES

Tramontana, Gianluca; Jung, Martin; Schwalm, Christopher R.; ...

2016-07-29

Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data andmore » (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange ( R 2 < 0.5), ecosystem respiration ( R 2 > 0.6), gross primary production ( R 2> 0.7), latent heat ( R 2 > 0.7), sensible heat ( R 2 > 0.7), and net radiation ( R 2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well ( R 2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted ( R 2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). Finally, the evaluated large ensemble of ML-based models will be the basis of new global flux products.« less

Antarctic ice sheet mass loss estimates using Modified Antarctic Mapping Mission surface flow observations

NASA Astrophysics Data System (ADS)

Ren, Diandong; Leslie, Lance M.; Lynch, Mervyn J.

2013-03-01

The long residence time of ice and the relatively gentle slopes of the Antarctica Ice Sheet make basal sliding a unique positive feedback mechanism in enhancing ice discharge along preferred routes. The highly organized ice stream channels extending to the interior from the lower reach of the outlets are a manifestation of the role of basal granular material in enhancing the ice flow. In this study, constraining the model-simulated year 2000 ice flow fields with surface velocities obtained from InSAR measurements permits retrieval of the basal sliding parameters. Forward integrations of the ice model driven by atmospheric and oceanic parameters from coupled general circulation models under different emission scenarios provide a range of estimates of total ice mass loss during the 21st century. The total mass loss rate has a small intermodel and interscenario spread, rising from approximately -160 km3/yr at present to approximately -220 km3/yr by 2100. The accelerated mass loss rate of the Antarctica Ice Sheet in a warming climate is due primarily to a dynamic response in the form of an increase in ice flow speed. Ice shelves contribute to this feedback through a reduced buttressing effect due to more frequent systematic, tabular calving events. For example, by 2100 the Ross Ice Shelf is projected to shed 40 km3 during each systematic tabular calving. After the frontal section's attrition, the remaining shelf will rebound. Consequently, the submerged cross-sectional area will reduce, as will the buttressing stress. Longitudinal differential warming of ocean temperature contributes to tabular calving. Because of the prevalence of fringe ice shelves, oceanic effects likely will play a very important role in the future mass balance of the Antarctica Ice Sheet, under a possible future warming climate.

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

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

Tramontana, Gianluca; Jung, Martin; Schwalm, Christopher R.

Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data andmore » (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange ( R 2 < 0.5), ecosystem respiration ( R 2 > 0.6), gross primary production ( R 2> 0.7), latent heat ( R 2 > 0.7), sensible heat ( R 2 > 0.7), and net radiation ( R 2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well ( R 2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted ( R 2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). Finally, the evaluated large ensemble of ML-based models will be the basis of new global flux products.« less

Probabilistic attribution of individual unprecedented extreme events

NASA Astrophysics Data System (ADS)

Diffenbaugh, N. S.

2016-12-01

The last decade has seen a rapid increase in efforts to understand the influence of global warming on individual extreme climate events. Although trends in the distributions of climate observations have been thoroughly analyzed, rigorously quantifying the contribution of global-scale warming to individual events that are unprecedented in the observed record presents a particular challenge. This paper describes a method for leveraging observations and climate model ensembles to quantify the influence of historical global warming on the severity and probability of unprecedented events. This approach uses formal inferential techniques to quantify four metrics: (1) the contribution of the observed trend to the event magnitude, (2) the contribution of the observed trend to the event probability, (3) the probability of the observed trend in the current climate and a climate without human influence, and (4) the probability of the event magnitude in the current climate and a climate without human influence. Illustrative examples are presented, spanning a range of climate variables, timescales, and regions. These examples illustrate that global warming can influence the severity and probability of unprecedented extremes. In some cases - particularly high temperatures - this change is indicated by changes in the mean. However, changes in probability do not always arise from changes in the mean, suggesting that global warming can alter the frequency with which complex physical conditions co-occur. Because our framework is transparent and highly generalized, it can be readily applied to a range of climate events, regions, and levels of climate forcing.

Research on Climate and Dengue in Malaysia: A Systematic Review.

