Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

2015-12-01

Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the new methodology as web services and incorporated the system into the Cloud. We have also developed a provenance management system for CMDA where CMDA service semantics modeling, service search and recommendation, and service execution history management are designed and implemented.

Retrieval of effective cloud field parameters from radiometric data

NASA Astrophysics Data System (ADS)

Paulescu, Marius; Badescu, Viorel; Brabec, Marek

2017-06-01

Clouds play a key role in establishing the Earth's climate. Real cloud fields are very different and very complex in both morphological and microphysical senses. Consequently, the numerical description of the cloud field is a critical task for accurate climate modeling. This study explores the feasibility of retrieving the effective cloud field parameters (namely the cloud aspect ratio and cloud factor) from systematic radiometric measurements at high frequency (measurement is taken every 15 s). Two different procedures are proposed, evaluated, and discussed with respect to both physical and numerical restrictions. None of the procedures is classified as best; therefore, the specific advantages and weaknesses are discussed. It is shown that the relationship between the cloud shade and point cloudiness computed using the estimated cloud field parameters recovers the typical relationship derived from measurements.

Sensitivity of projected long-term CO2 emissions across the Shared Socioeconomic Pathways

NASA Astrophysics Data System (ADS)

Marangoni, G.; Tavoni, M.; Bosetti, V.; Borgonovo, E.; Capros, P.; Fricko, O.; Gernaat, D. E. H. J.; Guivarch, C.; Havlik, P.; Huppmann, D.; Johnson, N.; Karkatsoulis, P.; Keppo, I.; Krey, V.; Ó Broin, E.; Price, J.; van Vuuren, D. P.

2017-01-01

Scenarios showing future greenhouse gas emissions are needed to estimate climate impacts and the mitigation efforts required for climate stabilization. Recently, the Shared Socioeconomic Pathways (SSPs) have been introduced to describe alternative social, economic and technical narratives, spanning a wide range of plausible futures in terms of challenges to mitigation and adaptation. Thus far the key drivers of the uncertainty in emissions projections have not been robustly disentangled. Here we assess the sensitivities of future CO2 emissions to key drivers characterizing the SSPs. We use six state-of-the-art integrated assessment models with different structural characteristics, and study the impact of five families of parameters, related to population, income, energy efficiency, fossil fuel availability, and low-carbon energy technology development. A recently developed sensitivity analysis algorithm allows us to parsimoniously compute both the direct and interaction effects of each of these drivers on cumulative emissions. The study reveals that the SSP assumptions about energy intensity and economic growth are the most important determinants of future CO2 emissions from energy combustion, both with and without a climate policy. Interaction terms between parameters are shown to be important determinants of the total sensitivities.

A Large-Scale, High-Resolution Hydrological Model Parameter Data Set for Climate Change Impact Assessment for the Conterminous US

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

Oubeidillah, Abdoul A; Kao, Shih-Chieh; Ashfaq, Moetasim

2014-01-01

To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation including meteorologic forcings, soil, land class, vegetation, and elevation were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous United States at refined 1/24 (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VICmore » simulation was driven by DAYMET daily meteorological forcing and was calibrated against USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous United States. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter dataset will be provided to interested parties to support further hydro-climate impact assessment.« less

Obtaining soil hydraulic parameters from data assimilation under different climatic/soil conditions

USDA-ARS?s Scientific Manuscript database

Obtaining reliable soil hydraulic properties is essential to correctly simulating soil water content (SWC), which is a key component of countless applications such as agricultural management, soil remediation, aquifer protection, etc. Soil hydraulic properties can be measured in the laboratory; howe...

Models and observations of Arctic melt ponds

NASA Astrophysics Data System (ADS)

Golden, K. M.

2016-12-01

During the Arctic melt season, the sea ice surface undergoes a striking transformation from vast expanses of snow covered ice to complex mosaics of ice and melt ponds. Sea ice albedo, a key parameter in climate modeling, is largely determined by the complex evolution of melt pond configurations. In fact, ice-albedo feedback has played a significant role in the recent declines of the summer Arctic sea ice pack. However, understanding melt pond evolution remains a challenge to improving climate projections. It has been found that as the ponds grow and coalesce, the fractal dimension of their boundaries undergoes a transition from 1 to about 2, around a critical length scale of 100 square meters in area. As the ponds evolve they take complex, self-similar shapes with boundaries resembling space-filling curves. I will outline how mathematical models of composite materials and statistical physics, such as percolation and Ising models, are being used to describe this evolution and predict key geometrical parameters that agree very closely with observations.

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

NASA Technical Reports Server (NTRS)

Molnar, Gyula; Susskind, Joel

2008-01-01

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

Sensitivity of the Eocene climate to CO2 and orbital variability

NASA Astrophysics Data System (ADS)

Keery, John S.; Holden, Philip B.; Edwards, Neil R.

2018-02-01

The early Eocene, from about 56 Ma, with high atmospheric CO2 levels, offers an analogue for the response of the Earth's climate system to anthropogenic fossil fuel burning. In this study, we present an ensemble of 50 Earth system model runs with an early Eocene palaeogeography and variation in the forcing values of atmospheric CO2 and the Earth's orbital parameters. Relationships between simple summary metrics of model outputs and the forcing parameters are identified by linear modelling, providing estimates of the relative magnitudes of the effects of atmospheric CO2 and each of the orbital parameters on important climatic features, including tropical-polar temperature difference, ocean-land temperature contrast, Asian, African and South (S.) American monsoon rains, and climate sensitivity. Our results indicate that although CO2 exerts a dominant control on most of the climatic features examined in this study, the orbital parameters also strongly influence important components of the ocean-atmosphere system in a greenhouse Earth. In our ensemble, atmospheric CO2 spans the range 280-3000 ppm, and this variation accounts for over 90 % of the effects on mean air temperature, southern winter high-latitude ocean-land temperature contrast and northern winter tropical-polar temperature difference. However, the variation of precession accounts for over 80 % of the influence of the forcing parameters on the Asian and African monsoon rainfall, and obliquity variation accounts for over 65 % of the effects on winter ocean-land temperature contrast in high northern latitudes and northern summer tropical-polar temperature difference. Our results indicate a bimodal climate sensitivity, with values of 4.36 and 2.54 °C, dependent on low or high states of atmospheric CO2 concentration, respectively, with a threshold at approximately 1000 ppm in this model, and due to a saturated vegetation-albedo feedback. Our method gives a quantitative ranking of the influence of each of the forcing parameters on key climatic model outputs, with additional spatial information from singular value decomposition providing insights into likely physical mechanisms. The results demonstrate the importance of orbital variation as an agent of change in climates of the past, and we demonstrate that emulators derived from our modelling output can be used as rapid and efficient surrogates of the full complexity model to provide estimates of climate conditions from any set of forcing parameters.

Quantifying Hydro-biogeochemical Model Sensitivity in Assessment of Climate Change Effect on Hyporheic Zone Processes

NASA Astrophysics Data System (ADS)

Song, X.; Chen, X.; Dai, H.; Hammond, G. E.; Song, H. S.; Stegen, J.

2016-12-01

The hyporheic zone is an active region for biogeochemical processes such as carbon and nitrogen cycling, where the groundwater and surface water mix and interact with each other with distinct biogeochemical and thermal properties. The biogeochemical dynamics within the hyporheic zone are driven by both river water and groundwater hydraulic dynamics, which are directly affected by climate change scenarios. Besides that, the hydraulic and thermal properties of local sediments and microbial and chemical processes also play important roles in biogeochemical dynamics. Thus for a comprehensive understanding of the biogeochemical processes in the hyporheic zone, a coupled thermo-hydro-biogeochemical model is needed. As multiple uncertainty sources are involved in the integrated model, it is important to identify its key modules/parameters through sensitivity analysis. In this study, we develop a 2D cross-section model in the hyporheic zone at the DOE Hanford site adjacent to Columbia River and use this model to quantify module and parametric sensitivity on assessment of climate change. To achieve this purpose, We 1) develop a facies-based groundwater flow and heat transfer model that incorporates facies geometry and heterogeneity characterized from a field data set, 2) derive multiple reaction networks/pathways from batch experiments with in-situ samples and integrate temperate dependent reactive transport modules to the flow model, 3) assign multiple climate change scenarios to the coupled model by analyzing historical river stage data, 4) apply a variance-based global sensitivity analysis to quantify scenario/module/parameter uncertainty in hierarchy level. The objectives of the research include: 1) identifing the key control factors of the coupled thermo-hydro-biogeochemical model in the assessment of climate change, and 2) quantify the carbon consumption in different climate change scenarios in the hyporheic zone.

Predicting species' range limits from functional traits for the tree flora of North America.

PubMed

Stahl, Ulrike; Reu, Björn; Wirth, Christian

2014-09-23

Using functional traits to explain species' range limits is a promising approach in functional biogeography. It replaces the idiosyncrasy of species-specific climate ranges with a generic trait-based predictive framework. In addition, it has the potential to shed light on specific filter mechanisms creating large-scale vegetation patterns. However, its application to a continental flora, spanning large climate gradients, has been hampered by a lack of trait data. Here, we explore whether five key plant functional traits (seed mass, wood density, specific leaf area (SLA), maximum height, and longevity of a tree)--indicative of life history, mechanical, and physiological adaptations--explain the climate ranges of 250 North American tree species distributed from the boreal to the subtropics. Although the relationship between traits and the median climate across a species range is weak, quantile regressions revealed strong effects on range limits. Wood density and seed mass were strongly related to the lower but not upper temperature range limits of species. Maximum height affects the species range limits in both dry and humid climates, whereas SLA and longevity do not show clear relationships. These results allow the definition and delineation of climatic "no-go areas" for North American tree species based on key traits. As some of these key traits serve as important parameters in recent vegetation models, the implementation of trait-based climatic constraints has the potential to predict both range shifts and ecosystem consequences on a more functional basis. Moreover, for future trait-based vegetation models our results provide a benchmark for model evaluation.

Comment on "High resolution coherence analysis between planetary and climate oscillations"

NASA Astrophysics Data System (ADS)

Holm, Sverre

2018-07-01

The paper by Scafetta entitled "High resolution coherence analysis between planetary and climate oscillations", May 2016 claims coherence between planetary movements and the global temperature anomaly. The claim is based on data analysis using the canonical covariance analysis (CCA) estimator for the magnitude squared coherence (MSC). It assumes a model with a predetermined number of sinusoids for the climate data. The results are highly dependent on this prior assumption, and may therefore be criticized for being based on the opposite of a null hypothesis. More importantly, since values of key parameters in the CCA method are not given, some experiments have been performed using the software of the original authors of the CCA estimator. The purpose was to replicate the results of Scafetta using what was perceived to be the most probable parameter values. Despite best efforts, this was not possible.

Ice_Sheets_CCI: Essential Climate Variables for the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Forsberg, R.; Sørensen, L. S.; Khan, A.; Aas, C.; Evansberget, D.; Adalsteinsdottir, G.; Mottram, R.; Andersen, S. B.; Ahlstrøm, A.; Dall, J.; Kusk, A.; Merryman, J.; Hvidberg, C.; Khvorostovsky, K.; Nagler, T.; Rott, H.; Scharrer, M.; Shepard, A.; Ticconi, F.; Engdahl, M.

2012-04-01

As part of the ESA Climate Change Initiative (www.esa-cci.org) a long-term project "ice_sheets_cci" started January 1, 2012, in addition to the existing 11 projects already generating Essential Climate Variables (ECV) for the Global Climate Observing System (GCOS). The "ice_sheets_cci" goal is to generate a consistent, long-term and timely set of key climate parameters for the Greenland ice sheet, to maximize the impact of European satellite data on climate research, from missions such as ERS, Envisat and the future Sentinel satellites. The climate parameters to be provided, at first in a research context, and in the longer perspective by a routine production system, would be grids of Greenland ice sheet elevation changes from radar altimetry, ice velocity from repeat-pass SAR data, as well as time series of marine-terminating glacier calving front locations and grounding lines for floating-front glaciers. The ice_sheets_cci project will involve a broad interaction of the relevant cryosphere and climate communities, first through user consultations and specifications, and later in 2012 optional participation in "best" algorithm selection activities, where prototype climate parameter variables for selected regions and time frames will be produced and validated using an objective set of criteria ("Round-Robin intercomparison"). This comparative algorithm selection activity will be completely open, and we invite all interested scientific groups with relevant experience to participate. The results of the "Round Robin" exercise will form the algorithmic basis for the future ECV production system. First prototype results will be generated and validated by early 2014. The poster will show the planned outline of the project and some early prototype results.

Professional Learning: A Fuzzy Logic-Based Modelling Approach

ERIC Educational Resources Information Center

Gravani, M. N.; Hadjileontiadou, S. J.; Nikolaidou, G. N.; Hadjileontiadis, L. J.

2007-01-01

Studies have suggested that professional learning is influenced by two key parameters, i.e., climate and planning, and their associated variables (mutual respect, collaboration, mutual trust, supportiveness, openness). In this paper, we applied analysis of the relationships between the proposed quantitative, fuzzy logic-based model and a series of…

Morphological leaf variability in natural populations of Pistacia atlantica Desf. subsp. atlantica along climatic gradient: new features to update Pistacia atlantica subsp. atlantica key.

PubMed

El Zerey-Belaskri, Asma; Benhassaini, Hachemi

2016-04-01

The effect of bioclimate range on the variation in Pistacia atlantica Desf. subsp. atlantica leaf morphology was studied on 16 sites in Northwest Algeria. The study examined biometrically mature leaves totaling 3520 compound leaves. Fifteen characters (10 quantitative and 5 qualitative) were assessed on each leaf. For each quantitative character, the nested analysis of variance (ANOVA) was used to examine relative magnitude of variation at each level of the nested hierarchy. The correlation between the climatic parameters and the leaf morphology was examined. The statistical analysis applied on the quantitative leaf characters showed highly significant variation at the within-site level and between-site variation. The correlation coefficient (r) showed also an important correlation between climatic parameters and leaf morphology. The results of this study exhibited several values reported for the first time on the species, such as the length and the width of the leaf (reaching up to 24.5 cm/21.9 cm), the number of leaflets (up to 18 leaflets/leaf), and the petiole length of the terminal leaflet (reaching up to 3.4 cm). The original findings of this study are used to update the P. atlantica subsp. atlantica identification key.

Sensitivity of black carbon concentrations and climate impact to aging and scavenging in OsloCTM2-M7

NASA Astrophysics Data System (ADS)

Lund, Marianne T.; Berntsen, Terje K.; Samset, Bjørn H.

2017-05-01

Accurate representation of black carbon (BC) concentrations in climate models is a key prerequisite for understanding its net climate impact. BC aging and scavenging are treated very differently in current models. Here, we examine the sensitivity of three-dimensional (3-D), temporally resolved BC concentrations to perturbations to individual model processes in the chemistry transport model OsloCTM2-M7. The main goals are to identify processes related to aerosol aging and scavenging where additional observational constraints may most effectively improve model performance, in particular for BC vertical profiles, and to give an indication of how model uncertainties in the BC life cycle propagate into uncertainties in climate impacts. Coupling OsloCTM2 with the microphysical aerosol module M7 allows us to investigate aging processes in more detail than possible with a simpler bulk parameterization. Here we include, for the first time in this model, a treatment of condensation of nitric acid on BC. Using kernels, we also estimate the range of radiative forcing and global surface temperature responses that may result from perturbations to key tunable parameters in the model. We find that BC concentrations in OsloCTM2-M7 are particularly sensitive to convective scavenging and the inclusion of condensation by nitric acid. The largest changes are found at higher altitudes around the Equator and at low altitudes over the Arctic. Convective scavenging of hydrophobic BC, and the amount of sulfate required for BC aging, are found to be key parameters, potentially reducing bias against HIAPER Pole-to-Pole Observations (HIPPO) flight-based measurements by 60 to 90 %. Even for extensive tuning, however, the total impact on global-mean surface temperature is estimated to less than 0.04 K. Similar results are found when nitric acid is allowed to condense on the BC aerosols. We conclude, in line with previous studies, that a shorter atmospheric BC lifetime broadly improves the comparison with measurements over the Pacific. However, we also find that the model-measurement discrepancies can not be uniquely attributed to uncertainties in a single process or parameter. Model development therefore needs to be focused on improvements to individual processes, supported by a broad range of observational and experimental data, rather than tuning of individual, effective parameters such as the global BC lifetime.

Comparing multiple model-derived aerosol optical properties to spatially collocated ground-based and satellite measurements

NASA Astrophysics Data System (ADS)

Ocko, Ilissa B.; Ginoux, Paul A.

2017-04-01

Anthropogenic aerosols are a key factor governing Earth's climate and play a central role in human-caused climate change. However, because of aerosols' complex physical, optical, and dynamical properties, aerosols are one of the most uncertain aspects of climate modeling. Fortunately, aerosol measurement networks over the past few decades have led to the establishment of long-term observations for numerous locations worldwide. Further, the availability of datasets from several different measurement techniques (such as ground-based and satellite instruments) can help scientists increasingly improve modeling efforts. This study explores the value of evaluating several model-simulated aerosol properties with data from spatially collocated instruments. We compare aerosol optical depth (AOD; total, scattering, and absorption), single-scattering albedo (SSA), Ångström exponent (α), and extinction vertical profiles in two prominent global climate models (Geophysical Fluid Dynamics Laboratory, GFDL, CM2.1 and CM3) to seasonal observations from collocated instruments (AErosol RObotic NETwork, AERONET, and Cloud-Aerosol Lidar with Orthogonal Polarization, CALIOP) at seven polluted and biomass burning regions worldwide. We find that a multi-parameter evaluation provides key insights on model biases, data from collocated instruments can reveal underlying aerosol-governing physics, column properties wash out important vertical distinctions, and improved models does not mean all aspects are improved. We conclude that it is important to make use of all available data (parameters and instruments) when evaluating aerosol properties derived by models.

A Dynamic Energy Budget (DEB) model to describe Laternula elliptica (King, 1832) seasonal feeding and metabolism

PubMed Central

Ahn, In-Young; Guillaumot, Charlène; Danis, Bruno

2017-01-01

Antarctic marine organisms are adapted to an extreme environment, characterized by a very low but stable temperature and a strong seasonality in food availability arousing from variations in day length. Ocean organisms are particularly vulnerable to global climate change with some regions being impacted by temperature increase and changes in primary production. Climate change also affects the biotic components of marine ecosystems and has an impact on the distribution and seasonal physiology of Antarctic marine organisms. Knowledge on the impact of climate change in key species is highly important because their performance affects ecosystem functioning. To predict the effects of climate change on marine ecosystems, a holistic understanding of the life history and physiology of Antarctic key species is urgently needed. DEB (Dynamic Energy Budget) theory captures the metabolic processes of an organism through its entire life cycle as a function of temperature and food availability. The DEB model is a tool that can be used to model lifetime feeding, growth, reproduction, and their responses to changes in biotic and abiotic conditions. In this study, we estimate the DEB model parameters for the bivalve Laternula elliptica using literature-extracted and field data. The DEB model we present here aims at better understanding the biology of L. elliptica and its levels of adaptation to its habitat with a special focus on food seasonality. The model parameters describe a metabolism specifically adapted to low temperatures, with a low maintenance cost and a high capacity to uptake and mobilise energy, providing this organism with a level of energetic performance matching that of related species from temperate regions. It was also found that L. elliptica has a large energy reserve that allows enduring long periods of starvation. Additionally, we applied DEB parameters to time-series data on biological traits (organism condition, gonad growth) to describe the effect of a varying environment in food and temperature on the organism condition and energy use. The DEB model developed here for L. elliptica allowed us to improve benchmark knowledge on the ecophysiology of this key species, providing new insights in the role of food availability and temperature on its life cycle and reproduction strategy. PMID:28850607

A Dynamic Energy Budget (DEB) model to describe Laternula elliptica (King, 1832) seasonal feeding and metabolism.

PubMed

Agüera, Antonio; Ahn, In-Young; Guillaumot, Charlène; Danis, Bruno

2017-01-01

Antarctic marine organisms are adapted to an extreme environment, characterized by a very low but stable temperature and a strong seasonality in food availability arousing from variations in day length. Ocean organisms are particularly vulnerable to global climate change with some regions being impacted by temperature increase and changes in primary production. Climate change also affects the biotic components of marine ecosystems and has an impact on the distribution and seasonal physiology of Antarctic marine organisms. Knowledge on the impact of climate change in key species is highly important because their performance affects ecosystem functioning. To predict the effects of climate change on marine ecosystems, a holistic understanding of the life history and physiology of Antarctic key species is urgently needed. DEB (Dynamic Energy Budget) theory captures the metabolic processes of an organism through its entire life cycle as a function of temperature and food availability. The DEB model is a tool that can be used to model lifetime feeding, growth, reproduction, and their responses to changes in biotic and abiotic conditions. In this study, we estimate the DEB model parameters for the bivalve Laternula elliptica using literature-extracted and field data. The DEB model we present here aims at better understanding the biology of L. elliptica and its levels of adaptation to its habitat with a special focus on food seasonality. The model parameters describe a metabolism specifically adapted to low temperatures, with a low maintenance cost and a high capacity to uptake and mobilise energy, providing this organism with a level of energetic performance matching that of related species from temperate regions. It was also found that L. elliptica has a large energy reserve that allows enduring long periods of starvation. Additionally, we applied DEB parameters to time-series data on biological traits (organism condition, gonad growth) to describe the effect of a varying environment in food and temperature on the organism condition and energy use. The DEB model developed here for L. elliptica allowed us to improve benchmark knowledge on the ecophysiology of this key species, providing new insights in the role of food availability and temperature on its life cycle and reproduction strategy.

Dominance of climate warming effects on recent drying trends over wet monsoon regions

NASA Astrophysics Data System (ADS)

Park, Chang-Eui; Jeong, Su-Jong; Ho, Chang-Hoi; Park, Hoonyoung; Piao, Shilong; Kim, Jinwon; Feng, Song

2017-09-01

Understanding changes in background dryness over land is key information for adapting to climate change because of its critical socioeconomic consequences. However, causes of continental dryness changes remain uncertain because various climate parameters control dryness. Here, we verify dominant climate variables determining dryness trends over continental eastern Asia, which is characterized by diverse hydroclimate regimes ranging from arid to humid, by quantifying the relative effects of changes in precipitation, solar radiation, wind speed, surface air temperature, and relative humidity on trends in the aridity index based on observed data from 189 weather stations for the period of 1961-2010. Before the early 1980s (1961-1983), change in precipitation is a primary condition for determining aridity trends. In the later period (1984-2010), the dominant climate parameter for aridity trends varies according to the hydroclimate regime. Drying trends in arid regions are mostly explained by reduced precipitation. In contrast, the increase in potential evapotranspiration due to increased atmospheric water-holding capacity, a secondary impact of warming, works to increase aridity over the humid monsoon region despite an enhanced water supply and relatively less warming. Our results show significant drying effects of warming over the humid monsoon region in recent decades; this also supports the drying trends over warm and water-sufficient regions in future climate.

Modeling High-Impact Weather and Climate: Lessons From a Tropical Cyclone Perspective

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

Done, James; Holland, Greg; Bruyere, Cindy

2013-10-19

Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding of the underlying physical processes. This challenge is driving fresh approaches to assess high-impact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias inmore » the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be guided by the need to: include relevant regional climate physical processes; resolve key impact parameters; and to accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters. Finally, through the example of a tropical cyclone damage index, direct impact assessments are resented as powerful tools that distill complex datasets into concise statements on likely impact, and as highly effective communication devices.« less

Generating multi-scale albedo look-up maps using MODIS BRDF/Albedo products and landsat imagery

USDA-ARS?s Scientific Manuscript database

Surface albedo determines radiative forcing and is a key parameter for driving Earth’s climate. Better characterization of surface albedo for individual land cover types can reduce the uncertainty in estimating changes to Earth’s radiation balance due to land cover change. This paper presents a mult...

Soil and vegetation parameter uncertainty on future terrestrial carbon sinks

NASA Astrophysics Data System (ADS)

Kothavala, Z.; Felzer, B. S.

2013-12-01

We examine the role of the terrestrial carbon cycle in a changing climate at the centennial scale using an intermediate complexity Earth system climate model that includes the effects of dynamic vegetation and the global carbon cycle. We present a series of ensemble simulations to evaluate the sensitivity of simulated terrestrial carbon sinks to three key model parameters: (a) The temperature dependence of soil carbon decomposition, (b) the upper temperature limits on the rate of photosynthesis, and (c) the nitrogen limitation of the maximum rate of carboxylation of Rubisco. We integrated the model in fully coupled mode for a 1200-year spin-up period, followed by a 300-year transient simulation starting at year 1800. Ensemble simulations were conducted varying each parameter individually and in combination with other variables. The results of the transient simulations show that terrestrial carbon uptake is very sensitive to the choice of model parameters. Changes in net primary productivity were most sensitive to the upper temperature limit on the rate of photosynthesis, which also had a dominant effect on overall land carbon trends; this is consistent with previous research that has shown the importance of climatic suppression of photosynthesis as a driver of carbon-climate feedbacks. Soil carbon generally decreased with increasing temperature, though the magnitude of this trend depends on both the net primary productivity changes and the temperature dependence of soil carbon decomposition. Vegetation carbon increased in some simulations, but this was not consistent across all configurations of model parameters. Comparing to global carbon budget observations, we identify the subset of model parameters which are consistent with observed carbon sinks; this serves to narrow considerably the future model projections of terrestrial carbon sink changes in comparison with the full model ensemble.

Implementation and calibration of a stochastic multicloud convective parameterization in the NCEP Climate Forecast System (CFSv2)

NASA Astrophysics Data System (ADS)

Goswami, B. B.; Khouider, B.; Phani, R.; Mukhopadhyay, P.; Majda, A. J.

2017-07-01

A comparative analysis of fourteen 5 year long climate simulations produced by the National Centers for Environmental Predictions (NCEP) Climate Forecast System version 2 (CFSv2), in which a stochastic multicloud (SMCM) cumulus parameterization is implemented, is presented here. These 5 year runs are made with different sets of parameters in order to figure out the best model configuration based on a suite of state-of-the-art metrics. This analysis is also a systematic attempt to understand the model sensitivity to the SMCM parameters. The model is found to be resilient to minor changes in the parameters used implying robustness of the SMCM formulation. The model is found to be most sensitive to the midtropospheric dryness parameter (MTD) and to the stratiform cloud decay timescale (τ30). MTD is more effective in controlling the global mean precipitation and its distribution while τ30 has more effect on the organization of convection as noticed in the simulation of the Madden-Julian oscillation (MJO). This is consistent with the fact that in the SMCM formulation, midtropospheric humidity controls the deepening of convection and stratiform clouds control the backward tilt of tropospheric heating and the strength of unsaturated downdrafts which cool and dry the boundary layer and trigger the propagation of organized convection. Many other studies have also found midtropospheric humidity to be a key factor in the capacity of a global climate model to simulate organized convection on the synoptic and intraseasonal scales.

Integrated remote sensing for multi-temporal analysis of urban land cover-climate interactions

NASA Astrophysics Data System (ADS)

Savastru, Dan M.; Zoran, Maria A.; Savastru, Roxana S.

2016-08-01

Climate change is considered to be the biggest environmental threat in the future in the South- Eastern part of Europe. In frame of predicted global warming, urban climate is an important issue in scientific research. Surface energy processes have an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. This paper investigated the influences of urban growth on thermal environment in relationship with other biophysical variables in Bucharest metropolitan area of Romania. Remote sensing data from Landsat TM/ETM+ and time series MODIS Terra/Aqua sensors have been used to assess urban land cover- climate interactions over period between 2000 and 2015 years. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also analyzed in relation with the Normalized Difference Vegetation Index (NDVI) at city level. Based on these parameters, the urban growth, and urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

Soil biochar amendment as a climate change mitigation tool: Key parameters and mechanisms involved.

PubMed

Brassard, Patrick; Godbout, Stéphane; Raghavan, Vijaya

2016-10-01

Biochar, a solid porous material obtained from the carbonization of biomass under low or no oxygen conditions, has been proposed as a climate change mitigation tool because it is expected to sequester carbon (C) for centuries and to reduce greenhouse gas (GHG) emissions from soils. This review aimed to identify key biochar properties and production parameters that have an effect on these specific applications of the biochar. Moreover, mechanisms involved in interactions between biochar and soils were highlighted. Following a compilation and comparison of the characteristics of 76 biochars from 40 research studies, biochars with a lower N content, and consequently a higher C/N ratio (>30), were found to be more suitable for mitigation of N2O emissions from soils. Moreover, biochars produced at a higher pyrolysis temperature, and with O/C ratio <0.2, H/Corg ratio <0.4 and volatile matter below 80% may have high C sequestration potential. Based on these observations, biochar production and application to the field can be used as a tool to mitigate climate change. However, it is important to determine the pyrolysis conditions and feedstock needed to produce a biochar with the desired properties for a specific application. More research studies are needed to identify the exact mechanisms involved following biochar amendment to soil. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-01

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. About 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). The relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.

The effects of climate change on heating energy consumption of office buildings in different climate zones in China

NASA Astrophysics Data System (ADS)

Meng, Fanchao; Li, Mingcai; Cao, Jingfu; Li, Ji; Xiong, Mingming; Feng, Xiaomei; Ren, Guoyu

2017-06-01

Climate plays an important role in heating energy consumption owing to the direct relationship between space heating and changes in meteorological conditions. To quantify the impact, the Transient System Simulation Program software was used to simulate the heating loads of office buildings in Harbin, Tianjin, and Shanghai, representing three major climate zones (i.e., severe cold, cold, and hot summer and cold winter climate zones) in China during 1961-2010. Stepwise multiple linear regression was performed to determine the key climatic parameters influencing heating energy consumption. The results showed that dry bulb temperature (DBT) is the dominant climatic parameter affecting building heating loads in all three climate zones across China during the heating period at daily, monthly, and yearly scales (R 2 ≥ 0.86). With the continuous warming climate in winter over the past 50 years, heating loads decreased by 14.2, 7.2, and 7.1 W/m2 in Harbin, Tianjin, and Shanghai, respectively, indicating that the decreasing rate is more apparent in severe cold climate zone. When the DBT increases by 1 °C, the heating loads decrease by 253.1 W/m2 in Harbin, 177.2 W/m2 in Tianjin, and 126.4 W/m2 in Shanghai. These results suggest that the heating energy consumption can be well predicted by the regression models at different temporal scales in different climate conditions owing to the high determination coefficients. In addition, a greater decrease in heating energy consumption in northern severe cold and cold climate zones may efficiently promote the energy saving in these areas with high energy consumption for heating. Particularly, the likely future increase in temperatures should be considered in improving building energy efficiency.

Intraspecific variation in host susceptibility and climatic factors mediate epidemics of sudden oak death in western US forests

Treesearch

D. Huberli; K.J. Hayden; M. Calver; M. Garbelotto

2011-01-01

Umbellularia californica is one of the key infectious hosts of the exotic Phytophthora ramorum, which causes sudden oak death (SOD) in California and Oregon forests. This study provides a comprehensive analysis of the epidemiologically relevant parameters for SOD in California and southern Oregon, including potential differences between the two...

Combined effects of climate and land management on watershed vegetation dynamics in an arid environment

Treesearch

Peilong Liu; Lu Hao; Cen Pan; Decheng Zhou; Yongqiang Liu; Ge Sun

2017-01-01

Leaf area index (LAI) is a key parameter to characterize vegetation dynamics and ecosystemstructure that determines the ecosystem functions and services such as cleanwater supply and carbon sequestration in awatershed. However, linking LAI dynamics and environmental controls (i.e., coupling biosphere, atmosphere, and anthroposphere) remains challenging and such type of...

Revisiting Melton: Analyzing the correlation structure of geomorphological and climatological parameters

NASA Astrophysics Data System (ADS)

Carothers, R. A.; Sangireddy, H.; Passalacqua, P.

2013-12-01

In his expansive 1957 study of over 80 basins in Arizona, Colorado, New Mexico, and Utah, Mark Melton measured key morphometric, soil, land cover, and climatic parameters [Melton, 1957]. He identified correlations between morphological parameters and climatic regimes in an attempt to characterize the geomorphology of the basin as a function of climate and vegetation. Using modern techniques such as high resolution digital terrain models in combination with high spatial resolution weather station records, vector soil maps, seamless raster geological data, and land cover vector maps, we revisit Melton's 1957 dataset with the following hypotheses: (1) Patterns of channelization carry strong, codependent signatures in the form of statistical correlations of rainfall variability, soil type, and vegetation patterns. (2) Channelization patterns reflect the erosion processes on sub-catchment scale and the subsequent processes of vegetation recovery and gullying. In order to characterize various topographic and climatic parameters, we obtain elevation and land cover data from the USGS National Elevation dataset, climate data from the Western Regional Climate Center and PRISM climate group database, and soil type from the USDA STATSGO soil database. We generate a correlative high resolution database on vegetation, soil cover, lithology, and climatology for the basins identified by Melton in his 1957 study. Using the GeoNet framework developed by Passalacqua et al. [2010], we extract various morphological parameters such as slope, drainage density, and stream frequency. We also calculate metrics for patterns of channelization such as number of channelized pixels in a basin and channel head density. In order to understand the correlation structure between climate and morphological variables, we compute the Pearson's correlation coefficient similar to Melton's analysis and also explore other statistical procedures to characterize the feedbacks between these variables. By identifying the differences in Melton's and our results, we address the influence of climate over the degree of channel dissection in the landscape. References: Melton, M. A. (1957). An analysis of the relations among elements of climate, surface properties, and geomorphology (No. CU-TR-11). COLUMBIA UNIV NEW YORK Passalacqua, P., Do Trung, T., Foufoula-Georgiou, E., Sapiro, G., & Dietrich, W. E. (2010). A geometric framework for channel network extraction from lidar: Nonlinear diffusion and geodesic paths. Journal of Geophysical Research: Earth Surface (2003-2012), 115(F1). PRISM Climate Group, Oregon State University, http://prism.oregonstate.edu, created 4 Feb 2004 Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. U.S. General Soil Map (STATSGO2). Available online at http://soildatamart.nrcs.usda.gov USGS National Map Viewer, United States Geological Survey. Web. 10 June 2013. http://viewer.nationalmap.gov/viewer/ Western U.S. Historical Climate Summaries, Western Regional Climate Group, 2013. Web. 10 June 2013. http://www.wrcc.dri.edu/Climsum.html

Recurrent seascape units identify key ecological processes along the western Antarctic Peninsula.

PubMed

Bowman, Jeff S; Kavanaugh, Maria T; Doney, Scott C; Ducklow, Hugh W

2018-04-10

The western Antarctic Peninsula (WAP) is a bellwether of global climate change and natural laboratory for identifying interactions between climate and ecosystems. The Palmer Long-Term Ecological Research (LTER) project has collected data on key ecological and environmental processes along the WAP since 1993. To better understand how key ecological parameters are changing across space and time, we developed a novel seascape classification approach based on in situ temperature, salinity, chlorophyll a, nitrate + nitrite, phosphate, and silicate. We anticipate that this approach will be broadly applicable to other geographical areas. Through the application of self-organizing maps (SOMs), we identified eight recurrent seascape units (SUs) in these data. These SUs have strong fidelity to known regional water masses but with an additional layer of biogeochemical detail, allowing us to identify multiple distinct nutrient profiles in several water masses. To identify the temporal and spatial distribution of these SUs, we mapped them across the Palmer LTER sampling grid via objective mapping of the original parameters. Analysis of the abundance and distribution of SUs since 1993 suggests two year types characterized by the partitioning of chlorophyll a into SUs with different spatial characteristics. By developing generalized linear models for correlated, time-lagged external drivers, we conclude that early spring sea ice conditions exert a strong influence on the distribution of chlorophyll a and nutrients along the WAP, but not necessarily the total chlorophyll a inventory. Because the distribution and density of phytoplankton biomass can have an impact on biomass transfer to the upper trophic levels, these results highlight anticipated links between the WAP marine ecosystem and climate. © 2018 John Wiley & Sons Ltd.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2011-12-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Uncertainty Quantification and Parameter Tuning: A Case Study of Convective Parameterization Scheme in the WRF Regional Climate Model

NASA Astrophysics Data System (ADS)

Qian, Y.; Yang, B.; Lin, G.; Leung, R.; Zhang, Y.

2012-04-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. The latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2012-03-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e. the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

A vertical hydroclimatology of the Upper Indus Basin and initial insights to potential hydrological change in the region

NASA Astrophysics Data System (ADS)

Forsythe, Nathan; Kilsby, Chris G.; Fowler, Hayley J.; Archer, David R.

2010-05-01

The water resources of the Upper Indus Basin (UIB) are of the utmost importance to the economic wellbeing of Pakistan. The irrigated agriculture made possible by Indus river runoff underpins the food security for Pakistan's nearly 200 million people. Contributions from hydropower account for more than one fifth of peak installed electrical generating capacity in a country where widespread, prolonged load-shedding handicaps business activity and industrial development. Pakistan's further socio-economic development thus depends largely on optimisation of its precious water resources. Confident, accurate projections of future water resource availability and variability are urgent insights needed by development planners and infrastructure managers at all levels. Correctly projecting future hydrological conditions depends first and foremost on a thorough understanding of the underlying mechanisms and processes of present hydroclimatology. The vertical and horizontal spatial variations in key climate parameters (temperature, precipitation) govern the contributions of the various elevation zones and subcatchments comprising the UIB. Trends in this complex mountainous region are highly varied by season and parameter. Observed changes here often do not match general global trends or even necessarily those found in neighbouring regions. This study considers data from a variety sources in order to compose the most complete picture possible of the vertical hydroclimatology of the UIB. The study presents the observed climatology and trends for precipitation and temperature from local observations at long-record meteorological stations (Pakistan Meteorological Department). These data are compared to characterisations of additional water cycle parameters (humidity, cloud, snow cover and snow-water-equivalent) derived from local short-record automatic weather stations, the ECMWF ‘ERA' reanalysis projects and satellite based observations (AVHRR, MODIS, etc). The potential implications of the vertical (hypsometric) distribution of these parameters are considered. Interlinkages between observed changes in these parameters and the evolution of large-scale circulation indices (ENSO, NAO, local vorticity) are also investigated. In parallel to these climatological considerations, the study presents the typology of the observed UIB hydrological regimes -- glacial, nival and pluvial -- including interannual variability as quantified from the available river gauging record. In order to begin to assess potential implications of future climate change on UIB hydrology, key modes of variability in the climate parameters are identified. The study then analyses in detail the corresponding observed anomalies in UIB discharge for years exemplifying these modes. In conclusion, this work postulates potential impacts of changes in the hydrological variability stemming from continuation of estimated present local climatic trends.

Drought is a recurring challenge in the Middle East.

PubMed

Kaniewski, David; Van Campo, Elise; Weiss, Harvey

2012-03-06

Climate change and water availability in the Middle East are important in understanding human adaptive capacities in the face of long-term environmental changes. The key role of water availability for sedentary and nomad populations in these arid to semiarid landscapes is understood, but the millennium-scale influence of hydrologic instability on vegetation dynamics, human occupation, and historic land use are unknown, which has led to a stochastic view of population responses and adaptive capacities to precipitation anomalies. Within the time-frame of the last two global climate events, the Medieval Climate Anomaly and the Little Ice Age, we report hydrologic instability reconstructed from pollen-derived climate proxies recovered near Tell Leilan, at the Wadi Jarrah in the Khabur Plains of northeastern Syria, at the heart of ancient northern Mesopotamia. By coupling climate proxies with archaeological-historical data and a pollen-based record of agriculture, this integrative study suggests that variability in precipitation is a key factor on crop yields, productivity, and economic systems. It may also have been one of the main parameters controlling human settlement and population migrations at the century to millennial timescales in the arid to semiarid areas of the Middle East. An abrupt shift to drier conditions at ca. AD 1400 is contemporaneous with a change from sedentary village life to regional desertion and nomadization (sheep/camel pastoralists) during the preindustrial era in formerly Ottoman realms, and thereby adds climate change to the multiple causes for Ottoman Empire "decline."

Drought is a recurring challenge in the Middle East

PubMed Central

Kaniewski, David; Van Campo, Elise; Weiss, Harvey

2012-01-01

Climate change and water availability in the Middle East are important in understanding human adaptive capacities in the face of long-term environmental changes. The key role of water availability for sedentary and nomad populations in these arid to semiarid landscapes is understood, but the millennium-scale influence of hydrologic instability on vegetation dynamics, human occupation, and historic land use are unknown, which has led to a stochastic view of population responses and adaptive capacities to precipitation anomalies. Within the time-frame of the last two global climate events, the Medieval Climate Anomaly and the Little Ice Age, we report hydrologic instability reconstructed from pollen-derived climate proxies recovered near Tell Leilan, at the Wadi Jarrah in the Khabur Plains of northeastern Syria, at the heart of ancient northern Mesopotamia. By coupling climate proxies with archaeological-historical data and a pollen-based record of agriculture, this integrative study suggests that variability in precipitation is a key factor on crop yields, productivity, and economic systems. It may also have been one of the main parameters controlling human settlement and population migrations at the century to millennial timescales in the arid to semiarid areas of the Middle East. An abrupt shift to drier conditions at ca. AD 1400 is contemporaneous with a change from sedentary village life to regional desertion and nomadization (sheep/camel pastoralists) during the preindustrial era in formerly Ottoman realms, and thereby adds climate change to the multiple causes for Ottoman Empire “decline.” PMID:22355126

Understanding controls of hydrologic processes across two monolithological catchments using model-data integration

NASA Astrophysics Data System (ADS)

Xiao, D.; Shi, Y.; Li, L.