PubMed

Hii, Yien Ling; Zaki, Rafdzah Ahmad; Aghamohammadi, Nasrin; Rocklöv, Joacim

2016-03-01

Dengue is a climate-sensitive infectious disease. Climate-based dengue early warning may be a simple, low-cost, and effective tool for enhancing surveillance and control. Scientific studies on climate and dengue in local context form the basis for advancing the development of a climate-based early warning system. This study aims to review the current status of scientific studies in climate and dengue and the prospect or challenges of such research on a climate-based dengue early warning system in a dengue-endemic country, taking Malaysia as a case study. We reviewed the relationship between climate and dengue derived from statistical modeling, laboratory tests, and field studies. We searched electronic databases including PubMed, Scopus, EBSCO (MEDLINE), Web of Science, and the World Health Organization publications, and assessed climate factors and their influence on dengue cases, mosquitoes, and virus and recent development in the field of climate and dengue. Few studies in Malaysia have emphasized the relationship between climate and dengue. Climatic factors such as temperature, rainfall, and humidity are associated with dengue; however, these relationships were not consistent. Climate change projections for Malaysia show a mounting risk for dengue in the future. Scientific studies on climate and dengue enhance dengue surveillance in the long run. It is essential for institutions in Malaysia to promote research on climate and vector-borne diseases to advance the development of climate-based early warning systems. Together, effective strategies that improve existing research capacity, maximize the use of limited resources, and promote local-international partnership are crucial for sustaining research on climate and health.

Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

NASA Technical Reports Server (NTRS)

Thiele, O. (Editor); Schiffer, R. A. (Editor)

1985-01-01

The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.

Challenges in the analysis of complex systems: introduction and overview

NASA Astrophysics Data System (ADS)

Hastings, Harold M.; Davidsen, Jörn; Leung, Henry

2017-12-01

One of the main challenges of modern physics is to provide a systematic understanding of systems far from equilibrium exhibiting emergent behavior. Prominent examples of such complex systems include, but are not limited to the cardiac electrical system, the brain, the power grid, social systems, material failure and earthquakes, and the climate system. Due to the technological advances over the last decade, the amount of observations and data available to characterize complex systems and their dynamics, as well as the capability to process that data, has increased substantially. The present issue discusses a cross section of the current research on complex systems, with a focus on novel experimental and data-driven approaches to complex systems that provide the necessary platform to model the behavior of such systems.

A Regional Climate Model Evaluation System based on contemporary Satellite and other Observations for Assessing Regional Climate Model Fidelity

NASA Astrophysics Data System (ADS)

Waliser, D. E.; Kim, J.; Mattman, C.; Goodale, C.; Hart, A.; Zimdars, P.; Lean, P.

2011-12-01

Evaluation of climate models against observations is an essential part of assessing the impact of climate variations and change on regionally important sectors and improving climate models. Regional climate models (RCMs) are of a particular concern. RCMs provide fine-scale climate needed by the assessment community via downscaling global climate model projections such as those contributing to the Coupled Model Intercomparison Project (CMIP) that form one aspect of the quantitative basis of the IPCC Assessment Reports. The lack of reliable fine-resolution observational data and formal tools and metrics has represented a challenge in evaluating RCMs. Recent satellite observations are particularly useful as they provide a wealth of information and constraints on many different processes within the climate system. Due to their large volume and the difficulties associated with accessing and using contemporary observations, however, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL and UCLA have developed the Regional Climate Model Evaluation System (RCMES) to help make satellite observations, in conjunction with in-situ and reanalysis datasets, more readily accessible to the regional modeling community. The system includes a central database (Regional Climate Model Evaluation Database: RCMED) to store multiple datasets in a common format and codes for calculating and plotting statistical metrics to assess model performance (Regional Climate Model Evaluation Tool: RCMET). This allows the time taken to compare model data with satellite observations to be reduced from weeks to days. RCMES is a component of the recent ExArch project, an international effort for facilitating the archive and access of massive amounts data for users using cloud-based infrastructure, in this case as applied to the study of climate and climate change. This presentation will describe RCMES and demonstrate its utility using examples from RCMs applied to the southwest US as well as to Africa based on output from the CORDEX activity. Application of RCMES to the evaluation of multi-RCM hindcast for CORDEX-Africa will be presented in a companion paper in A41.

Process-oriented Observational Metrics for CMIP6 Climate Model Assessments

NASA Astrophysics Data System (ADS)

Jiang, J. H.; Su, H.

2016-12-01

Observational metrics based on satellite observations have been developed and effectively applied during post-CMIP5 model evaluation and improvement projects. As new physics and parameterizations continue to be included in models for the upcoming CMIP6, it is important to continue objective comparisons between observations and model results. This talk will summarize the process-oriented observational metrics and methodologies for constraining climate models with A-Train satellite observations and support CMIP6 model assessments. We target parameters and processes related to atmospheric clouds and water vapor, which are critically important for Earth's radiative budget, climate feedbacks, and water and energy cycles, and thus reduce uncertainties in climate models.