2016-12-01

Field measurements are important to understand the fluxes of water, energy, sediment, and solute in the Critical Zone however are expensive in time, money, and labor. This study aims to assess the model predictability of hydrological processes in a watershed using information from another intensively-measured watershed. We compare two watersheds of different lithology using national datasets, field measurements, and physics-based model, Flux-PIHM. We focus on two monolithological, forested watersheds under the same climate in the Shale Hills Susquehanna CZO in central Pennsylvania: the Shale-based Shale Hills (SSH, 0.08 km2) and the sandstone-based Garner Run (GR, 1.34 km2). We firstly tested the transferability of calibration coefficients from SSH to GR. We found that without any calibration the model can successfully predict seasonal average soil moisture and discharge which shows the advantage of a physics-based model, however, cannot precisely capture some peaks or the runoff in summer. The model reproduces the GR field data better after calibrating the soil hydrology parameters. In particular, the percentage of sand turns out to be a critical parameter in reproducing data. With sandstone being the dominant lithology, GR has much higher sand percentage than SSH (48.02% vs. 29.01%), leading to higher hydraulic conductivity, lower overall water storage capacity, and in general lower soil moisture. This is consistent with area averaged soil moisture observations using the cosmic-ray soil moisture observing system (COSMOS) at the two sites. This work indicates that some parameters, including evapotranspiration parameters, are transferrable due to similar climatic and land cover conditions. However, the key parameters that control soil moisture, including the sand percentage, need to be recalibrated, reflecting the key role of soil hydrological properties.

Linking the climatic and geochemical controls on global soil carbon cycling

NASA Astrophysics Data System (ADS)

Doetterl, Sebastian; Stevens, Antoine; Six, Johan; Merckx, Roel; Van Oost, Kristof; Casanova Pinto, Manuel; Casanova-Katny, Angélica; Muñoz, Cristina; Boudin, Mathieu; Zagal Venegas, Erick; Boeckx, Pascal

2015-04-01

Climatic and geochemical parameters are regarded as the primary controls for soil organic carbon (SOC) storage and turnover. However, due to the difference in scale between climate and geochemical-related soil research, the interaction of these key factors for SOC dynamics have rarely been assessed. Across a large geochemical and climatic transect in similar biomes in Chile and the Antarctic Peninsula we show how abiotic geochemical soil features describing soil mineralogy and weathering pose a direct control on SOC stocks, concentration and turnover and are central to explaining soil C dynamics at larger scales. Precipitation and temperature had an only indirect control by regulating geochemistry. Soils with high SOC content have low specific potential CO2 respiration rates, but a large fraction of SOC that is stabilized via organo-mineral interactions. The opposite was observed for soils with low SOC content. The observed differences for topsoil SOC stocks along this transect of similar biomes but differing geo-climatic site conditions are of the same magnitude as differences observed for topsoil SOC stocks across all major global biomes. Using precipitation and a set of abiotic geochemical parameters describing soil mineralogy and weathering status led to predictions of high accuracy (R2 0.53-0.94) for different C response variables. Partial correlation analyses revealed that the strength of the correlation between climatic predictors and SOC response variables decreased by 51 - 83% when controlling for geochemical predictors. In contrast, controlling for climatic variables did not result in a strong decrease in the strength of the correlations of between most geochemical variables and SOC response variables. In summary, geochemical parameters describing soil mineralogy and weathering were found to be essential for accurate predictions of SOC stocks and potential CO2 respiration, while climatic factors were of minor importance as a direct control, but are important through governing soil weathering and geochemistry. In conclusion, we pledge for a stronger implementation of geochemical soil properties to predict SOC stocks on a global scale. Understanding the effects of climate (temperature and precipitation) change on SOC dynamics also requires good understanding of the relationship between climate and soil geochemistry.

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

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

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

DOE PAGES

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-27

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

Close packing effects on clean and dirty snow albedo and associated climatic implications

NASA Astrophysics Data System (ADS)

He, C.; Liou, K. N.; Takano, Y.

2017-12-01

Previous modeling of snow albedo, a key climate feedback parameter, follows the independent scattering approximation (ISA) such that snow grains are considered as a number of separate units with distances longer than wavelengths. Here we develop a new snow albedo model for widely observed close-packed snow grains internally mixed with black carbon (BC) and demonstrate that albedo simulations match closer to observations. Close packing results in a stronger light absorption for clean and BC-contaminated snow. Compared with ISA, close packing reduces pure snow albedos by up to 0.05, whereas it enhances BC-induced snow albedo reduction and associated surface radiative forcing by up to 15% (20%) for fresh (old) snow, with larger enhancements for stronger structure packing. Finally, our results suggest that BC-snow albedo forcing and snow albedo feedback (climate sensitivity) are underestimated in previous modeling studies, making snow close packing consideration a necessity in climate modeling and analysis.

Close packing effects on clean and dirty snow albedo and associated climatic implications

NASA Astrophysics Data System (ADS)

He, Cenlin; Takano, Yoshi; Liou, Kuo-Nan

2017-04-01

Previous modeling of snow albedo, a key climate feedback parameter, follows the independent scattering approximation (ISA) such that snow grains are considered as a number of separate units with distances longer than wavelengths. Here we develop a new snow albedo model for widely observed close-packed snow grains internally mixed with black carbon (BC) and demonstrate that albedo simulations match closer to observations. Close packing results in a stronger light absorption for clean and BC-contaminated snow. Compared with ISA, close packing reduces pure snow albedos by up to 0.05, whereas it enhances BC-induced snow albedo reduction and associated surface radiative forcing by up to 15% (20%) for fresh (old) snow, with larger enhancements for stronger structure packing. Finally, our results suggest that BC-snow albedo forcing and snow albedo feedback (climate sensitivity) are underestimated in previous modeling studies, making snow close packing consideration a necessity in climate modeling and analysis.

Variation in White Stork ( Ciconia ciconia) diet along a climatic gradient and across rural-to-urban landscapes in North Africa

NASA Astrophysics Data System (ADS)

Chenchouni, Haroun

2017-03-01

Assessing diet composition of White Storks ( Ciconia ciconia) breeding under North African conditions provides key information to understanding its trophic niche for conservation purpose. Since, climate controls productivities of foraging habitats and thus food availability for predators, this study examines how Storks' diet parameters varied following a climate gradient along with rural-to-urban landscapes in north-eastern Algeria. Feeding strategies to cope with severe conditions were discussed in light of climate aridity and urbanization and how these influence reproduction, population dynamics and distribution. While invertebrate prey accounted for 94 % of ingested individuals, the biomass intake was dominated by chicken remains scavenged from rubbish dumps (67 %) and small mammals (14 %). Generalized linear models revealed that prey numbers varied significantly between climatic regions and landscapes types, but no significant differences were observed for other dietary parameters, including prey biomass. The study showed high dietary similarity between study climates and landscapes, mainly among rural and urban colonies located in semi-arid and sub-humid areas, which differed from those in suburban and arid climate. Rarefaction and extrapolation curves indicated that prey species richness in White Stork diets was expected to be higher in urban colonies located in sub-humid climate. Despite low prey species diversity in arid regions, the White Stork demonstrates a broad trophic niche, which could be due to supplementary feeding from human refuse. This study suggests that regardless of the climate or landscape, White Storks ensure a constant food intake, despite prey biomass fluctuations, by adapting their diet. Foraging in diverse habitats, including trash dumps, ensures a sufficiently balanced diet to meet nutritional requirements.

Variation in White Stork (Ciconia ciconia) diet along a climatic gradient and across rural-to-urban landscapes in North Africa.

PubMed

Chenchouni, Haroun

2017-03-01

Assessing diet composition of White Storks (Ciconia ciconia) breeding under North African conditions provides key information to understanding its trophic niche for conservation purpose. Since, climate controls productivities of foraging habitats and thus food availability for predators, this study examines how Storks' diet parameters varied following a climate gradient along with rural-to-urban landscapes in north-eastern Algeria. Feeding strategies to cope with severe conditions were discussed in light of climate aridity and urbanization and how these influence reproduction, population dynamics and distribution. While invertebrate prey accounted for 94 % of ingested individuals, the biomass intake was dominated by chicken remains scavenged from rubbish dumps (67 %) and small mammals (14 %). Generalized linear models revealed that prey numbers varied significantly between climatic regions and landscapes types, but no significant differences were observed for other dietary parameters, including prey biomass. The study showed high dietary similarity between study climates and landscapes, mainly among rural and urban colonies located in semi-arid and sub-humid areas, which differed from those in suburban and arid climate. Rarefaction and extrapolation curves indicated that prey species richness in White Stork diets was expected to be higher in urban colonies located in sub-humid climate. Despite low prey species diversity in arid regions, the White Stork demonstrates a broad trophic niche, which could be due to supplementary feeding from human refuse. This study suggests that regardless of the climate or landscape, White Storks ensure a constant food intake, despite prey biomass fluctuations, by adapting their diet. Foraging in diverse habitats, including trash dumps, ensures a sufficiently balanced diet to meet nutritional requirements.

Event-based stormwater management pond runoff temperature model

NASA Astrophysics Data System (ADS)

Sabouri, F.; Gharabaghi, B.; Sattar, A. M. A.; Thompson, A. M.

2016-09-01

Stormwater management wet ponds are generally very shallow and hence can significantly increase (about 5.4 °C on average in this study) runoff temperatures in summer months, which adversely affects receiving urban stream ecosystems. This study uses gene expression programming (GEP) and artificial neural networks (ANN) modeling techniques to advance our knowledge of the key factors governing thermal enrichment effects of stormwater ponds. The models developed in this study build upon and compliment the ANN model developed by Sabouri et al. (2013) that predicts the catchment event mean runoff temperature entering the pond as a function of event climatic and catchment characteristic parameters. The key factors that control pond outlet runoff temperature, include: (1) Upland Catchment Parameters (catchment drainage area and event mean runoff temperature inflow to the pond); (2) Climatic Parameters (rainfall depth, event mean air temperature, and pond initial water temperature); and (3) Pond Design Parameters (pond length-to-width ratio, pond surface area, pond average depth, and pond outlet depth). We used monitoring data for three summers from 2009 to 2011 in four stormwater management ponds, located in the cities of Guelph and Kitchener, Ontario, Canada to develop the models. The prediction uncertainties of the developed ANN and GEP models for the case study sites are around 0.4% and 1.7% of the median value. Sensitivity analysis of the trained models indicates that the thermal enrichment of the pond outlet runoff is inversely proportional to pond length-to-width ratio, pond outlet depth, and directly proportional to event runoff volume, event mean pond inflow runoff temperature, and pond initial water temperature.

Practice and philosophy of climate model tuning across six US modeling centers

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

Schmidt, Gavin A.; Bader, David; Donner, Leo J.

Model calibration (or tuning) is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientificmore » missions, tuning targets, and tunable parameters, there is a core commonality of approaches. Furthermore, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.« less

Practice and philosophy of climate model tuning across six US modeling centers

NASA Astrophysics Data System (ADS)

Schmidt, Gavin A.; Bader, David; Donner, Leo J.; Elsaesser, Gregory S.; Golaz, Jean-Christophe; Hannay, Cecile; Molod, Andrea; Neale, Richard B.; Saha, Suranjana

2017-09-01

Model calibration (or tuning) is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets, and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.

Practice and philosophy of climate model tuning across six US modeling centers

DOE PAGES

Schmidt, Gavin A.; Bader, David; Donner, Leo J.; ...

2017-09-01

Model calibration (or tuning) is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientificmore » missions, tuning targets, and tunable parameters, there is a core commonality of approaches. Furthermore, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.« less

A Process-based, Climate-Sensitive Model to Derive Methane Emissions from Natural Wetlands: Application to 5 Wetland Sites, Sensitivity to Model Parameters and Climate

NASA Technical Reports Server (NTRS)

Walter, Bernadette P.; Heimann, Martin

1999-01-01

Methane emissions from natural wetlands constitutes the largest methane source at present and depends highly on the climate. In order to investigate the response of methane emissions from natural wetlands to climate variations, a 1-dimensional process-based climate-sensitive model to derive methane emissions from natural wetlands is developed. In the model the processes leading to methane emission are simulated within a 1-dimensional soil column and the three different transport mechanisms diffusion, plant-mediated transport and ebullition are modeled explicitly. The model forcing consists of daily values of soil temperature, water table and Net Primary Productivity, and at permafrost sites the thaw depth is included. The methane model is tested using observational data obtained at 5 wetland sites located in North America, Europe and Central America, representing a large variety of environmental conditions. It can be shown that in most cases seasonal variations in methane emissions can be explained by the combined effect of changes in soil temperature and the position of the water table. Our results also show that a process-based approach is needed, because there is no simple relationship between these controlling factors and methane emissions that applies to a variety of wetland sites. The sensitivity of the model to the choice of key model parameters is tested and further sensitivity tests are performed to demonstrate how methane emissions from wetlands respond to climate variations.

Climate anomalies associated with the occurrence of rockfalls at high-elevation in the Italian Alps

NASA Astrophysics Data System (ADS)

Paranunzio, Roberta; Laio, Francesco; Chiarle, Marta; Nigrelli, Guido; Guzzetti, Fausto

2016-09-01

Climate change is seriously affecting the cryosphere in terms, for example, of permafrost thaw, alteration of rain / snow ratio, and glacier shrinkage. There is concern about the increasing number of rockfalls at high elevation in the last decades. Nevertheless, the exact role of climate parameters in slope instability at high elevation has not been fully explored yet. In this paper, we investigate 41 rockfalls listed in different sources (newspapers, technical reports, and CNR IRPI archive) in the elevation range 1500-4200 m a.s.l. in the Italian Alps between 1997 and 2013 in the absence of an evident trigger. We apply and improve an existing data-based statistical approach to detect the anomalies of climate parameters (temperature and precipitation) associated with rockfall occurrences. The identified climate anomalies have been related to the spatiotemporal distribution of the events. Rockfalls occurred in association with significant temperature anomalies in 83 % of our case studies. Temperature represents a key factor contributing to slope failure occurrence in different ways. As expected, warm temperatures accelerate snowmelt and permafrost thaw; however, surprisingly, negative anomalies are also often associated with slope failures. Interestingly, different regional patterns emerge from the data: higher-than-average temperatures are often associated with rockfalls in the Western Alps, while in the Eastern Alps slope failures are mainly associated with colder-than-average temperatures.

Agriculture and Climate Change in Global Scenarios: Why Don't the Models Agree

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

Nelson, Gerald; van der Mensbrugghe, Dominique; Ahammad, Helal

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs makes direct use of weather inputs. Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes of key variables such as prices, production, and trade. These divergent outcomes arise from differences in model inputs and model specification. The goal of this paper is to review climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. Bymore » providing common productivity drivers that include climate change effects, differences in model outcomes are reduced. All models show higher prices in 2050 because of negative productivity shocks from climate change. The magnitude of the price increases, and the adaptation responses, differ significantly across the various models. Substantial differences exist in the structural parameters affecting demand, area, and yield, and should be a topic for future research.« less

Effects of future climate and land use scenarios on riverine source water quality.

PubMed

Delpla, Ianis; Rodriguez, Manuel J

2014-09-15

Surface water quality is particularly sensitive to land use practices and climatic events that affect its catchment. The relative influence of a set of watershed characteristics (climate, land use, morphology and pedology) and climatic variables on two key water quality parameters (turbidity and fecal coliforms (FC)) was examined in 24 eastern Canadian catchments at various spatial scales (1 km, 5 km, 10 km and the entire catchment). A regression analysis revealed that the entire catchment was a better predictor of water quality. Based on this information, linear mixed effect models for predicting turbidity and FC levels were developed. A set of land use and climate scenarios was considered and applied within the water quality models. Four land use scenarios (no change, same rate of variation, optimistic and pessimistic) and three climate change scenarios (B1, A1B and A2) were tested and variations for the near future (2025) were assessed and compared to the reference period (2000). Climate change impacts on water quality remained low annually for this time horizon (turbidity: +1.5%, FC: +1.6%, A2 scenario). On the other hand, the influence of land use changes appeared to predominate. Significant benefits for both parameters could be expected following the optimistic scenario (turbidity: -16.4%, FC: -6.3%; p < 0.05). However, pessimistic land use scenario led to significant increases on an annual basis (turbidity: +11.6%, FC: +15.2%; p < 0.05). Additional simulations conducted for the late 21st century (2090) revealed that climate change impacts could become equivalent to those modeled for land use for this horizon. Copyright © 2014 Elsevier B.V. All rights reserved.

Key Parameters for Urban Heat Island Assessment in A Mediterranean Context: A Sensitivity Analysis Using the Urban Weather Generator Model

NASA Astrophysics Data System (ADS)

Salvati, Agnese; Palme, Massimo; Inostroza, Luis

2017-10-01

Although Urban Heat Island (UHI) is a fundamental effect modifying the urban climate, being widely studied, the relative weight of the parameters involved in its generation is still not clear. This paper investigates the hierarchy of importance of eight parameters responsible for UHI intensity in the Mediterranean context. Sensitivity analyses have been carried out using the Urban Weather Generator model, considering the range of variability of: 1) city radius, 2) urban morphology, 3) tree coverage, 4) anthropogenic heat from vehicles, 5) building’s cooling set point, 6) heat released to canyon from HVAC systems, 7) wall construction properties and 8) albedo of vertical and horizontal surfaces. Results show a clear hierarchy of significance among the considered parameters; the urban morphology is the most important variable, causing a relative change up to 120% of the annual average UHI intensity in the Mediterranean context. The impact of anthropogenic sources of heat such as cooling systems and vehicles is also significant. These results suggest that urban morphology parameters can be used as descriptors of the climatic performance of different urban areas, easing the work of urban planners and designers in understanding a complex physical phenomenon, such as the UHI.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling.

PubMed

Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha; Thompson, Jill; Zimmerman, Jess K; Murphy, Lora

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate. © 2017 John Wiley & Sons Ltd.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

USGS Publications Warehouse

Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha C.; Thompson, Jill; Zimmerman, Jess K.; Murphy, Lora

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured inter-annual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including above-ground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.

Design and simulation of 532nm Rayleigh-Mie Doppler wind Lidar system

NASA Astrophysics Data System (ADS)

Peng, Zhuang; Xie, Chenbo; Wang, Bangxin; Shen, Fahua; Tan, Min; Li, Lu; Zhang, Zhanye

2018-02-01

Wind is one of the most significant parameter in weather forecast and the research of climate.It is essential for the weather forecast seasonally to yearly ,atmospheric dynamics,study of thermodynamics and go into the water, chemistry and aerosol which are have to do with global climate statusto measure three-dimensional troposphericwind field accurately.Structure of the doppler wind lidar system which based on Fabry-Perot etalon is introduced detailedly. In this section,the key parameters of the triple Fabry-Perot etalon are optimized and this is the key point.The results of optimizing etalon are as follows:the FSR is 8GHz,the FWHM is1GHz,3.48 GHz is the separation distance between two edge channels,and the separation distance between locking channel and the left edge channel is 1.16 GHz. In this condition,the sensitivity of wind velocity of Mie scattering and Rayleigh scattering is both 0.70%/(m/s) when the temperature is 255K in the height of 5Km and there is no wind. The simulation to this system states that in+/-50m/s radial wind speed range, the wind speed bias induced by Mie signal is less than 0.15m/s from 5 to 50km altitude.

Climate Controls AM Fungal Distributions from Global to Local Scales

NASA Astrophysics Data System (ADS)

Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.

2016-12-01

Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal composition and root colonization, with weaker influences of plant identity and soil nutrients. These two studies across scales suggest prevailing effects of climate on AM fungal distributions. Thus, incorporating climate when forecasting future ranges of AM fungi will enhance predictions of AM fungal abundance and associated ecosystem functions.

Invasive potential of cattle fever ticks in the southern United States

PubMed Central

2014-01-01

Abstract' Background For >100 years cattle production in the southern United States has been threatened by cattle fever. It is caused by an invasive parasite-vector complex that includes the protozoan hemoparasites Babesia bovis and B. bigemina, which are transmitted among domestic cattle via Rhipicephalus tick vectors of the subgenus Boophilus. In 1906 an eradication effort was started and by 1943 Boophilus ticks had been confined to a narrow tick eradication quarantine area (TEQA) along the Texas-Mexico border. However, a dramatic increase in tick infestations in areas outside the TEQA over the last decade suggests these tick vectors may be poised to re-invade the southern United States. We investigated historical and potential future distributions of climatic habitats of cattle fever ticks to assess the potential for a range expansion. Methods We built robust spatial predictions of habitat suitability for the vector species Rhipicephalus (Boophilus) microplus and R. (B.) annulatus across the southern United States for three time periods: 1906, present day (2012), and 2050. We used analysis of molecular variance (AMOVA) to identify persistent tick occurrences and analysis of bias in the climate proximate to these occurrences to identify key environmental parameters associated with the ecology of both species. We then used ecological niche modeling algorithms GARP and Maxent to construct models that related known occurrences of ticks in the TEQA during 2001–2011 with geospatial data layers that summarized important climate parameters at all three time periods. Results We identified persistent tick infestations and specific climate parameters that appear to be drivers of ecological niches of the two tick species. Spatial models projected onto climate data representative of climate in 1906 reproduced historical pre-eradication tick distributions. Present-day predictions, although constrained to areas near the TEQA, extrapolated well onto climate projections for 2050. Conclusions Our models indicate the potential for range expansion of climate suitable for survival of R. microplus and R. annulatus in the southern United States by mid-century, which increases the risk of reintroduction of these ticks and cattle tick fever into major cattle producing areas. PMID:24742062

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

NASA Astrophysics Data System (ADS)

Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

2017-04-01

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to constrain model uncertainty for an - assumed to be - ungauged basin. This shows that our method is promising for reconstructing long-term flow data for ungauged catchments on the Pacific side of Central America, and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.

Indigenous Waters: Applying the SWAT Hydrological Model to the Lumbee River Watershed

NASA Astrophysics Data System (ADS)

Painter, J.; Singh, N.; Martin, K. L.; Vose, J. M.; Wear, D. N.; Emanuel, R. E.

2016-12-01

Hydrological modeling can reveal insight about how rainfall becomes streamflow in a watershed comprising heterogeneous soils, terrain and land cover. Modeling can also help disentangle predicted impacts of climate and land use change on hydrological processes. We applied a hydrological model to the Lumbee River watershed, also known as the Lumber River Watershed, in the coastal plain of North Carolina (USA) to better understand how streamflow may be impacted by predicted climate and land use change in the mid-21st century. The Lumbee River flows through a predominantly Native American community, which may be affected by changing water resources during this period. The long-term goal of our project is to predict the effects of climate and land use change on the Lumbee River watershed and on the Native community that relies upon the river. We applied the Soil & Water Assessment Tool for ArcGIS (ArcSWAT), which was calibrated to historical climate and USGS streamflow data during the late 20th century, and we determined frequency distributions for key model parameters that best predicted streamflow during this time period. After calibrating and validating the model during the historical period, we identified land use and climate projections to represent a range of future conditions in the watershed. Specifically, we selected downscaled climate forcing data from four general circulation models running the RCP8.5 scenario. We also selected land use projections from a cornerstone scenario of the USDA Forest Service's Southern Forest Futures Project. This presentation reports on our methods for propagating parameter and climatic uncertainty through model predictions, and it reports on spatial patterns of land use change predicted by the cornerstone scenario.

Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, FrançOis P.; Poulin, Annie; Leconte, Robert

2011-12-01

General circulation models (GCMs) and greenhouse gas emissions scenarios (GGES) are generally considered to be the two major sources of uncertainty in quantifying the climate change impacts on hydrology. Other sources of uncertainty have been given less attention. This study considers overall uncertainty by combining results from an ensemble of two GGES, six GCMs, five GCM initial conditions, four downscaling techniques, three hydrological model structures, and 10 sets of hydrological model parameters. Each climate projection is equally weighted to predict the hydrology on a Canadian watershed for the 2081-2100 horizon. The results show that the choice of GCM is consistently a major contributor to uncertainty. However, other sources of uncertainty, such as the choice of a downscaling method and the GCM initial conditions, also have a comparable or even larger uncertainty for some hydrological variables. Uncertainties linked to GGES and the hydrological model structure are somewhat less than those related to GCMs and downscaling techniques. Uncertainty due to the hydrological model parameter selection has the least important contribution among all the variables considered. Overall, this research underlines the importance of adequately covering all sources of uncertainty. A failure to do so may result in moderately to severely biased climate change impact studies. Results further indicate that the major contributors to uncertainty vary depending on the hydrological variables selected, and that the methodology presented in this paper is successful at identifying the key sources of uncertainty to consider for a climate change impact study.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-05-01

Physical parameterizations in General Circulation Models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage.

Solar Effects on Global Climate Due to Cosmic Rays and Solar Energetic Particles

NASA Technical Reports Server (NTRS)

Turco, R. P.; Raeder, J.; DAuria, R.

2005-01-01

Although the work reported here does not directly connect solar variability with global climate change, this research establishes a plausible quantitative causative link between observed solar activity and apparently correlated variations in terrestrial climate parameters. Specifically, we have demonstrated that ion-mediated nucleation of atmospheric particles is a likely, and likely widespread, phenomenon that relates solar variability to changes in the microphysical properties of clouds. To investigate this relationship, we have constructed and applied a new model describing the formation and evolution of ionic clusters under a range of atmospheric conditions throughout the lower atmosphere. The activation of large ionic clusters into cloud nuclei is predicted to be favorable in the upper troposphere and mesosphere, and possibly in the lower stratosphere. The model developed under this grant needs to be extended to include additional cluster families, and should be incorporated into microphysical models to further test the cause-and-effect linkages that may ultimately explain key aspects of the connections between solar variability and climate.

Calibration of the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

NASA Technical Reports Server (NTRS)

Thome, Kurtis; Barnes, Robert; Baize, Rosemary; O'Connell, Joseph; Hair, Jason

2010-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) plans to observe climate change trends over decadal time scales to determine the accuracy of climate projections. The project relies on spaceborne earth observations of SI-traceable variables sensitive to key decadal change parameters. The mission includes a reflected solar instrument retrieving at-sensor reflectance over the 320 to 2300 nm spectral range with 500-m spatial resolution and 100-km swath. Reflectance is obtained from the ratio of measurements of the earth s surface to those while viewing the sun relying on a calibration approach that retrieves reflectance with uncertainties less than 0.3%. The calibration is predicated on heritage hardware, reduction of sensor complexity, adherence to detector-based calibration standards, and an ability to simulate in the laboratory on-orbit sources in both size and brightness to provide the basis of a transfer to orbit of the laboratory calibration including a link to absolute solar irradiance measurements.

Surface radiation budget for climate applications

NASA Technical Reports Server (NTRS)

Suttles, J. T. (Editor); Ohring, G. (Editor)

1986-01-01

The Surface Radiation Budget (SRB) consists of the upwelling and downwelling radiation fluxes at the surface, separately determined for the broadband shortwave (SW) (0 to 5 micron) and longwave (LW) (greater than 5 microns) spectral regions plus certain key parameters that control these fluxes, specifically, SW albedo, LW emissivity, and surface temperature. The uses and requirements for SRB data, critical assessment of current capabilities for producing these data, and directions for future research are presented.

Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America—Modern data for climatic estimation from vegetation inventories

USGS Publications Warehouse

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

2012-01-01

Vegetation inventories (plant taxa present in a vegetation assemblage at a given site) can be used to estimate climatic parameters based on the identification of the range of a given parameter where all taxa in an assemblage overlap ("Mutual Climatic Range"). For the reconstruction of past climates from fossil or subfossil plant assemblages, we assembled the data necessary for such analyses for 530 woody plant taxa and eight climatic parameters in North America. Here we present examples of how these data can be used to obtain paleoclimatic estimates from botanical data in a straightforward, simple, and robust fashion. We also include matrices of climate parameter versus occurrence or nonoccurrence of the individual taxa. These relations are depicted graphically as histograms of the population distributions of the occurrences of a given taxon plotted against a given climatic parameter. This provides a new method for quantification of paleoclimatic parameters from fossil plant assemblages.

Harmonising and semantically linking key variables from in-situ observing networks of an Integrated Atlantic Ocean Observing System, AtlantOS

NASA Astrophysics Data System (ADS)

Darroch, Louise; Buck, Justin

2017-04-01

Atlantic Ocean observation is currently undertaken through loosely-coordinated, in-situ observing networks, satellite observations and data management arrangements at regional, national and international scales. The EU Horizon 2020 AtlantOS project aims to deliver an advanced framework for the development of an Integrated Atlantic Ocean Observing System that strengthens the Global Ocean Observing System (GOOS) and contributes to the aims of the Galway Statement on Atlantic Ocean Cooperation. One goal is to ensure that data from different and diverse in-situ observing networks are readily accessible and useable to a wider community, including the international ocean science community and other stakeholders in this field. To help achieve this goal, the British Oceanographic Data Centre (BODC) produced a parameter matrix to harmonise data exchange, data flow and data integration for the key variables acquired by multiple in-situ AtlantOS observing networks such as ARGO, Seafloor Mapping and OceanSITES. Our solution used semantic linking of controlled vocabularies and metadata for parameters that were "mappable" to existing EU and international standard vocabularies. An AtlantOS Essential Variables list of terms (aggregated level) based on Global Climate Observing System (GCOS) Essential Climate Variables (ECV), GOOS Essential Ocean Variables (EOV) and other key network variables was defined and published on the Natural Environment Research Council (NERC) Vocabulary Server (version 2.0) as collection A05 (http://vocab.nerc.ac.uk/collection/A05/current/). This new vocabulary was semantically linked to standardised metadata for observed properties and units that had been validated by the AtlantOS community: SeaDataNet parameters (P01), Climate and Forecast (CF) Standard Names (P07) and SeaDataNet units (P06). Observed properties were mapped to biological entities from the internationally assured AphiaID from the WOrld Register of Marine Species (WoRMS), http://www.marinespecies.org/aphia.php?p=webservice. The AtlantOS parameter matrix offers a way to harmonise the globally important variables (such as ECVs and EOVs) from in-situ observing networks that use different flavours of exchange formats based on SeaDataNet and CF parameter metadata. It also offers a way to standardise data in the wider Integrated Ocean Observing System. It uses sustainable and trusted standardised vocabularies that are governed by internationally renowned and long-standing organisations and is interoperable through the use of persistent resource identifiers, such as URNs and PURLs. It is the first step to integrating and serving data in a variety of international exchange formats using Application programming interfaces (API) improving both data discoverability and utility for users.

Observing the ExoEarth: Simulating the Retrieval of Exoplanet Parameters Using DSCOVR

NASA Astrophysics Data System (ADS)

Kane, S.; Cowan, N. B.; Domagal-Goldman, S. D.; Herman, J. R.; Robinson, T.; Stine, A.

2017-12-01

The field of exoplanets has rapidly expanded from detection to include exoplanet characterization. This has been enabled by developments such as the detection of terrestrial-sized planets and the use of transit spectroscopy to study exoplanet atmospheres. Studies of rocky planets are leading towards the direct imaging of exoplanets and the development of techniques to extract their intrinsic properties. The importance of properties such as rotation, albedo, and obliquity are significant since they inform planet formation theories and are key input parameters for Global Circulation Models used to determine surface conditions, including habitability. Thus, a complete characterization of exoplanets for understanding habitable climates requires the ability to measure these key planetary parameters. The retrieval of planetary rotation rates, albedos, and obliquities from highly undersampled imaging data can be honed using satellites designed to study the Earth's atmosphere. In this talk I will describe how the Deep Space Climate Observatory (DSCOVR) provides a unique opportunity to test such retrieval methods using data for the sunlit hemisphere of the Earth. Our methods use the high-resolution DSCOVR-EPIC images to simulate the Earth as an exoplanet, by deconvolving the images to match a variety of expected exoplanet mission requirements, and by comparing EPIC data with the cavity radiometer data from DSCOVR-NISTAR that views the Earth as a single pixel. Through this methodology, we are creating a grid of retrieval states as a function of image resolution, observing cadence, passband, etc. Our modeling of the DSCOVR data will provide an effective baseline from which to develop tools that can be applied to a variety of exoplanet imaging data.

Environmental conditions regulate the impact of plants on cloud formation

PubMed Central

Zhao, D. F.; Buchholz, A.; Tillmann, R.; Kleist, E.; Wu, C.; Rubach, F.; Kiendler-Scharr, A.; Rudich, Y.; Wildt, J.; Mentel, Th. F.

2017-01-01

The terrestrial vegetation emits large amounts of volatile organic compounds (VOC) into the atmosphere, which on oxidation produce secondary organic aerosol (SOA). By acting as cloud condensation nuclei (CCN), SOA influences cloud formation and climate. In a warming climate, changes in environmental factors can cause stresses to plants, inducing changes of the emitted VOC. These can modify particle size and composition. Here we report how induced emissions eventually affect CCN activity of SOA, a key parameter in cloud formation. For boreal forest tree species, insect infestation by aphids causes additional VOC emissions which modifies SOA composition thus hygroscopicity and CCN activity. Moderate heat increases the total amount of constitutive VOC, which has a minor effect on hygroscopicity, but affects CCN activity by increasing the particles' size. The coupling of plant stresses, VOC composition and CCN activity points to an important impact of induced plant emissions on cloud formation and climate. PMID:28218253

Environmental conditions regulate the impact of plants on cloud formation.

PubMed

Zhao, D F; Buchholz, A; Tillmann, R; Kleist, E; Wu, C; Rubach, F; Kiendler-Scharr, A; Rudich, Y; Wildt, J; Mentel, Th F

2017-02-20

The terrestrial vegetation emits large amounts of volatile organic compounds (VOC) into the atmosphere, which on oxidation produce secondary organic aerosol (SOA). By acting as cloud condensation nuclei (CCN), SOA influences cloud formation and climate. In a warming climate, changes in environmental factors can cause stresses to plants, inducing changes of the emitted VOC. These can modify particle size and composition. Here we report how induced emissions eventually affect CCN activity of SOA, a key parameter in cloud formation. For boreal forest tree species, insect infestation by aphids causes additional VOC emissions which modifies SOA composition thus hygroscopicity and CCN activity. Moderate heat increases the total amount of constitutive VOC, which has a minor effect on hygroscopicity, but affects CCN activity by increasing the particles' size. The coupling of plant stresses, VOC composition and CCN activity points to an important impact of induced plant emissions on cloud formation and climate.

Site-specific climate analysis elucidates revegetation challenges for post-mining landscapes in eastern Australia

NASA Astrophysics Data System (ADS)

Audet, P.; Arnold, S.; Lechner, A. M.; Baumgartl, T.

2013-10-01

In eastern Australia, the availability of water is critical for the successful rehabilitation of post-mining landscapes and climatic characteristics of this diverse geographical region are closely defined by factors such as erratic rainfall and periods of drought and flooding. Despite this, specific metrics of climate patterning are seldom incorporated into the initial design of current post-mining land rehabilitation strategies. Our study proposes that a few common rainfall parameters can be combined and rated using arbitrary rainfall thresholds to characterise bioregional climate sensitivity relevant to the rehabilitation these landscapes. This approach included assessments of annual rainfall depth, average recurrence interval of prolonged low intensity rainfall, average recurrence intervals of short or prolonged high intensity events, median period without rain (or water-deficit) and standard deviation for this period in order to address climatic factors such as total water availability, seasonality and intensity - which were selected as potential proxies of both short- and long-term biological sensitivity to climate within the context of post-disturbance ecological development and recovery. Following our survey of available climate data, we derived site "climate sensitivity" indexes and compared the performance of 9 ongoing mine sites: Weipa, Mt. Isa and Cloncurry, Eromanga, Kidston, the Bowen Basin (Curragh), Tarong, North Stradbroke Island, and the Newnes Plateau. The sites were then ranked from most-to-least sensitive and compared with natural bioregional patterns of vegetation density using mean NDVI. It was determined that regular rainfall and relatively short periods of water-deficit were key characteristics of sites having less sensitivity to climate - as found among the relatively more temperate inland mining locations. Whereas, high rainfall variability, frequently occurring high intensity events, and (or) prolonged seasonal drought were primary indicators of sites having greater sensitivity to climate - as found among the semi-arid central-inland sites. Overall, the manner in which these climatic factors are identified and ultimately addressed by land managers and rehabilitation practitioners could be a key determinant of achievable success at given locations at the planning stages of rehabilitation design.

The Chew Bahir Drilling Project (HSPDP). Deciphering climate information from the Chew Bahir sediment cores: Towards a continuous half-million year climate record near the Omo - Turkana key palaeonanthropological Site

NASA Astrophysics Data System (ADS)

Foerster, Verena E.; Asrat, Asfawossen; Chapot, Melissa S.; Cohen, Andrew S.; Dean, Jonathan R.; Deino, Alan; Günter, Christina; Junginger, Annett; Lamb, Henry F.; Leng, Melanie J.; Roberts, Helen M.; Schaebitz, Frank; Trauth, Martin H.

2017-04-01

As a contribution towards an enhanced understanding of human-climate interactions, the Hominin Sites and Paleolakes Drilling Project (HSPDP) has successfully completed coring five dominantly lacustrine archives of climate change during the last 3.5 Ma in East Africa. All five sites in Ethiopia and Kenya are adjacent to key paleoanthropological research areas encompassing diverse milestones in human evolution, dispersal episodes, and technological innovation. The 280 m-long Chew Bahir sediment records, recovered from a tectonically-bound basin in the southern Ethiopian rift in late 2014, cover the past 550 ka of environmental history, a time period that includes the transition to the Middle Stone Age, and the origin and dispersal of modern Homo sapiens. Deciphering climate information from lake sediments is challenging, due to the complex relationship between climate parameters and sediment composition. We will present the first results in our efforts to develop a reliable climate-proxy tool box for Chew Bahir by deconvolving the relationship between sedimentological and geochemical sediment composition and strongly climate-controlled processes in the basin, such as incongruent weathering, transportation and authigenic mineral alteration. Combining our first results from the long cores with those from a pilot study of short cores taken in 2009/10 along a NW-SE transect of the basin, we have developed a hypothesis linking climate forcing and paleoenvironmental signal-formation processes in the basin. X-ray diffraction analysis of the first sample sets from the long Chew Bahir record reveals similar processes that have been recognized for the uppermost 20 m during the pilot-study of the project: the diagenetic illitization of smectites during episodes of higher alkalinity and salinity in the closed-basin lake induced by a drier climate. The precise time resolution, largely continuous record and (eventually) a detailed understanding of site specific proxy formation, will give us a continuous record of environmental history on decadal to orbital timescales. Our data enable us to test current hypotheses of the impact of a variety of climate shifts on human evolution and dispersal.

Modelling predicts that tolerance to drought during reproductive development will be required for high yield potential and stability of wheat in Europe

NASA Astrophysics Data System (ADS)

Semenov, Mikhail A.; Stratonovitch, Pierre; Paul, Matthew J.

2017-04-01

Short periods of extreme weather, such as a spell of high temperature or drought during a sensitive stage of development, could result in substantial yield losses due to reduction in grain number and grain size. In a modelling study (Stratonovitch & Semenov 2015), heat tolerance around flowering in wheat was identified as a key trait for increased yield potential in Europe under climate change. Ji et all (Ji et al. 2010) demonstrated cultivar specific responses of yield to drought stress around flowering in wheat. They hypothesised that carbohydrate supply to anthers may be the key in maintaining pollen fertility and grain number in wheat. It was shown in (Nuccio et al. 2015) that genetically modified varieties of maize that increase the concentration of sucrose in ear spikelets, performed better under non-drought and drought conditions in field experiments. The objective of this modelling study was to assess potential benefits of tolerance to drought during reproductive development for wheat yield potential and yield stability across Europe. We used the Sirius wheat model to optimise wheat ideotypes for 2050 (HadGEM2, RCP8.5) climate scenarios at selected European sites. Eight cultivar parameters were optimised to maximise mean yields, including parameters controlling phenology, canopy growth and water limitation. At those sites where water could be limited, ideotypes sensitive to drought produced substantially lower mean yields and higher yield variability compare with tolerant ideotypes. Therefore, tolerance to drought during reproductive development is likely to be required for wheat cultivars optimised for the future climate in Europe in order to achieve high yield potential and yield stability.

Estimation of Pre-industrial Nitrous Oxide Emission from the Terrestrial Biosphere

NASA Astrophysics Data System (ADS)

Xu, R.; Tian, H.; Lu, C.; Zhang, B.; Pan, S.; Yang, J.

2015-12-01

Nitrous oxide (N2O) is currently the third most important greenhouse gases (GHG) after methane (CH4) and carbon dioxide (CO2). Global N2O emission increased substantially primarily due to reactive nitrogen (N) enrichment through fossil fuel combustion, fertilizer production, and legume crop cultivation etc. In order to understand how climate system is perturbed by anthropogenic N2O emissions from the terrestrial biosphere, it is necessary to better estimate the pre-industrial N2O emissions. Previous estimations of natural N2O emissions from the terrestrial biosphere range from 3.3-9.0 Tg N2O-N yr-1. This large uncertainty in the estimation of pre-industrial N2O emissions from the terrestrial biosphere may be caused by uncertainty associated with key parameters such as maximum nitrification and denitrification rates, half-saturation coefficients of soil ammonium and nitrate, N fixation rate, and maximum N uptake rate. In addition to the large estimation range, previous studies did not provide an estimate on preindustrial N2O emissions at regional and biome levels. In this study, we applied a process-based coupled biogeochemical model to estimate the magnitude and spatial patterns of pre-industrial N2O fluxes at biome and continental scales as driven by multiple input data, including pre-industrial climate data, atmospheric CO2 concentration, N deposition, N fixation, and land cover types and distributions. Uncertainty associated with key parameters is also evaluated. Finally, we generate sector-based estimates of pre-industrial N2O emission, which provides a reference for assessing the climate forcing of anthropogenic N2O emission from the land biosphere.