Rising temperatures reduce global wheat production

USDA-ARS?s Scientific Manuscript database

Crop models are essential to assess the threat of climate change for food production but have not been systematically tested against temperature experiments, despite demonstrated uncertainty in temperature response. Herein, we compare 30 different wheat crop models against field experiments in which...

Carbon cycle observations: gaps threaten climate mitigation policies

Treesearch

Richard Birdsey; Nick Bates; MIke Behrenfeld; Kenneth Davis; Scott C. Doney; Richard Feely; Dennis Hansell; Linda Heath; et al.

2009-01-01

Successful management of carbon dioxide (CO2) requires robust and sustained carbon cycle observations. Yet key elements of a national observation network are lacking or at risk. A U.S. National Research Council review of the U.S. Climate Change Science Program earlier this year highlighted the critical need for a U.S. climate observing system to...

Mitigating and adapting to climate change: multi-functional and multi-scale assessment of green urban infrastructure.

PubMed

Demuzere, M; Orru, K; Heidrich, O; Olazabal, E; Geneletti, D; Orru, H; Bhave, A G; Mittal, N; Feliu, E; Faehnle, M

2014-12-15

In order to develop climate resilient urban areas and reduce emissions, several opportunities exist starting from conscious planning and design of green (and blue) spaces in these landscapes. Green urban infrastructure has been regarded as beneficial, e.g. by balancing water flows, providing thermal comfort. This article explores the existing evidence on the contribution of green spaces to climate change mitigation and adaptation services. We suggest a framework of ecosystem services for systematizing the evidence on the provision of bio-physical benefits (e.g. CO2 sequestration) as well as social and psychological benefits (e.g. improved health) that enable coping with (adaptation) or reducing the adverse effects (mitigation) of climate change. The multi-functional and multi-scale nature of green urban infrastructure complicates the categorization of services and benefits, since in reality the interactions between various benefits are manifold and appear on different scales. We will show the relevance of the benefits from green urban infrastructures on three spatial scales (i.e. city, neighborhood and site specific scales). We will further report on co-benefits and trade-offs between the various services indicating that a benefit could in turn be detrimental in relation to other functions. The manuscript identifies avenues for further research on the role of green urban infrastructure, in different types of cities, climates and social contexts. Our systematic understanding of the bio-physical and social processes defining various services allows targeting stressors that may hamper the provision of green urban infrastructure services in individual behavior as well as in wider planning and environmental management in urban areas. Copyright © 2014 Elsevier Ltd. All rights reserved.

A diagram for evaluating multiple aspects of model performance in simulating vector fields

NASA Astrophysics Data System (ADS)

Xu, Zhongfeng; Hou, Zhaolu; Han, Ying; Guo, Weidong

2016-12-01

Vector quantities, e.g., vector winds, play an extremely important role in climate systems. The energy and water exchanges between different regions are strongly dominated by wind, which in turn shapes the regional climate. Thus, how well climate models can simulate vector fields directly affects model performance in reproducing the nature of a regional climate. This paper devises a new diagram, termed the vector field evaluation (VFE) diagram, which is a generalized Taylor diagram and able to provide a concise evaluation of model performance in simulating vector fields. The diagram can measure how well two vector fields match each other in terms of three statistical variables, i.e., the vector similarity coefficient, root mean square length (RMSL), and root mean square vector difference (RMSVD). Similar to the Taylor diagram, the VFE diagram is especially useful for evaluating climate models. The pattern similarity of two vector fields is measured by a vector similarity coefficient (VSC) that is defined by the arithmetic mean of the inner product of normalized vector pairs. Examples are provided, showing that VSC can identify how close one vector field resembles another. Note that VSC can only describe the pattern similarity, and it does not reflect the systematic difference in the mean vector length between two vector fields. To measure the vector length, RMSL is included in the diagram. The third variable, RMSVD, is used to identify the magnitude of the overall difference between two vector fields. Examples show that the VFE diagram can clearly illustrate the extent to which the overall RMSVD is attributed to the systematic difference in RMSL and how much is due to the poor pattern similarity.

Organizational climate and employee mental health outcomes: A systematic review of studies in health care organizations.