Extensions and applications of a second-order landsurface parameterization

NASA Technical Reports Server (NTRS)

Andreou, S. A.; Eagleson, P. S.

1983-01-01

Extensions and applications of a second order land surface parameterization, proposed by Andreou and Eagleson are developed. Procedures for evaluating the near surface storage depth used in one cell land surface parameterizations are suggested and tested by using the model. Sensitivity analysis to the key soil parameters is performed. A case study involving comparison with an "exact" numerical model and another simplified parameterization, under very dry climatic conditions and for two different soil types, is also incorporated.

Flexible parameter-sparse global temperature time profiles that stabilise at 1.5 and 2.0 °C

NASA Astrophysics Data System (ADS)

Huntingford, Chris; Yang, Hui; Harper, Anna; Cox, Peter M.; Gedney, Nicola; Burke, Eleanor J.; Lowe, Jason A.; Hayman, Garry; Collins, William J.; Smith, Stephen M.; Comyn-Platt, Edward

2017-07-01

The meeting of the United Nations Framework Convention on Climate Change (UNFCCC) in December 2015 committed parties at the convention to hold the rise in global average temperature to well below 2.0 °C above pre-industrial levels. It also committed the parties to pursue efforts to limit warming to 1.5 °C. This leads to two key questions. First, what extent of emissions reduction will achieve either target? Second, what is the benefit of the reduced climate impacts from keeping warming at or below 1.5 °C? To provide answers, climate model simulations need to follow trajectories consistent with these global temperature limits. It is useful to operate models in an inverse mode to make model-specific estimates of greenhouse gas (GHG) concentration pathways consistent with the prescribed temperature profiles. Further inversion derives related emissions pathways for these concentrations. For this to happen, and to enable climate research centres to compare GHG concentrations and emissions estimates, common temperature trajectory scenarios are required. Here we define algebraic curves that asymptote to a stabilised limit, while also matching the magnitude and gradient of recent warming levels. The curves are deliberately parameter-sparse, needing the prescription of just two parameters plus the final temperature. Yet despite this simplicity, they can allow for temperature overshoot and for generational changes, for which more effort to decelerate warming change needs to be made by future generations. The curves capture temperature profiles from the existing Representative Concentration Pathway (RCP2.6) scenario projections by a range of different Earth system models (ESMs), which have warming amounts towards the lower levels of those that society is discussing.

School Climate Improvement Action Guide for Working with Students. School Climate Improvement Resource Package

ERIC Educational Resources Information Center

National Center on Safe Supportive Learning Environments, 2017

2017-01-01

Improving school climate takes time and commitment from a variety of people in a variety of roles. This document outlines key action steps to engage students in the school climate improvement process. Key action steps are provided for the following strategies: (1) Participate in planning for school climate improvements; (2) Engage stakeholders in…

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-11-01

Physical parameterizations in general circulation models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time-consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determining the model's sensitivity to the parameters and the other choosing the optimum initial value for those sensitive parameters, are introduced before the downhill simplex method. This new method reduces the number of parameters to be tuned and accelerates the convergence of the downhill simplex method. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

Climate Change Tower Integrated Project (CCT-IP) A scientific platform to investigate processes at the surface and in the low troposphere

NASA Astrophysics Data System (ADS)

Vitale, Vito; Udisti, Roberto

2010-05-01

V.Vitale, R.Udisti, A.Viola, S.Argentini, M.Nardino, C.Lanconelli, M. Mazzola, T.Georgiadis, R.Salvatori, A.Ianniello, C.Turetta, C.Barbante, F.Spataro, M.Valt, F.Cairo, L.Diliberto, S.Becagli, R.Sparapani, R. Casacchia ************************************************************************ To improve parameterization and reduce uncertainties in climate models, experimental measurements are needed to deep the knowledge on the complex physico-chemical process that characterize the Arctic troposphere and the air-sea-land interaction. Svalbard Islands, located at the northernmost margin of the southern warm current of the Atlantic Ocean, lies in an ideal position to study the combined effects of climate change affecting the atmosphere, as well as the ocean and land. Furthermore, Ny-Ålesund represents a unique site, where international cooperation among countries can allow the monitoring of a greater number of key parameters of the Arctic physical and chemical systems. Based on these remarks, since 2008, CNR Earth and Environment Department sustained and funded the Climate Change Integrate Project ( CCT-IP) in the Kongsfjorden area, aiming to setup a scientific platform at the Italian station "Dirigibile Italia", in Ny Alesund. This platform will be able to complement research activities provided by other national (MIUR-PRIN07) and international research programs. In the framework of this project, it was planned obtaining a comprehensive data set of physical and chemical atmospheric parameters, useful to determine all components of the energy budget at the surface, their temporal variations, and role played by different processes involving air, aerosol, snow, ice and land (permafrost and vegetation). Key element of such platform is the new 32 m high Admundsen-Nobile Climate Change Tower (CCT) that will allow to deeply investigate energy budget and the atmospheric boundary layer dynamics and exchange fluxes (heat, momentum, chemical substances) at the surface. A first set of instruments to measure the radiation balance, surface albedo, the vertical profile of meteorological parameters and the heat flux at the air -snow interface has been installed in September 2009. The on-site measurements are continously running and the data are sent in Italy via a internet connection and stored in a comprehensive database A six months intensive field campaign will start in March 2010 to measure physical characteristics and chemical composition of the aerosol and snow, the down and upwelling mass fluxes of aerosols and gaseous substances and short-lived pollutants (SLPs). These measurements will improve our knowledge on the processes controlling sources, transport processes and atmospheric transformation of chemical compound in snow and aerosol, useful as environmental and climatic marker, and will highlight the importance of local surface processes with respect of large scale transport processes.

Seasonal Correlations of SST, Water Vapor, and Convective Activity in Tropical Oceans: A New Hyperspectral Data Set for Climate Model Testing

NASA Technical Reports Server (NTRS)

Aumann, Hartmut H.; Gregorich, David T.; Broberg, Steven E.; Elliott, Denis A.

2007-01-01

The analysis of the response of the Earth Climate System to the seasonal changes of solar forcing in the tropical oceans using four years of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) data between 2002 and 2006 gives new insight into amplitude and phase relationships between surface and tropospheric temperatures, humidity, and convective activity. The intensity of the convective activity is measured by counting deep convective clouds. The peaks of convective activity, temperature in the mid-troposphere, and water vapor in the 0 - 30 N and 0 - 30 S tropical ocean zonal means occur about two months after solstice, all leading the peak of the sea surface temperature by several weeks. Phase is key to the evaluation of feedback. The evaluation of climate models in terms of zonal and annual means and annual mean deviations from zonal means can now be supplemented by evaluating the phase of key atmospheric and surface parameters relative to solstice. The ability of climate models to reproduce the statistical flavor of the observed amplitudes and relative phases for broad zonal means should lead to increased confidence in the realism of their water vapor and cloud feedback algorithms. AIRS and AMSU were launched into a 705 km altitude polar sun-synchronous orbit on the EOS Aqua spacecraft on May 4, 2002, and have been in routine data gathering mode since September 2002.

Seasonal Correlations of SST, Water Vapor, and Convective Activity in Tropical Oceans: A New Hyperspectral Data Set for Climate Model Testing

NASA Technical Reports Server (NTRS)

Aumann, Hartmut H.; Gregorich, David T.; Broberg, Steven E.; Elliott, Denis A.

2007-01-01

The analysis of the response of the Earth Climate System to the seasonal changes of solar forcing in the tropical oceans using four years of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) data between 2002 and 2006 gives new insight into amplitude and phase relationships between surface and tropospheric temperatures, humidity, and convective activity. The intensity of the convective activity is measured by counting deep convective clouds. The peaks of convective activity, temperature in the mid-troposphere, and water vapor in the 0-30 N and 0-30 S tropical ocean zonal means occur about two months after solstice, all leading the peak of the sea surface temperature by several weeks. Phase is key to the evaluation of feedback. The evaluation of climate models in terms of zonal and annual means and annual mean deviations from zonal means can now be supplemented by evaluating the phase of key atmospheric and surface parameters relative to solstice. The ability of climate models to reproduce the statistical flavor of the observed amplitudes and relative phases for broad zonal means should lead to increased confidence in the realism of their water vapor and cloud feedback algorithms. AIRS and AMSU were launched into a 705 km altitude polar sun-synchronous orbit on the EOS Aqua spacecraft on May 4, 2002, and have been in routine data gathering mode since September 2002.

Identifying water mass depletion in northern Iraq observed by GRACE

NASA Astrophysics Data System (ADS)

Mulder, G.; Olsthoorn, T. N.; Al-Manmi, D. A. M. A.; Schrama, E. J. O.; Smidt, E. H.

2015-03-01

Observations acquired by Gravity Recovery And Climate Experiment (GRACE) mission indicate a mass loss of 146 ± 6 mm equivalent water height (EWH) in northern Iraq between 2007 and 2009. These data are used as an independent validation of lake mass variations and a rainfall-runoff model, which is based on local geology and climate conditions. Model inputs are precipitation from Tropical Rainfall Measurement Mission (TRMM) observations, and climatic parameters from Global Land Data Assimilation Systems (GLDAS) model parameters. The model is calibrated with observed river discharge and includes a representation of the karstified aquifers in the region to improve model realism. Lake mass variations were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) in combination with satellite altimetry and some in situ data. Our rainfall-runoff model confirms that northern Iraq suffered a drought between 2007 and 2009 and captures the annual cycle and longer trend of the observed GRACE data. The total mass depletion seen by GRACE between 2007 and 2009 is mainly explained by a lake mass depletion of 75 ± 3 mm EWH and a natural groundwater depletion of 39 ± 8 mm EWH. Our findings indicate that anthropogenic groundwater extraction has a minor influence in this region, while a decline in lake mass and natural depletion of groundwater play a key role.

Utilization of GPS Tropospheric Delays for Climate Research

NASA Astrophysics Data System (ADS)

Suparta, Wayan

2017-05-01

The tropospheric delay is one of the main error sources in Global Positioning Systems (GPS) and its impact plays a crucial role in near real-time weather forecasting. Accessibility and accurate estimation of this parameter are essential for weather and climate research. Advances in GPS application has allowed the measurements of zenith tropospheric delay (ZTD) in all weather conditions and on a global scale with fine temporal and spatial resolution. In addition to the rapid advancement of GPS technology and informatics and the development of research in the field of Earth and Planetary Sciences, the GPS data has been available free of charge. Now only required sophisticated processing techniques but user friendly. On the other hand, the ZTD parameter obtained from the models or measurements needs to be converted into precipitable water vapor (PWV) to make it more useful as a component of weather forecasting and analysis atmospheric hazards such as tropical storms, flash floods, landslide, pollution, and earthquake as well as for climate change studies. This paper addresses the determination of ZTD as a signal error or delay source during the propagation from the satellite to a receiver on the ground and is a key driving force behind the atmospheric events. Some results in terms of ZTD and PWV will be highlighted in this paper.

Study of gravity waves propagation in the thermosphere of Mars based on MAVEN/NGIMS density measurements

NASA Astrophysics Data System (ADS)

Vals, M.

2017-09-01

We use MAVEN/NGIMS CO2 density measurements to analyse gravity waves in the thermosphere of Mars. In particular the seasonal/latitudinal variability of their amplitude is studied and interpreted. Key background parameters controlling the activity of gravity waves are analysed with the help of the Mars Climate Database (MCD). Gravity waves activity presents a good anti-correlation to the temperature variability retrieved from the MCD. An analysis at pressure levels is ongoing.

Remote sensing of the atmosphere of Mars using infrared pressure modulation and filter radiometry

NASA Technical Reports Server (NTRS)

Mccleese, D. J.; Schofield, J. T.; Zurek, R. W.; Martonchik, J. V.; Haskins, R. D.

1986-01-01

The study of the atmosphere and climate of Mars will soon be advanced considerably by the Mars Observer mission. This paper describes the atmospheric sounder for this mission and how it will measure key Martian atmospheric parameters using IR gas correlation and filter radiometry. The instrument now under development will provide high-resolution vertical profiles of atmospheric temperature, pressure, water vapor, dust, and clouds using limb sounding techniques as well as nadir observations of surface thermal properties and polar radiative balance.

Evaluating Ammonium, Nitrate and Sulfate Aerosols in 3-Dimensions

NASA Technical Reports Server (NTRS)

Mezuman, Keren; Bauer, Susanne E.; Tsigaridis, Kostas

2015-01-01

The effect aerosols have on climate and air quality is a func-on of their chemical composi-on, concentra-on and spa-al distribu-on. These parameters are controlled by emissions, heterogeneous and homogeneous chemistry, where thermodynamics plays a key role, transport, which includes stratospheric-­- tropospheric exchange, and deposi-onal sinks. In this work we demonstrate the effect of some of these processes on the SO4-NH4­-NO3 system using the GISS ModelE2 Global Circula-on Model (GCM).

School Climate Improvement Action Guide for District Leaders. School Climate Improvement Resource Package

ERIC Educational Resources Information Center

National Center on Safe Supportive Learning Environments, 2017

2017-01-01

Improving school climate takes time and commitment from a variety of people in a variety of roles. This document outlines key action steps that district leaders--including superintendents, assistant superintendents, directors of student support services, or others--can take to support school climate improvements. Key action steps are provided for…

Break and trend analysis of EUMETSAT Climate Data Records

NASA Astrophysics Data System (ADS)

Doutriaux-Boucher, Marie; Zeder, Joel; Lattanzio, Alessio; Khlystova, Iryna; Graw, Kathrin

2016-04-01

EUMETSAT reprocessed imagery acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat 8-9. The data covers the period from 2004 to 2012. Climate Data Records (CDRs) of atmospheric parameters such as Atmospheric Motion Vectors (AMV) as well as Clear and All Sky Radiances (CSR and ASR) have been generated. Such CDRs are mainly ingested by ECMWF to produce a reanalysis data. In addition, EUMETSAT produced a long CDR (1982-2004) of land surface albedo exploiting imagery acquired by the Meteosat Visible and Infrared Imager (MVIRI) on board Meteosat 2-7. Such CDR is key information in climate analysis and climate models. Extensive validation has been performed for the surface albedo record and a first validation of the winds and clear sky radiances have been done. All validation results demonstrated that the time series of all parameter appear homogeneous at first sight. Statistical science offers a variety of analyses methods that have been applied to further analyse the homogeneity of the CDRs. Many breakpoint analysis techniques depend on the comparison of two time series which incorporates the issue that both may have breakpoints. This paper will present a quantitative and statistical analysis of eventual breakpoints found in the MVIRI and SEVIRI CDRs that includes attribution of breakpoints to changes of instruments and other events in the data series compared. The value of different methods applied will be discussed with suggestions how to further develop this type of analysis for quality evaluation of CDRs.

Effect of Simultaneous Inoculation with Yeast and Bacteria on Fermentation Kinetics and Key Wine Parameters of Cool-Climate Chardonnay

PubMed Central

Jussier, Delphine; Dubé Morneau, Amélie; Mira de Orduña, Ramón

2006-01-01

Inoculating grape musts with wine yeast and lactic acid bacteria (LAB) concurrently in order to induce simultaneous alcoholic fermentation (AF) and malolactic fermentation (MLF) can be an efficient alternative to overcome potential inhibition of LAB in wines because of high ethanol concentrations and reduced nutrient content. In this study, the simultaneous inoculation of yeast and LAB into must was compared with a traditional vinification protocol, where MLF was induced after completion of AF. For this, two suitable commercial yeast-bacterium combinations were tested in cool-climate Chardonnay must. The time courses of glucose and fructose, acetaldehyde, several organic acids, and nitrogenous compounds were measured along with the final values of other key wine parameters. Sensory evaluation was done after 12 months of storage. The current study could not confirm a negative impact of simultaneous AF/MLF on fermentation success and kinetics or on final wine parameters. While acetic acid concentrations were slightly increased in wines after simultaneous AF/MLF, the differences were of neither practical nor legal significance. No statistically significant differences were found with regard to the final values of pH or total acidity and the concentrations of ethanol, acetaldehyde, glycerol, citric and lactic acids, and the nitrogen compounds arginine, ammonia, urea, citrulline, and ornithine. Sensory evaluation by a semiexpert panel confirmed the similarity of the wines. However, simultaneous inoculation led to considerable reductions in overall fermentation durations. Furthermore, differences of physiological and microbiological relevance were found. Specifically, we report the vinification of “super-dry” wines devoid of glucose and fructose after simultaneous inoculation of yeast and bacteria. PMID:16391046

Statistical methods for the analysis of climate extremes

NASA Astrophysics Data System (ADS)

Naveau, Philippe; Nogaj, Marta; Ammann, Caspar; Yiou, Pascal; Cooley, Daniel; Jomelli, Vincent

2005-08-01

Currently there is an increasing research activity in the area of climate extremes because they represent a key manifestation of non-linear systems and an enormous impact on economic and social human activities. Our understanding of the mean behavior of climate and its 'normal' variability has been improving significantly during the last decades. In comparison, climate extreme events have been hard to study and even harder to predict because they are, by definition, rare and obey different statistical laws than averages. In this context, the motivation for this paper is twofold. Firstly, we recall the basic principles of Extreme Value Theory that is used on a regular basis in finance and hydrology, but it still does not have the same success in climate studies. More precisely, the theoretical distributions of maxima and large peaks are recalled. The parameters of such distributions are estimated with the maximum likelihood estimation procedure that offers the flexibility to take into account explanatory variables in our analysis. Secondly, we detail three case-studies to show that this theory can provide a solid statistical foundation, specially when assessing the uncertainty associated with extreme events in a wide range of applications linked to the study of our climate. To cite this article: P. Naveau et al., C. R. Geoscience 337 (2005).

Climate sensitivity uncertainty: when is good news bad?

PubMed

Freeman, Mark C; Wagner, Gernot; Zeckhauser, Richard J

2015-11-28

Climate change is real and dangerous. Exactly how bad it will get, however, is uncertain. Uncertainty is particularly relevant for estimates of one of the key parameters: equilibrium climate sensitivity--how eventual temperatures will react as atmospheric carbon dioxide concentrations double. Despite significant advances in climate science and increased confidence in the accuracy of the range itself, the 'likely' range has been 1.5-4.5°C for over three decades. In 2007, the Intergovernmental Panel on Climate Change (IPCC) narrowed it to 2-4.5°C, only to reverse its decision in 2013, reinstating the prior range. In addition, the 2013 IPCC report removed prior mention of 3°C as the 'best estimate'. We interpret the implications of the 2013 IPCC decision to lower the bottom of the range and excise a best estimate. Intuitively, it might seem that a lower bottom would be good news. Here we ask: when might apparently good news about climate sensitivity in fact be bad news in the sense that it lowers societal well-being? The lowered bottom value also implies higher uncertainty about the temperature increase, definitely bad news. Under reasonable assumptions, both the lowering of the lower bound and the removal of the 'best estimate' may well be bad news. © 2015 The Author(s).

Climatic Forecasting of Net Infiltration at Yucca Mountain, Using Analogue Meteorological Data

NASA Astrophysics Data System (ADS)

Faybishenko, B.

2005-12-01

Net infiltration is a key hydrologic parameter that, throughout the unsaturated zone, controls the rate of deep percolation, the groundwater recharge, radionuclide transport, and seepage into underground tunnels. Because net infiltration is largely affected by climatic conditions, future changes in climatic conditions will potentially alter net infiltration. The objectives of this presentation are to: (1) Present a conceptual model and a semi-empirical approach for regional climatic forecasting of net infiltration, based on precipitation and temperature data from analogue meteorological stations; and (2) Demonstrate the results of forecasting net infiltration for future climates - interglacial, monsoon and glacial - over the Yucca Mountain region for a period of 500,000 years. Calculations of net infiltration were performed using a modified Budyko's water-balance model, and potential evapotranspiration was evaluated from the temperature-based Thornthwaite formula. (Both Budyko's and Thornthwaite's formulae have been used broadly in hydrological studies.) The results of these calculations were used for ranking net infiltration, along with aridity and precipitation-effectiveness (P-E) indices, for future climatic scenarios. Using this approach, we determined a general trend of increasing net infiltration from the present-day (interglacial) climate to the monsoon, intermediate (glacial transition) climate, a trend that continued into the glacial climate time frame. The ranking of aridity and P-E indices is practically the same as that for net infiltration. Validation of the computed net infiltration rates yielded a good match with other field and modeling study results related to groundwater recharge and net infiltration evaluation.

Data-Conditioned Distributions of Groundwater Recharge Under Climate Change Scenarios

NASA Astrophysics Data System (ADS)

McLaughlin, D.; Ng, G. C.; Entekhabi, D.; Scanlon, B.

2008-12-01

Groundwater recharge is likely to be impacted by climate change, with changes in precipitation amounts altering moisture availability and changes in temperature affecting evaporative demand. This could have major implications for sustainable aquifer pumping rates and contaminant transport into groundwater reservoirs in the future, thus making predictions of recharge under climate change very important. Unfortunately, in dry environments where groundwater resources are often most critical, low recharge rates are difficult to resolve due to high sensitivity to modeling and input errors. Some recent studies on climate change and groundwater have considered recharge using a suite of general circulation model (GCM) weather predictions, an obvious and key source of uncertainty. This work extends beyond those efforts by also accounting for uncertainty in other land-surface model inputs in a probabilistic manner. Recharge predictions are made using a range of GCM projections for a rain-fed cotton site in the semi-arid Southern High Plains region of Texas. Results showed that model simulations using a range of unconstrained literature-based parameter values produce highly uncertain and often misleading recharge rates. Thus, distributional recharge predictions are found using soil and vegetation parameters conditioned on current unsaturated zone soil moisture and chloride concentration observations; assimilation of observations is carried out with an ensemble importance sampling method. Our findings show that the predicted distribution shapes can differ for the various GCM conditions considered, underscoring the importance of probabilistic analysis over deterministic simulations. The recharge predictions indicate that the temporal distribution (over seasons and rain events) of climate change will be particularly critical for groundwater impacts. Overall, changes in recharge amounts and intensity were often more pronounced than changes in annual precipitation and temperature, thus suggesting high susceptibility of groundwater systems to future climate change. Our approach provides a probabilistic sensitivity analysis of recharge under potential climate changes, which will be critical for future management of water resources.

School Climate Improvement Action Guide for Instructional Staff. School Climate Improvement Resource Package

ERIC Educational Resources Information Center

National Center on Safe Supportive Learning Environments, 2017

2017-01-01

Improving school climate takes time and commitment from a variety of people in a variety of roles. This document outlines key action steps that instructional staff--including teachers, paraprofessionals, and others in the classroom who provide instruction or assistance--can take to support school climate improvements. Key action steps are provided…

School Climate Improvement Action Guide for School Leaders. School Climate Improvement Resource Package

ERIC Educational Resources Information Center

National Center on Safe Supportive Learning Environments, 2017

2017-01-01

Improving school climate takes time and commitment from a variety of people in a variety of roles. This document outlines key action steps that school leaders--including principals, assistant/vice principals, and building leaders--can take to support school climate improvements. Key action steps are provided for the following strategies: (1)…

State and Parameter Estimation for a Coupled Ocean--Atmosphere Model

NASA Astrophysics Data System (ADS)

Ghil, M.; Kondrashov, D.; Sun, C.

2006-12-01

The El-Nino/Southern-Oscillation (ENSO) dominates interannual climate variability and plays, therefore, a key role in seasonal-to-interannual prediction. Much is known by now about the main physical mechanisms that give rise to and modulate ENSO, but the values of several parameters that enter these mechanisms are an important unknown. We apply Extended Kalman Filtering (EKF) for both model state and parameter estimation in an intermediate, nonlinear, coupled ocean--atmosphere model of ENSO. The coupled model consists of an upper-ocean, reduced-gravity model of the Tropical Pacific and a steady-state atmospheric response to the sea surface temperature (SST). The model errors are assumed to be mainly in the atmospheric wind stress, and assimilated data are equatorial Pacific SSTs. Model behavior is very sensitive to two key parameters: (i) μ, the ocean-atmosphere coupling coefficient between SST and wind stress anomalies; and (ii) δs, the surface-layer coefficient. Previous work has shown that δs determines the period of the model's self-sustained oscillation, while μ measures the degree of nonlinearity. Depending on the values of these parameters, the spatio-temporal pattern of model solutions is either that of a delayed oscillator or of a westward propagating mode. Estimation of these parameters is tested first on synthetic data and allows us to recover the delayed-oscillator mode starting from model parameter values that correspond to the westward-propagating case. Assimilation of SST data from the NCEP-NCAR Reanalysis-2 shows that the parameters can vary on fairly short time scales and switch between values that approximate the two distinct modes of ENSO behavior. Rapid adjustments of these parameters occur, in particular, during strong ENSO events. Ways to apply EKF parameter estimation efficiently to state-of-the-art coupled ocean--atmosphere GCMs will be discussed.

Watershed-scale response to climate change through the twenty-first century for selected basins across the United States

USGS Publications Warehouse

Hay, Lauren E.; Markstrom, Steven; Ward-Garrison, Christian D.

2011-01-01

The hydrologic response of different climate-change emission scenarios for the twenty-first century were evaluated in 14 basins from different hydroclimatic regions across the United States using the Precipitation-Runoff Modeling System (PRMS), a process-based, distributed-parameter watershed model. This study involves four major steps: 1) setup and calibration of the PRMS model in 14 basins across the United States by local U.S. Geological Survey personnel; 2) statistical downscaling of the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3 climate-change emission scenarios to create PRMS input files that reflect these emission scenarios; 3) run PRMS for the climate-change emission scenarios for the 14 basins; and 4) evaluation of the PRMS output.This paper presents an overview of this project, details of the methodology, results from the 14 basin simulations, and interpretation of these results. A key finding is that the hydrological response of the different geographical regions of the United States to potential climate change may be very different, depending on the dominant physical processes of that particular region. Also considered is the tremendous amount of uncertainty present in the climate emission scenarios and how this uncertainty propagates through the hydrologic simulations. This paper concludes with a discussion of the lessons learned and potential for future work.

Development of a simulation environment to support intercalibration studies over the Algodones Dunes system

NASA Astrophysics Data System (ADS)

Eon, Rehman S.; Gerace, Aaron D.; Montanaro, Matthew; Ambeau, Brittany L.; McCorkel, Joel T.

2018-01-01

The ability of sensors to detect changes in the Earth's environment is dependent on retrieving radiometrically consistent and calibrated measurements from its surface. Intercalibration provides consistency among satellite instruments and ensures fidelity of scientific information. Intercalibration is especially important for spaceborne satellites without any on-board calibration, as accuracy of instruments is significantly affected by changes that occur postlaunch. To better understand the key parameters that impact the intercalibration process, this paper describes a simulation environment that was developed to support the primary mission of the Algodones Dunes campaign. Specifically, measurements obtained from the campaign were utilized to create a synthetic landscape to assess the feasibility of using the Algodones Dunes system as an intercalibration site for spaceborne instruments. The impact of two key parameters (differing view-angles and temporal offsets between instruments) on the intercalibration process was assessed. Results of these studies indicate that although the accuracy of intercalibration is sensitive to these parameters, proper knowledge of their impact leads to situations that minimize their effect. This paper concludes with a case study that addresses the feasibility of performing intercalibration on the International Space Station's platform to support NASA's CLARREO, the climate absolute radiance and refractivity observatory, mission.

Evaluating climate variables, indexes and thresholds governing Arctic urban sustainability: case study of Russian permafrost regions

NASA Astrophysics Data System (ADS)

Anisimov, O. A.; Kokorev, V.

2013-12-01

Addressing Arctic urban sustainability today forces planners to deal with the complex interplay of multiple factors, including governance and economic development, demography and migration, environmental changes and land use, changes in the ecosystems and their services, and climate change. While the latter can be seen as a factor that exacerbates the existing vulnerabilities to other stressors, changes in temperature, precipitation, snow, river and lake ice, and the hydrological regime also have direct implications for the cities in the North. Climate change leads to reduced demand for heating energy, on one hand, and heightened concerns about the fate of the infrastructure built upon thawing permafrost, on the other. Changes in snowfall are particularly important and have direct implications for the urban economy, as together with heating costs, expenses for snow removal from streets, airport runways, roofs and ventilation corridors underneath buildings erected on pile foundations on permafrost constitute the bulk of the city's maintenance budget. Many cities are located in river valleys and are prone to flooding that leads to enormous economic losses and casualties, including human deaths. The severity of the northern climate has direct implications for demographic changes governed by regional migration and labor flows. Climate could thus be viewed as an inexhaustible public resource that creates opportunities for sustainable urban development. Long-term trends show that climate as a resource is becoming more readily available in the Russian North, notwithstanding the general perception that globally climate change is one of the challenges facing humanity in the 21st century. In this study we explore the sustainability of the Arctic urban environment under changing climatic conditions. We identify key governing variables and indexes and study the thresholds beyond which changes in the governing climatic parameters have significant impact on the economy, infrastructure and society in the Arctic cities. We use CMIP-5 ensemble projection to evaluate future changes in these parameters and identify regions where immediate attention is needed to develop appropriate adaptation strategies. Acknowledgement. This study is supported by the German-Russian Otto Schmidt Laboratory, project OSL-13-02, and the Russian Foundation for Basic Research, projects 13-05-0072 and 13-05-91171.

Improving Assimilated Global Climate Data Using TRMM and SSM/I Rainfall and Moisture Data

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. Work has been underway at NASA's Data Assimilation Office to explore the use of TRMM and SSM/I-derived rainfall and total precipitable water (TPW) data in global data assimilation to directly constrain these hydrological parameters. We found that assimilating these data types improves not only the precipitation and moisture estimates but also key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation in the tropics. We will present results showing that assimilating TRMM and SSM/I 6-hour averaged rain rates and TPW estimates significantly reduces the state-dependent systematic errors in assimilated products. Specifically, rainfall assimilation improves cloud and latent heating distributions, which, in turn, improves the cloudy-sky radiation and the large-scale circulation, while TPW assimilation reduces moisture biases to improve radiation in clear-sky regions. Rainfall and TPW assimilation also improves tropical forecasts beyond 1 day.

Measuring progress of the global sea level observing system

NASA Astrophysics Data System (ADS)

Woodworth, Philip L.; Aarup, Thorkild; Merrifield, Mark; Mitchum, Gary T.; Le Provost, Christian

Sea level is such a fundamental parameter in the sciences of oceanography geophysics, and climate change, that in the mid-1980s, the Intergovernmental Oceanographic Commission (IOC) established the Global Sea Level Observing System (GLOSS). GLOSS was to improve the quantity and quality of data provided to the Permanent Service for Mean Sea Level (PSMSL), and thereby, data for input to studies of long-term sea level change by the Intergovernmental Panel on Climate Change (IPCC). It would also provide the key data needed for international programs, such as the World Ocean Circulation Experiment (WOCE) and later, the Climate Variability and Predictability Programme (CLIVAR).GLOSS is now one of the main observation components of the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM) of IOC and the World Meteorological Organization (WMO). Progress and deficiencies in GLOSS were presented in July to the 22nd IOC Assembly at UNESCO in Paris and are contained in the GLOSS Assessment Report (GAR) [IOC, 2003a].

Anthropogenic climate change and allergen exposure: The role of plant biology.

PubMed

Ziska, Lewis H; Beggs, Paul J

2012-01-01

Accumulation of anthropogenic gases, particularly CO(2), is likely to have 2 fundamental effects on plant biology. The first is an indirect effect through Earth's increasing average surface temperatures, with subsequent effects on other aspects of climate, such as rainfall and extreme weather events. The second is a direct effect caused by CO(2)-induced stimulation of photosynthesis and plant growth. Both effects are likely to alter a number of fundamental aspects of plant biology and human health, including aerobiology and allergic diseases, respectively. This review highlights the current and projected effect of increasing CO(2) and climate change in the context of plants and allergen exposure, emphasizing direct effects on plant physiologic parameters (eg, pollen production) and indirect effects (eg, fungal sporulation) related to diverse biotic and abiotic interactions. Overall, the review assumes that future global mitigation efforts will be limited and suggests a number of key research areas that will assist in adapting to the ongoing challenges to public health associated with increased allergen exposure. Published by Mosby, Inc.

Exploring the Mass Balance and Sea Level Contribution of Global Glaciers During the Last Interglaciation and Mid-Holocene

NASA Astrophysics Data System (ADS)

Smith, S.; Ullman, D. J.; He, F.; Carlson, A. E.; Marzeion, B.; Maussion, F.

2017-12-01

Understanding the behavior of the world's glaciers during previous interglaciations is key to interpreting the sensitivity and behavior of the cryosphere under scenarios of future anthropogenic warming. Previous studies of the Last Interglaciation (LIG, 130 ka to 116 ka) indicate elevated global temperatures and higher sea levels than the Holocene, but most assessments of the impact on the cryosphere have focused on the mass balance and volume change of polar ice sheets. In assessing sea-level sources, most studies assume complete deglacation of global glaciers, but this has yet to be tested. In addition, the significant changes in orbital forcing during the LIG and the associated impacts on climate seasonality and variability may have led to unique glacier evolution.Here, we explore the effect of LIG climate on the global glacier budget. We employ the Open Global Glacier Model (OGGM), forced by simulated LIG equilibrium climate anomalies (127 ka) from the Community Climate System Model Version 3 (CCSM3). OGGM is a glacier mass balance and dynamics model, specifically designed to reconstruct global glacier volume change. Our simulations have been conducted in an equilibrium state to determine the effect of the prolonged climate forcing of the LIG. Due to unknown flow characteristics of glaciers during the LIG, we explore the parametric uncertainty in the mass balance and flow sensitivity parameters. As a point of comparison, we also conduct a series of simulations using forcing anomalies from the CCSM3 mid-Holocene (6 ka) experiment. Results from both experiments show that glacier mass balance is highly sensitive to these sensitivity parameters, pointing at the need for glacier margin calibration for OGGM in paleoclimate applications.

Short ensembles: An Efficient Method for Discerning Climate-relevant Sensitivities in Atmospheric General Circulation Models

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

Wan, Hui; Rasch, Philip J.; Zhang, Kai

2014-09-08

This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivitymore » of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model version 5. The first example demonstrates that the method is capable of characterizing the model cloud and precipitation sensitivity to time step length. A nudging technique is also applied to an additional set of simulations to help understand the contribution of physics-dynamics interaction to the detected time step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol lifecycle are perturbed simultaneously in order to explore which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. Results show that in both examples, short ensembles are able to correctly reproduce the main signals of model sensitivities revealed by traditional long-term climate simulations for fast processes in the climate system. The efficiency of the ensemble method makes it particularly useful for the development of high-resolution, costly and complex climate models.« less

Land-Sea relationships of climate-related records: example of the Holocene in the eastern Canadian Arctic and Greenland

NASA Astrophysics Data System (ADS)

de Vernal, Anne; Fréchette, Bianca; Hillaire-Marcel, Claude

2017-04-01

Anne de Vernal, Bianca Fréchette, Claude Hillaire-Marcel Important progresses have been made to reconstruct climate and ocean changes through time. However, there is often a hiatus between the land-based climate reconstructions and paleoceanographical data. The reconstructed parameters are not the same (e.g. surface air temperature vs. sea-surface temperature). Moreover, the spatial (local to regional) and temporal dimensions (seasonal, annual to multi-decadal) of proxy-data are often inconsistent, thus preventing direct correlation of time series and often leading to uncertainties in multi-site, multi-proxy compilations. Here, we address the issue of land-sea relationships in the eastern Canadian Arctic-Baffin Bay-Labrador Sea-western Greenland based on the examination of different climate-related information from marine cores (dinocysts) collected nearshore vs. offshore, ice cores (isotopes), fjord and lake data (pollen). The combined information tends to indicate that "climate" changes are not easily neither adequately captured by temperature and temperature shifts. However, the seasonal contrast of temperatures seems to be a key parameter. Whereas it is often attenuated offshore, it is generally easy to reconstruct nearshore, where water stratification is usually stronger. The confrontation of data also shows a relationship between ice core data and sea-ice cover and/or sea-surface salinity, suggesting that air-sea exchanges in basins surrounding ice sheets play a significant role with respect to their isotopic composition. On the whole, combined onshore-offshore data consistently suggest a two-step shift towards optimal summer and winter conditions the circum Baffin Bay and northern Labrador Sea at 7.5 and 6 ka BP. These delayed optimal conditions seem to result from ice-meltwater discharges maintaining low salinity conditions in marine surface waters and thus a strong seasonality.

Climate and marine biogeochemistry during the Holocene from transient model simulations

NASA Astrophysics Data System (ADS)

Segschneider, Joachim; Schneider, Birgit; Khon, Vyacheslav

2018-06-01

Climate and marine biogeochemistry changes over the Holocene are investigated based on transient global climate and biogeochemistry model simulations over the last 9500 years. The simulations are forced by accelerated and non-accelerated orbital parameters, respectively, and atmospheric pCO2, CH4, and N2O. The analysis focusses on key climatic parameters of relevance to the marine biogeochemistry, and on the physical and biogeochemical processes that drive atmosphere-ocean carbon fluxes and changes in the oxygen minimum zones (OMZs). The simulated global mean ocean temperature is characterized by a mid-Holocene cooling and a late Holocene warming, a common feature among Holocene climate simulations which, however, contradicts a proxy-derived mid-Holocene climate optimum. As the most significant result, and only in the non-accelerated simulation, we find a substantial increase in volume of the OMZ in the eastern equatorial Pacific (EEP) continuing into the late Holocene. The concurrent increase in apparent oxygen utilization (AOU) and age of the water mass within the EEP OMZ can be attributed to a weakening of the deep northward inflow into the Pacific. This results in a large-scale mid-to-late Holocene increase in AOU in most of the Pacific and hence the source regions of the EEP OMZ waters. The simulated expansion of the EEP OMZ raises the question of whether the deoxygenation that has been observed over the last 5 decades could be a - perhaps accelerated - continuation of an orbitally driven decline in oxygen. Changes in global mean biological production and export of detritus remain of the order of 10 %, with generally lower values in the mid-Holocene. The simulated atmosphere-ocean CO2 flux would result in atmospheric pCO2 changes of similar magnitudes to those observed for the Holocene, but with different timing. More technically, as the increase in EEP OMZ volume can only be simulated with the non-accelerated model simulation, non-accelerated model simulations are required for an analysis of the marine biogeochemistry in the Holocene. Notably, the long control experiment also displays similar magnitude variability to the transient experiment for some parameters. This indicates that also long control runs are required when investigating Holocene climate and marine biogeochemistry, and that some of the Holocene variations could be attributed to internal variability of the atmosphere-ocean system.

Spatial trends in Pearson Type III statistical parameters

USGS Publications Warehouse

Lichty, R.W.; Karlinger, M.R.

1995-01-01

Spatial trends in the statistical parameters (mean, standard deviation, and skewness coefficient) of a Pearson Type III distribution of the logarithms of annual flood peaks for small rural basins (less than 90 km2) are delineated using a climate factor CT, (T=2-, 25-, and 100-yr recurrence intervals), which quantifies the effects of long-term climatic data (rainfall and pan evaporation) on observed T-yr floods. Maps showing trends in average parameter values demonstrate the geographically varying influence of climate on the magnitude of Pearson Type III statistical parameters. The spatial trends in variability of the parameter values characterize the sensitivity of statistical parameters to the interaction of basin-runoff characteristics (hydrology) and climate. -from Authors

Carpathian mountain forest vegetation and its responses to climate stressors

NASA Astrophysics Data System (ADS)

Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.; Dida, Adrian I.

2017-10-01

Due to anthropogenic and climatic changes, Carpathian Mountains forests in Romania experience environmental degradation. As a result of global climate change, there is growing evidence that some of the most severe weather events could become more frequent in Romania over the next 50 to 100 years. In the case of Carpathian mountain forests, winter storms and heat waves are considered key climate risks, particularly in prealpine and alpine areas. Effects of climate extremes on forests can have both short-term and long-term implications for standing biomass, tree health and species composition. The preservation and enhancement of mountain forest vegetation cover in natural, semi-natural forestry ecosystems is an essential factor in sustaining environmental health and averting natural hazards. This paper aims to: (i) describe observed trends and scenarios for summer heat waves, windstorms and heavy precipitation, based on results from satellite time series NOAA AVHRR, MODIS Terra/Aqua and Landsat TM/ETM+/OLI NDVI and LAI data recorded during 2000-2016 period correlated with meteorological parameters, regional climate models, and other downscaling procedures, and (ii) discuss potential impacts of climate changes and extreme events on Carpathian mountain forest system in Romania. The response of forest land cover vegetation in Carpathian Mountains, Romania to climatic factors varies in different seasons of the years, the diverse vegetation feedbacks to climate changes being related to different vegetation characteristics and meteorological conditions. Based on integrated analysis of satellite and field data was concluded that forest ecosystem functions are responsible of the relationships between mountain specific vegetation and climate.