PubMed

Bronkhorst, Babette; Tummers, Lars; Steijn, Bram; Vijverberg, Dominique

2015-01-01

In recent years, the high prevalence of mental health problems among health care workers has given rise to great concern. The academic literature suggests that employees' perceptions of their work environment can play a role in explaining mental health outcomes. We conducted a systematic review of the literature in order to answer the following two research questions: (1) how does organizational climate relate to mental health outcomes among employees working in health care organizations and (2) which organizational climate dimension is most strongly related to mental health outcomes among employees working in health care organizations? Four search strategies plus inclusion and quality assessment criteria were applied to identify and select eligible studies. As a result, 21 studies were included in the review. Data were extracted from the studies to create a findings database. The contents of the studies were analyzed and categorized according to common characteristics. Perceptions of a good organizational climate were significantly associated with positive employee mental health outcomes such as lower levels of burnout, depression, and anxiety. More specifically, our findings indicate that group relationships between coworkers are very important in explaining the mental health of health care workers. There is also evidence that aspects of leadership and supervision affect mental health outcomes. Relationships between communication, or participation, and mental health outcomes were less clear. If health care organizations want to address mental health issues among their staff, our findings suggest that organizations will benefit from incorporating organizational climate factors in their health and safety policies. Stimulating a supportive atmosphere among coworkers and developing relationship-oriented leadership styles would seem to be steps in the right direction.

Application of GRACE for Monitoring Groundwater in Data Scarce Regions

NASA Technical Reports Server (NTRS)

Rodell, Matt; Li, Bailing; Famiglietti, Jay; Zaitchik, Ben

2012-01-01

In the United States, groundwater storage is somewhat well monitored (spatial and temporal data gaps notwithstanding) and abundant data are freely and easily accessible. Outside of the U.S., groundwater often is not monitored systematically and where it is the data are rarely centralized and made available. Since 2002 the Gravity Recovery and Climate Experiment (GRACE) satellite mission has delivered gravity field observations which have been used to infer variations in total terrestrial water storage, including groundwater, at regional to continental scales. Challenges to using GRACE for groundwater monitoring include its relatively coarse spatial and temporal resolutions, its inability to differentiate groundwater from other types of water on and under the land surface, and typical 2-3 month data latency. Data assimilation can be used to overcome these challenges, but uncertainty in the results remains and is difficult to quantify without independent observations. Nevertheless, the results are preferable to the alternative - no data at all- and GRACE has already revealed groundwater variability and trends in regions where only anecdotal evidence existed previously.

A review of downscaling procedures - a contribution to the research on climate change impacts at city scale

NASA Astrophysics Data System (ADS)

Smid, Marek; Costa, Ana; Pebesma, Edzer; Granell, Carlos; Bhattacharya, Devanjan

2016-04-01

Human kind is currently predominantly urban based, and the majority of ever continuing population growth will take place in urban agglomerations. Urban systems are not only major drivers of climate change, but also the impact hot spots. Furthermore, climate change impacts are commonly managed at city scale. Therefore, assessing climate change impacts on urban systems is a very relevant subject of research. Climate and its impacts on all levels (local, meso and global scale) and also the inter-scale dependencies of those processes should be a subject to detail analysis. While global and regional projections of future climate are currently available, local-scale information is lacking. Hence, statistical downscaling methodologies represent a potentially efficient way to help to close this gap. In general, the methodological reviews of downscaling procedures cover the various methods according to their application (e.g. downscaling for the hydrological modelling). Some of the most recent and comprehensive studies, such as the ESSEM COST Action ES1102 (VALUE), use the concept of Perfect Prog and MOS. Other examples of classification schemes of downscaling techniques consider three main categories: linear methods, weather classifications and weather generators. Downscaling and climate modelling represent a multidisciplinary field, where researchers from various backgrounds intersect their efforts, resulting in specific terminology, which may be somewhat confusing. For instance, the Polynomial Regression (also called the Surface Trend Analysis) is a statistical technique. In the context of the spatial interpolation procedures, it is commonly classified as a deterministic technique, and kriging approaches are classified as stochastic. Furthermore, the terms "statistical" and "stochastic" (frequently used as names of sub-classes in downscaling methodological reviews) are not always considered as synonymous, even though both terms could be seen as identical since they are referring to methods handling input modelling factors as variables with certain probability distributions. In addition, the recent development is going towards multi-step methodologies containing deterministic and stochastic components. This evolution leads to the introduction of new terms like hybrid or semi-stochastic approaches, which makes the efforts to systematically classifying downscaling methods to the previously defined categories even more challenging. This work presents a review of statistical downscaling procedures, which classifies the methods in two steps. In the first step, we describe several techniques that produce a single climatic surface based on observations. The methods are classified into two categories using an approximation to the broadest consensual statistical terms: linear and non-linear methods. The second step covers techniques that use simulations to generate alternative surfaces, which correspond to different realizations of the same processes. Those simulations are essential because there is a limited number of real observational data, and such procedures are crucial for modelling extremes. This work emphasises the link between statistical downscaling methods and the research of climate change impacts at city scale.