Using Local Climate Science to Educate "Key Influentials" and their Communities in the San Diego Region

NASA Astrophysics Data System (ADS)

Boudrias, M. A.; Estrada, M.; Anders, S.; Silva-Send, N. J.; Yin, Z.; Schultz, P.; Young, E.

2012-12-01

The San Diego Regional Climate Education Partnership has formed an innovative and collaborative team whose mission is to implement a research-based climate science education and communications program to increase knowledge about climate science among highly-influential leaders and their communities and foster informed decision making based on climate science and impacts. The team includes climate scientists, behavioral psychologists, formal and informal educators and communication specialists. The Partnership's strategic plan has three major goals: (1) raise public understanding of the causes and consequences of climate change; (2) identify the most effective educational methods to educate non-traditional audiences (Key Influentials) about the causes and consequences of climate change; and (3) develop and implement a replicable model for regional climate change education. To implement this strategic plan, we have anchored our project on three major pillars: (1) Local climate science (causes, impacts and long-term consequences); (2) theoretical, research-based evaluation framework (TIMSI); and (3) Key! Influentials (KI) as primary audience for messages (working w! ith and through them). During CCEP-I, the Partnership formed and convened an advisory board of Key Influentials, completed interviews with a sample of Key Influentials, conducted a public opinion survey, developed a website (www.sandiego.edu/climate) , compiled inventories on literature of climate science education resources and climate change community groups and local activities, hosted stakeholder forums, and completed the first phase of on an experiment to test the effects of different messengers delivering the same local climate change message via video. Results of 38 KI Interviews provided evidence of local climate knowledge, strong concern about climate change, and deeply held values related to climate change education and regional leadership. The most intriguing result was that while 90% of Key Influentials described themselves as concerned about climate change, they believed only 10% of their peers were equally concerned. Results from a public opinion survey of 1001 San Diego residents exhibited two clear trends: San Diegans were consistently more attuned and concerned about climate change and its impacts than nationwide average; and similar to the KI findings, they do not believe others are as concerned as they are. Further, mediation analysis of results supported TIMSI, showing that climate change education that promotes efficacy, identity and values endorsed by a concerned community are most likely to result in engagement in mitigation and adaptive behaviors. All CCEP-I activities informed and directed the design of our Phase II Strategic plan and will provide baseline data for assessing changes that occur as we implement the educational plan. Implementation strategies for the next Phase will emphasize (1) presenting local climate science and unique climate impacts, (2) working with Key Influentials in diverse ways, including educational both formal and informal dialogues for this non-traditional audience, developing climate education messages to be delivered by KIs to their peers and their communities, and engaging certain KIs to be the portal to their constituents; and (3) using social media to connect educators and their audiences.

ENSO activity during the last climate cycle using Individual Foraminifera Analysis

NASA Astrophysics Data System (ADS)

Leduc, G.; Vidal, L.; Thirumalai, K.

2017-12-01

The El Niño / Southern Oscillation (ENSO) is the principal mode of interannual climate variability and affects key climate parameters such as low-latitude rainfall variability. Recent climate modeling experiments tend to suggest an increase in the frequency of both El Niño and La Niña events in the future, but these results remain model-dependent and require to be validated by paleodata-model comparisons. Fossil corals indicate that the ENSO variance during the 20th century is particularly high as compared to other time periods of the Holocene. Beyond the Holocene, however, little is known on past ENSO changes, which makes difficult to test paleoclimate model simulations that are used to study the ENSO sensitivity to various types of forcings. We have expanded an Individual Foraminifera Analysis (IFA) dataset using the thermocline-dwelling N. dutertrei on a marine core collected in the Panama Basin (Leduc et al., 2009), that has proven to be a skillful way to reconstruct the ENSO (Thirumalai et al., 2013). Our new IFA dataset comprehensively covers the Holocene, allowing to verify how the IFA method compares with ENSO reconstructions using corals. The dataset then extends back in time to Marine Isotope Stage 6 (MIS), with a special focus the last deglaciation and Termination II (MIS5/6) time windows, as well as key time periods to tests the sensitivity of ENSO to ice volume and orbital parameters. The new dataset confirms variable ENSO activity during the Holocene and weaker activity during LGM than during the Holocene, as a recent isotope-enabled climate model simulations of the LGM suggests (Zhu et al., 2017). Such pattern is reproduced for the Termination II. Leduc, G., L. Vidal, O. Cartapanis, and E. Bard (2009), Modes of eastern equatorial Pacific thermocline variability: Implications for ENSO dynamics over the last glacial period, Paleoceanography, 24, PA3202, doi:10.1029/2008PA001701. Thirumalai, K., J. W. Partin, C. S. Jackson, and T. M. Quinn (2013), Statistical constraints on El Niño Southern Oscillation reconstructions using individual foraminifera: A sensitivity analysis, Paleoceanography, 28, 401-412, doi:10.1002/palo.20037. Zhu, J., et al. (2017), Reduced ENSO variability at the LGM revealed by an isotope-enabled Earth system model, Geophys. Res. Lett., 44, 6984-6992, doi:10.1002/2017GL073406.

Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments.

PubMed

Tao, Fulu; Rötter, Reimund P; Palosuo, Taru; Gregorio Hernández Díaz-Ambrona, Carlos; Mínguez, M Inés; Semenov, Mikhail A; Kersebaum, Kurt Christian; Nendel, Claas; Specka, Xenia; Hoffmann, Holger; Ewert, Frank; Dambreville, Anaelle; Martre, Pierre; Rodríguez, Lucía; Ruiz-Ramos, Margarita; Gaiser, Thomas; Höhn, Jukka G; Salo, Tapio; Ferrise, Roberto; Bindi, Marco; Cammarano, Davide; Schulman, Alan H

2018-03-01

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was -4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981-2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources. © 2017 John Wiley & Sons Ltd.

ESA's Earth Observation Programmes in the Changing Anthropocene

NASA Astrophysics Data System (ADS)

Liebig, Volker

2016-07-01

The intervention will present ESA's Earth Observation programmes and their relevance to studying the anthropocene. ESA's Earth observation missions are mainly grouped into three categories: The Sentinel satellites in the context of the European Copernicus Programme, the scientific Earth Explorers and the meteorological missions. Developments, applications and scientific results for the different mission types will be addressed, along with overall trends and strategies. The Earth Explorers, who form the science and research element of ESA's Living Planet Programme, focus on the atmosphere, biosphere, hydrosphere, cryosphere and Earth's interior. The Earth Explorers also aim at learning more about the interactions between these components and the impact that human activity is having on natural Earth processes. The Sentinel missions provide accurate, timely, long term and uninterrupted data to provide key information services, improving the way the environment is managed, and helping to mitigate the effects of climate change. The operational Sentinel satellites can also be exploited for scientific studies of the anthropocene. In the anthropocene human activities affect the whole planet and space is a very efficient means to measure their impact, but for relevant endeavours to be successful they can only be carried out in international cooperation. ESA maintains long-standing partnerships with other space agencies and institutions worldwide. In running its Earth observation programmes, ESA responds to societal needs and challenges and to requirements resulting from political priorities set by decision makers. Activities related to Climate Change are a prime example. Within ESA's Climate Change Initiative, 13 Essential Climate Variables are constantly monitored to create a long-term record of key geophysical parameters.

Executive summary: Climate change in the northwest: Implications for our landscapes, waters, and communities

USGS Publications Warehouse

Dalton, Meghan M.; Bethel, Jeffrey; Capalbo, Susan M.; Cuhaciyan, J.E.; Eigenbrode, Sanford D.; Glick, Patty; Houston, Laurie L.; Littell, Jeremy S.; Lynn, Kathy; Mote, Philip W.; Raymondi, Rick R.; Reeder, W. Spencer; Shafer, Sarah L.; Snover, Amy K.

2013-01-01

Climate Change in the Northwest: Implications for Our Landscapes, Waters, and Communities is aimed at assessing the state of knowledge about key climate impacts and consequences to various sectors and communities in the northwest United States. It draws on a wealth of peer-reviewed literature, earlier state-level assessment reports conducted for Washington (2009) and Oregon (2010), as well as a risk-framing workshop. As an assessment, it aims to be representative (though not exhaustive) of the key climate change issues as reflected in the growing body of Northwest climate change science, impacts, and adaptation literature now available. This report will serve as an updated resource for scientists, stakeholders, decision makers, students, and community members interested in understanding and preparing for climate change impacts on Oregon, Washington, and Idaho. This more detailed, foundational report is intended to support the key findings presented in the Northwest chapter of the Third National Climate Assessment.

The HOAPS Climatology V4: updates and results from comparisons to various satellite, buoy and ship data records

NASA Astrophysics Data System (ADS)

Schroeder, Marc; Graw, Kathrin; Andersson, Axel; Fennig, Karsten; Bakan, Stephan; Klepp, Christian

2017-04-01

The global water cycle is a key component of the global climate system as it describes and links many important processes such as evaporation, convection, cloud formation and precipitation. Through latent heat release, it is also closely connected to the global energy cycle and its changes. The difference between precipitation and evaporation yields the freshwater flux, which indicates if a particular region of the earth receives more water through precipitation than it loses through evaporation or vice versa. On global scale and long time periods, however, the amounts of evaporation and precipitation are balanced. A profound understanding of the water cycle is therefore a key prerequisite for successful climate modelling. The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) set is a fully satellite based climatology of precipitation, evaporation and freshwater budget as well as related turbulent heat fluxes and atmospheric state variables over the global ice free oceans. All geophysical parameters are derived from passive microwave radiometers, except for the SST, which is taken from AVHRR measurements based on thermal emission of the Earth. Starting with the release 3.1, the HOAPS climate data record is hosted by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) and the further development is shared with the University of Hamburg and the MPI-M. While the HOAPS release 3.2 in 2012 covered the entire record of the passive microwave radiometer SSM/I, the new version of the HOAPS data set, version 4, includes also the SSMIS record up to December 2014 and uncertainty estimates for parameters related to evaporation. These HOAPS data products are available as monthly averages and 6-hourly composites on a regular latitude/longitude grid with a spatial resolution of 0.5° x 0.5° from July 1987 to December 2014 (December 2008 for HOAPS3.2). Covering nearly 28 years the new HOAPS data set is highly valuable for climate applications. The data can be retrieved from the CM SAF web user interface http://wui.cmsaf.eu and from http://www.hoaps.org. The presentation will cover details of the HOAPS-4 release, recent enhancements as well as future plans for the further development of the HOAPS data set. E.g., for the integrated water vapour and the near surface wind speed product, a new 1D-Var based retrieval was developed. We show the differences between the statistical retrievals used in HOAPS-3.2 compared to the new HOAPS-4 products, results from comparisons to various satellite-based data records and results from comparisons to buoy and ship observations. A specific focus is on the assessment of the stability and uncertainties.

Parameter Estimations of Dynamic Energy Budget (DEB) Model over the Life History of a Key Antarctic Species: The Antarctic Sea Star Odontaster validus Koehler, 1906.

PubMed

Agüera, Antonio; Collard, Marie; Jossart, Quentin; Moreau, Camille; Danis, Bruno

2015-01-01

Marine organisms in Antarctica are adapted to an extreme ecosystem including extremely stable temperatures and strong seasonality due to changes in day length. It is now largely accepted that Southern Ocean organisms are particularly vulnerable to global warming with some regions already being challenged by a rapid increase of temperature. Climate change affects both the physical and biotic components of marine ecosystems and will have an impact on the distribution and population dynamics of Antarctic marine organisms. To predict and assess the effect of climate change on marine ecosystems a more comprehensive knowledge of the life history and physiology of key species is urgently needed. In this study we estimate the Dynamic Energy Budget (DEB) model parameters for key benthic Antarctic species the sea star Odontaster validus using available information from literature and experiments. The DEB theory is unique in capturing the metabolic processes of an organism through its entire life cycle as a function of temperature and food availability. The DEB model allows for the inclusion of the different life history stages, and thus, becomes a tool that can be used to model lifetime feeding, growth, reproduction, and their responses to changes in biotic and abiotic conditions. The DEB model presented here includes the estimation of reproduction handling rules for the development of simultaneous oocyte cohorts within the gonad. Additionally it links the DEB model reserves to the pyloric caeca an organ whose function has long been ascribed to energy storage. Model parameters described a slowed down metabolism of long living animals that mature slowly. O. validus has a large reserve that-matching low maintenance costs- allow withstanding long periods of starvation. Gonad development is continuous and individual cohorts developed within the gonads grow in biomass following a power function of the age of the cohort. The DEB model developed here for O. validus allowed us to increase our knowledge on the ecophysiology of this species, providing new insights on the role of food availability and temperature on its life cycle and reproduction strategy.

ClimateImpactsOnline: A web platform for regional climate impacts

NASA Astrophysics Data System (ADS)

Nocke, Thomas

2013-04-01

Climate change is widely known but there is often uncertainty about the specific effects. One of the key tasks is - beyond discussing climate change and its impacts in specialist groups - to present these to a wider audience. In that respect, decision-makers in the public sector as well as directly affected professional groups require to obtain easy-to-understand information. These groups are not made up of specialist scientists. This gives rise to two challenges: (1) the complex information must be presented such that it is commonly understood, and (2) access to the information must be easy. Interested parties do not have time to familiarize themselves over a lengthy period, but rather want to immediately work with the information. Beside providing climate information globally, regional information become of increasing interest for local decision making regarding awareness building and adaptation options. In addition, current web portals mainly focus on climate information, considering climate impacts on different sectors only implicitly. As solution, Potsdam Institute for Climate Impact Research and WetterOnline have jointly developed an Internet portal that is easy to use, groups together interesting information about climate impacts and offers it in a directly usable form. This new web portal ClimateImpactsOnline.com provides detailed information, combining multiple sectors for the test case of Germany. For this region, numerous individual studies on climate change have been prepared by various institutions. These studies differ in terms of their aim, region and time period of interest. Thus, the goal of ClimateImpactsOnline.com is to present a synthesized view on regional impacts of global climate change on hydrology, agriculture, forest, energy, tourism and health sector. The climate and impact variables are available on a decadal time resolution for the period from 1901-2100, combining observed data and future projections. Detailed information are presented threefold: (1) color maps of absolute and difference values to consider parameter variations, (2) textual tables for individual decades including uncertainties (bandwidth), and (3) time series graphs visualizing the temporal parameter development. Tables and time series graphs are available for administrative units at three aggregation levels (nation, federal state, district). We executed a larger test study with German public institutions and are currently improving functionalities due to appr. 50 user feedbacks. In the talk/poster, we present the scientific basics, graphical user interface in combination with the visual representations and the feedback from the public sector institutions and portal users.

Climatic impact on isovolumetric weathering of a coarse-grained schist in the northern Piedmont Province of the central Atlantic states

USGS Publications Warehouse

Cleaves, E.T.

1993-01-01

The possible impact of periglacial climates on the rate of chemical weathering of a coarse-grained plagioclase-muscovite-quartz schist has been determined for a small watershed near Baltimore, Maryland. The isovolumetric chemical weathering model formulated from the geochemical mass balance study of the watershed shows that the weathering front advances at a velocity of 9.1 m/m.y., if the modern environmental parameters remain the same back through time. However, recent surficial geological mapping demonstrates that periglacial climates have impacted the area. Such an impact significantly affects two key chemical weathering parameters, the concentration of CO2 in the soil and groundwater moving past the weathering front. Depending upon the assumptions used in the model, the rate of saprolitization varies from 2.2 to 5.3 m/m.y. The possible impact of periglacial processes suggested by the chemical weathering rates indicates a need to reconsider theories of landscape evolution as they apply to the northern Piedmont Province of the mid-Atlantic states. I suggest that from the Late Miocene to the present that the major rivers have become incised in their present locations; this incision has enhanced groundwater circulation and chemical weathering such that crystalline rocks beneath interfluvial areas remain mantled by saprolite; and the saprolite mantle has been partially stripped as periglacial conditions alternate with humid-temperate conditions. ?? 1993.

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

NASA Astrophysics Data System (ADS)

Sarofim, M. C.; Martinich, J.; Waldhoff, S.; DeAngelo, B. J.; McFarland, J.; Jantarasami, L.; Shouse, K.; Crimmins, A.; Li, J.

2014-12-01

The Climate Change Impacts and Risk Analysis (CIRA) project establishes a new multi-model framework to systematically assess the physical impacts, economic damages, and risks from climate change. The primary goal of this framework is to estimate the degree to which climate change impacts and damages in the United States are avoided or reduced in the 21st century under multiple greenhouse gas (GHG) emissions mitigation scenarios. The first phase of the CIRA project is a modeling exercise that included two integrated assessment models and 15 sectoral models encompassing five broad impacts sectors: water resources, electric power, infrastructure, human health, and ecosystems. Three consistent socioeconomic and climate scenarios are used to analyze the benefits of global GHG mitigation targets: a reference scenario and two policy scenarios with total radiative forcing targets in 2100 of 4.5 W/m2 and 3.7 W/m2. In this exercise, the implications of key uncertainties are explored, including climate sensitivity, climate model, natural variability, and model structures and parameters. This presentation describes the motivations and goals of the CIRA project; the design and academic contribution of the first CIRA modeling exercise; and briefly summarizes several papers published in a special issue of Climatic Change. The results across impact sectors show that GHG mitigation provides benefits to the United States that increase over time, the effects of climate change can be strongly influenced by near-term policy choices, adaptation can reduce net damages, and impacts exhibit spatial and temporal patterns that may inform mitigation and adaptation policy discussions.

Climate Change Literacy across the Critical Zone Observatory Network

NASA Astrophysics Data System (ADS)

Moore, A.; Derry, L. A.; Zabel, I.; Duggan-Haas, D.; Ross, R. M.

2017-12-01

Earth's Critical Zone extends from the top of the tree canopy to the base of the groundwater lens. Thus the Critical Zone is examined as a suite of interconnected systems and study of the CZ is inherently interdisciplinary. Climate change is an important driver of CZ processes. The US Critical Zone Observatory Network comprises nine observatories and a coordinating National Office. Educational programs and materials developed at each CZO and the National Office have been collected, reviewed, and presented on-line at the CZONO (criticalzone.org/national/education-outreach/resources). Because the CZOs are designed to observe and measure a suite of common parameters on varying geological substrates and within different ecological contexts, educational resources reflect the diversity of processes represented across the network. As climate change has a network-wide impact, the fundamental building blocks of climate change literacy are key elements in many activities within the CZONO resource collection. Carbon-cycle and hydrologic cycle processes are well-represented, with emphasis on human interactions with these resources, as well as the impact of extreme events and the changing climate. Current work on the resource collection focuses on connecting individual resources to "Teach Climate Science" project and the Teacher-Friendly Guide to Climate Change (teachclimatescience.wordpress.com). The Teacher-Friendly Guide is a manual for K-12 teachers that presents both the fundamentals of climate science alongside resources for effective teaching of this controversial topic. Using the reach of the CZO network we hope to disseminate effective climate literacy resources and support to the K-12 community.

Solving the Global Climate Monitoring Problem in the Atmosphere: Towards SI-tied Climate Records with Integrated Uncertainty Propagation

NASA Astrophysics Data System (ADS)

Kirchengast, G.; Schwaerz, M.; Fritzer, J.; Schwarz, J.; Scherllin-Pirscher, B.; Steiner, A. K.

2013-12-01

Monitoring the atmosphere to gain accurate and long-term stable records of essential climate variables (ECVs) such as temperature and greenhouse gases is the backbone of contemporary atmospheric and climate science. Earth observation from space is the key to obtain such data globally in the atmosphere. Currently, however, not any existing satellite-based atmospheric ECV record can serve as authoritative benchmark over months to decades so that climate variability and change in the atmosphere are not yet reliably monitored. Radio occultation (RO) using Global Navigation Satellite System (GNSS) signals provides a unique opportunity to solve this problem in the free atmosphere (from ~1-2 km altitude upwards) for core ECVs: the thermodynamic variables temperature and pressure, and to some degree water vapor, which are key parameters for tracking climate change. On top of RO we have recently conceived next-generation methods, microwave and infrared-laser occultation and nadir-looking infrared-laser reflectometry. These can monitor a full set of thermo-dynamic ECVs (incl. wind) as well as the greenhouse gases such as carbon dioxide and methane as main drivers of climate change; for the latter we also target the boundary layer for tracking carbon sources and sinks. We briefly introduce to why the atmospheric climate monitoring challenge is unsolved so far and why just the above methods have the capabilities to break through. We then focus on RO, which already provided more than a decade of observations. RO accurately measures time delays from refraction of GNSS signals during atmospheric occultation events. This enables to tie RO-derived ECVs and their uncertainty to fundamental time standards, effectively the SI second, and to their unique long-term stability and narrow uncertainty. However, despite impressive advances since the pioneering RO mission GPS/Met in the mid-1990ties no rigorous trace from fundamental time to the ECVs (duly accounting also for relevant side influences) exists so far. Establishing such a trace first-time in form of the Reference Occultation Processing System rOPS, providing reference RO data for climate science and applications, is therefore a current cornerstone endeavor at the Wegener Center over 2011 to 2015, supported also by colleagues from other key groups at EUMETSAT Darmstadt, UCAR Boulder, DMI Copenhagen, ECMWF Reading, IAP Moscow, AIUB Berne, and RMIT Melbourne. With the rOPS we undertake to process the full chain from the SI-tied raw data to the atmospheric ECVs with integrated uncertainty propagation. We summarize where we currently stand in quantifying RO accuracy and long-term stability and then discuss the concept, development status and initial results from the rOPS, with emphasis on its novel capability to provide SI-tied reference data with integrated uncertainty estimation. We comment how these data can provide ground-breaking support to challenges such as climate model evaluation, anthropogenic change detection and attribution, and calibration of complementary climate observing systems.

Refractory periods and climate forcing in cholera dynamics.

PubMed

Koelle, Katia; Rodó, Xavier; Pascual, Mercedes; Yunus, Md; Mostafa, Golam

2005-08-04

Outbreaks of many infectious diseases, including cholera, malaria and dengue, vary over characteristic periods longer than 1 year. Evidence that climate variability drives these interannual cycles has been highly controversial, chiefly because it is difficult to isolate the contribution of environmental forcing while taking into account nonlinear epidemiological dynamics generated by mechanisms such as host immunity. Here we show that a critical interplay of environmental forcing, specifically climate variability, and temporary immunity explains the interannual disease cycles present in a four-decade cholera time series from Matlab, Bangladesh. We reconstruct the transmission rate, the key epidemiological parameter affected by extrinsic forcing, over time for the predominant strain (El Tor) with a nonlinear population model that permits a contributing effect of intrinsic immunity. Transmission shows clear interannual variability with a strong correspondence to climate patterns at long periods (over 7 years, for monsoon rains and Brahmaputra river discharge) and at shorter periods (under 7 years, for flood extent in Bangladesh, sea surface temperatures in the Bay of Bengal and the El Niño-Southern Oscillation). The importance of the interplay between extrinsic and intrinsic factors in determining disease dynamics is illustrated during refractory periods, when population susceptibility levels are low as the result of immunity and the size of cholera outbreaks only weakly reflects climate forcing.

Evaluation Of The MODIS-VIIRS Land Surface Reflectance Fundamental Climate Data Record.

NASA Astrophysics Data System (ADS)

Roger, J. C.; Vermote, E.; Skakun, S.; Murphy, E.; Holben, B. N.; Justice, C. O.

2016-12-01

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and has been recognized as a key parameter in the understanding of the land-surface-climate processes. Here, we present the validation of the Land surface reflectance used for MODIS and VIIRS data. This methodology uses the 6SV Code and data from the AERONET network. The first part was to define a protocol to use the AERONET data. To correctly take into account the aerosol model, we used the aerosol microphysical properties provided by the AERONET network including size-distribution (%Cf, %Cc, rf, rc, σr, σc), complex refractive indices and sphericity. Over the 670 available AERONET sites, we selected 230 sites with sufficient data. To be useful for validation, the aerosol model should be readily available anytime, which is rarely the case. We then used regressions for each microphysical parameter using the aerosol optical thickness at 440nm and the Angström coefficient as parameters. Comparisons with the AERONET dataset give good APU (Accuracy-Precision-Uncertainties) for each parameter. The second part of the study relies on the theoretical land surface retrieval. We generated TOA synthetic data using aerosol models from AERONET and determined APU on the surface reflectance retrieval while applying the MODIS and VIRRS Atmospheric correction software. Over 250 AERONET sites, the global uncertainties are for MODIS band 1 (red) is always lower than 0.0015 (when surface reflectance is > 0.04). This very good result shows the validity of our reference. Then, we used this reference for validating the MODIS and VIIRS surface reflectance products. The overall accuracy clearly reaches specifications. Finally, we will present an error budget of the surface reflectance retrieval. Indeed, to better understand how to improve the methodology, we defined an exhaustive error budget. We included all inputs i.e. sensor, calibration, aerosol properties, atmospheric conditions… This latter work provides a lot of information, such as the aerosol optical thickness obviously drives the uncertainties of the retrieval, the absorption and the volume concentration of the fine aerosol mode have an important impact as well…

An Assessment of the Subseasonal Predictability of Severe Thunderstorm Environments and Activity using the Climate Forecast System Version 2

NASA Astrophysics Data System (ADS)

Stepanek, Adam J.

The prospect for skillful long-term predictions of atmospheric conditions known to directly contribute to the onset and maintenance of severe convective storms remains unclear. A thorough assessment of the capability for a global climate model such as the Climate Forecast System Version 2 (CFSv2) to skillfully represent parameters related to severe weather has the potential to significantly improve medium- to long-range outlooks vital to risk managers. Environmental convective available potential energy (CAPE) and deep-layer vertical wind shear (DLS) can be used to distinguish an atmosphere conducive to severe storms from one supportive of primarily non-severe 'ordinary' convection. As such, this research concentrates on the predictability of CAPE, DLS, and a product of the two parameters (CAPEDLS) by the CFSv2 with a specific focus on the subseasonal timescale. Individual month-long verification periods from the Climate Forecast System reanalysis (CFSR) dataset are measured against a climatological standard using cumulative distribution function (CDF) and area-under-the-CDF (AUCDF) techniques designed mitigate inherent model biases while concurrently assessing the entire distribution of a given parameter in lieu of a threshold-based approach. Similar methods imposed upon the CFS reforecast (CFSRef) and operational CFSv2 allow for comparisons elucidating both spatial and temporal trends in skill using correlation coefficients, proportion correct metrics, Heidke skill score (HSS), and root-mean-square-error (RMSE) statistics. Key results show the CFSv2-based output often demonstrates skill beyond a climatologically-based threshold when the forecast is notably anomalous from the 29-year (1982-2010) mean CFSRef prediction (exceeding one standard deviation at grid point level). CFSRef analysis indicates enhanced skill during the months of April and June (relative to May) and for predictions of DLS. Furthermore, years exhibiting skill in terms of RMSE are shown to possess certain correlations with El Nino-Southern Oscillation conditions from the preceding winter and concurrent Madden Julian Oscillation activity. Applying results gleaned from the CFSRef analysis to the operational CFSv2 (2011-16) indicates predictive skill can be increased by isolating forecasts meeting multiple parameter-based relationships.

The response of arid soil communities to climate change: Chapter 8

USGS Publications Warehouse

Steven, Blaire; McHugh, Theresa Ann; Reed, Sasha C.

2017-01-01

Arid and semiarid ecosystems cover approximately 40% of Earth’s terrestrial surface and are present on each of the planet’s continents [1]. Drylands are characterized by their aridity, but there is substantial geographic, edaphic, and climatic variability among these vast ecosystems, and these differences underscore substantial variation in dryland soil microbial communities, as well as in the future climates predicted among arid and semiarid systems globally. Furthermore, arid ecosystems are commonly patchy at a variety of spatial scales [2,3]. Vascular plants are widely interspersed in drylands and bare soil, or soil that is covered with biological soil crusts, fill these spaces. The variability acts to further enhance spatial heterogeneity, as these different zones within dryland ecosystems differ in characteristics such as water retention, albedo, and nutrient cycling [4–6]. Importantly, the various soil patches of an arid landscape may be differentially sensitive to climate change. Soil communities are only active when enough moisture is available, and drylands show large spatial variability in soil moisture, with potentially long dry periods followed by pulses of moisture. The pulse dynamics associated with this wetting and drying affect the composition, structure, and function of dryland soil communities, and integrate biotic and abiotic processes via pulse-driven exchanges, interactions, transitions, and transfers. Climate change will likely alter the size, frequency, and intensity of future precipitation pulses, as well as influence non-rainfall sources of soil moisture, and aridland ecosystems are known to be highly sensitive to such climate variability. Despite great heterogeneity, arid ecosystems are united by a key parameter: a limitation in water availability. This characteristic may help to uncover unifying aspects of dryland soil responses to global change. The dryness of an ecosystem can be described by its aridity index (AI). Several AIs have been proposed, but the most widely used metrics determine the difference between average precipitation and potential evapotranspiration, where evapotranspiration is the sum of evaporation and plant transpiration, both of which move water from the ecosystem to the atmosphere [7–9]. Because evapotranspiration can be affected by various environmental factors such as temperature and incident radiation (Fig. 10.1), regions that receive the same average precipitation may have significantly different AI values [10,11]. Multiple studies have documented that mean annual precipitation, and thus AI, is highly correlated with biological diversity and net primary productivity [12–15]. Accordingly, AI is considered to be a central regulator of the diversity, structure, and productivity of an ecosystem, playing an especially influential role in arid ecosystems. Thus, the climate parameters that drive alterations in the AI of a region are likely to play an disproportionate role in shaping the response of arid soil communities to a changing climate. In this chapter we consider climate parameters that have been shown to be altered through climate change, with a focus on how these parameters are likely to affect dryland soil communities, including microorganisms and invertebrates. In particular, our goal is to highlight dryland soil community structure and function in the context of climate change, and we will focus on community relationships with increased atmospheric CO2 concentrations (a primary driver of climate change), temperature, and sources of soil moisture.

Creating a Partnering Community Aimed to Foster Climate Literacy in the Southeastern United States

NASA Astrophysics Data System (ADS)

Rutherford, D.; McNeal, K. S.; Smith, R.; Hare, D.; Nair, U. S.

2011-12-01

The Climate Literacy Partnership in the Southeast (CLiPSE) is a part of the Climate Change Education Program supported by the National Science Foundation (http://CLiPSE-project.org). The established CLiPSE partnership is dedicated to improving climate literacy in the southeast through crafting a shared vision and strategic plan among stakeholders that promotes scientific formal and informal educational resources, materials and programs; a diverse network of key partnering organizations throughout the Southeastern United States (SE US); and effective public dialogues that address diverse learners and audiences and supports learning of climate, climate change, and its relevance upon human and environmental systems. The CLiPSE project has been successful in creating partnerships with more than fifty key stakeholders that stem from a few key publics such as agriculture, education, leisure, religious organizations, and culturally diverse communities. These key publics in the SE US frequently consist of individuals that place great trust in local, private efforts, and CLiPSE has realized the importance of the role of the partnering organizations in providing information through a trusted source. A second unique characteristic of the SE US is the predominately conservative and Protestant citizenry in the region. Working with and through these communities enhances climate change education outreach to this citizenry. The CLiPSE project rests on solid climate science and learning science research in order to formulate an effective plan with desired learning outcomes of critical thinking and civil conversation through effective communication strategies. This paper will present the CLiPSE model in reaching the key publics that traditionally hold ideologies that are traditionally perceived as incompatible with climate change science. We will present the strategies utilized to bring together experts and researchers in climate science, learning science, and social science with practitioners and leaders of key stakeholder groups to formulate a shared climate change education plan in the SE US that is uniquely formatted for each target audience. We will also share what we have learned from interacting with the leaders of our partnering organizations in crafting effective messages for their audiences and addressing learners' affective and cognitive domains.

Ungulate reproductive parameters track satellite observations of plant phenology across latitude and climatological regimes

USGS Publications Warehouse

Stoner, David; Sexton, Joseph O.; Nagol, Jyoteshwar; Bernales, Heather H.; Edwards, Thomas C.

2016-01-01

The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primary productivity. Interannual variation in weather influences the quality and timing of forage availability, which can influence neonatal survival. Here, we evaluated macro-scale patterns in reproductive performance of a widely distributed ungulate (mule deer, Odocoileus hemionus) across contrasting climatological regimes using satellite-derived indices of primary productivity and plant phenology over eight degrees of latitude (890 km) in the American Southwest. The dataset comprised > 180,000 animal observations taken from 54 populations over eight years (2004–2011). Regionally, both the start and peak of growing season (“Start” and “Peak”, respectively) are negatively and significantly correlated with latitude, an unusual pattern stemming from a change in the dominance of spring snowmelt in the north to the influence of the North American Monsoon in the south. Corresponding to the timing and variation in both the Start and Peak, mule deer reproduction was latest, lowest, and most variable at lower latitudes where plant phenology is timed to the onset of monsoonal moisture. Parturition dates closely tracked the growing season across space, lagging behind the Start and preceding the Peak by 27 and 23 days, respectively. Mean juvenile production increased, and variation decreased, with increasing latitude. Temporally, juvenile production was best predicted by primary productivity during summer, which encompassed late pregnancy, parturition, and early lactation. Our findings offer a parsimonious explanation of two key reproductive parameters in ungulate demography, timing of parturition and mean annual production, across latitude and changing climatological regimes. Practically, this demonstrates the potential for broad-scale modeling of couplings between climate, plant phenology, and animal populations using space-borne observations.

Assessing Soil Organic C Stability at the Continental Scale: An Analysis of Soil C and Radiocarbon Profiles Across the NEON Sites

NASA Astrophysics Data System (ADS)

Heckman, K. A.; Gallo, A.; Hatten, J. A.; Swanston, C.; McKnight, D. M.; Strahm, B. D.; Sanclements, M.

2017-12-01

Soil carbon stocks have become recognized as increasingly important in the context of climate change and global C cycle modeling. As modelers seek to identify key parameters affecting the size and stability of belowground C stocks, attention has been drawn to the mineral matrix and the soil physiochemical factors influenced by it. Though clay content has often been utilized as a convenient and key explanatory variable for soil C dynamics, its utility has recently come under scrutiny as new paradigms of soil organic matter stabilization have been developed. We utilized soil cores from a range of National Ecological Observatory Network (NEON) experimental plots to examine the influence of physicochemical parameters on soil C stocks and turnover, and their relative importance in comparison to climatic variables. Soils were cored at NEON sites, sampled by genetic horizon, and density separated into light fractions (particulate organics neither occluded within aggregates nor associated with mineral surfaces), occluded fractions (particulate organics occluded within aggregates), and heavy fractions (organics associated with mineral surfaces). Bulk soils and density fractions were measured for % C and radiocarbon abundance (as a measure of C stability). Carbon and radiocarbon abundances were examined among fractions and in the context of climatic variables (temperature, precipitation, elevation) and soil physiochemical variables (% clay and pH). No direct relationships between temperature and soil C or radiocarbon abundances were found. As a whole, soil radiocarbon abundance in density fractions decreased in the order of light>heavy>occluded, highlighting the importance of both surface sorption and aggregation to the preservation of organics. Radiocarbon abundance was correlated with pH, with variance also grouping by dominate vegetation type. Soil order was also identified as an important proxy variable for C and radiocarbon abundance. Preliminary results suggest that both integrative proxies as well as physicochemical properties may be needed to account for variation in soil C abundance and stability at the continental scale.

Ungulate Reproductive Parameters Track Satellite Observations of Plant Phenology across Latitude and Climatological Regimes

PubMed Central

Stoner, David C.; Sexton, Joseph O.; Nagol, Jyoteshwar; Bernales, Heather H.; Edwards, Thomas C.

2016-01-01

The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primary productivity. Interannual variation in weather influences the quality and timing of forage availability, which can influence neonatal survival. Here, we evaluated macro-scale patterns in reproductive performance of a widely distributed ungulate (mule deer, Odocoileus hemionus) across contrasting climatological regimes using satellite-derived indices of primary productivity and plant phenology over eight degrees of latitude (890 km) in the American Southwest. The dataset comprised > 180,000 animal observations taken from 54 populations over eight years (2004–2011). Regionally, both the start and peak of growing season (“Start” and “Peak”, respectively) are negatively and significantly correlated with latitude, an unusual pattern stemming from a change in the dominance of spring snowmelt in the north to the influence of the North American Monsoon in the south. Corresponding to the timing and variation in both the Start and Peak, mule deer reproduction was latest, lowest, and most variable at lower latitudes where plant phenology is timed to the onset of monsoonal moisture. Parturition dates closely tracked the growing season across space, lagging behind the Start and preceding the Peak by 27 and 23 days, respectively. Mean juvenile production increased, and variation decreased, with increasing latitude. Temporally, juvenile production was best predicted by primary productivity during summer, which encompassed late pregnancy, parturition, and early lactation. Our findings offer a parsimonious explanation of two key reproductive parameters in ungulate demography, timing of parturition and mean annual production, across latitude and changing climatological regimes. Practically, this demonstrates the potential for broad-scale modeling of couplings between climate, plant phenology, and animal populations using space-borne observations. PMID:26849642

Ungulate Reproductive Parameters Track Satellite Observations of Plant Phenology across Latitude and Climatological Regimes.

PubMed

Stoner, David C; Sexton, Joseph O; Nagol, Jyoteshwar; Bernales, Heather H; Edwards, Thomas C

2016-01-01

The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primary productivity. Interannual variation in weather influences the quality and timing of forage availability, which can influence neonatal survival. Here, we evaluated macro-scale patterns in reproductive performance of a widely distributed ungulate (mule deer, Odocoileus hemionus) across contrasting climatological regimes using satellite-derived indices of primary productivity and plant phenology over eight degrees of latitude (890 km) in the American Southwest. The dataset comprised > 180,000 animal observations taken from 54 populations over eight years (2004-2011). Regionally, both the start and peak of growing season ("Start" and "Peak", respectively) are negatively and significantly correlated with latitude, an unusual pattern stemming from a change in the dominance of spring snowmelt in the north to the influence of the North American Monsoon in the south. Corresponding to the timing and variation in both the Start and Peak, mule deer reproduction was latest, lowest, and most variable at lower latitudes where plant phenology is timed to the onset of monsoonal moisture. Parturition dates closely tracked the growing season across space, lagging behind the Start and preceding the Peak by 27 and 23 days, respectively. Mean juvenile production increased, and variation decreased, with increasing latitude. Temporally, juvenile production was best predicted by primary productivity during summer, which encompassed late pregnancy, parturition, and early lactation. Our findings offer a parsimonious explanation of two key reproductive parameters in ungulate demography, timing of parturition and mean annual production, across latitude and changing climatological regimes. Practically, this demonstrates the potential for broad-scale modeling of couplings between climate, plant phenology, and animal populations using space-borne observations.

Application of advanced data assimilation techniques to the study of cloud and precipitation feedbacks in the tropical climate system

NASA Astrophysics Data System (ADS)

Posselt, Derek J.

The research documented in this study centers around two topics: evaluation of the response of precipitating cloud systems to changes in the tropical climate system, and assimilation of cloud and precipitation information from remote-sensing platforms. The motivation for this work proceeds from the following outstanding problems: (1) Use of models to study the response of clouds to perturbations in the climate system is hampered by uncertainties in cloud microphysical parameterizations. (2) Though there is an ever-growing set of available observations, cloud and precipitation assimilation remains a difficult problem, particularly in the tropics. (3) Though it is widely acknowledged that cloud and precipitation processes play a key role in regulating the Earth's response to surface warming, the response of the tropical hydrologic cycle to climate perturbations remains largely unknown. The above issues are addressed in the following manner. First, Markov chain Monte Carlo (MCMC) methods are used to quantify the sensitivity of the NASA Goddard Cumulus Ensemble (GCE) cloud resolving model (CRM) to changes in its cloud odcrnpbymiC8l parameters. TRMM retrievals of precipitation rate, cloud properties, and radiative fluxes and heating rates over the South China Sea are then assimilated into the GCE model to constrain cloud microphysical parameters to values characteristic of convection in the tropics, and the resulting observation-constrained model is used to assess the response of the tropical hydrologic cycle to surface warming. The major findings of this study are the following: (1) MCMC provides an effective tool with which to evaluate both model parameterizations and the assumption of Gaussian statistics used in optimal estimation procedures. (2) Statistics of the tropical radiation budget and hydrologic cycle can be used to effectively constrain CRM cloud microphysical parameters. (3) For 2D CRM simulations run with and without shear, the precipitation efficiency of cloud systems increases with increasing sea surface temperature, while the high cloud fraction and outgoing shortwave radiation decrease.

Nile Basin Vegetation Response and Vulnerability to Climate Change: A Multi-Sensor Remote Sensing Approach

NASA Astrophysics Data System (ADS)

Yitayew, M.; Didan, K.; Barreto-munoz, A.

2013-12-01

The Nile Basin is one of the world's water resources hotspot that is home to over 437 million people in ten riparian countries with 54% or 238 millions live directly within the basin. The basin like all other basins of the world is facing water resources challenges exacerbated by climate change and increased demand. Nowadays any water resource management action in the basin has to assess the impacts of climate change to be able to predict future water supply and also to help in the negotiation process. Presently, there is a lack of basin wide weather networks to understand sensitivity of the vegetation cover to the impacts of climate change. Vegetation plays major economic and ecological functions in the basin and provides key services ranging from pastoralism, agricultural production, firewood, habitat and food sources for the rich wildlife, as well as a major role in the carbon cycle and climate regulation of the region. Under the threat of climate change and the incessant anthropogenic pressure the distribution and services of the region's ecosystems are projected to change The goal of this work is to assess and characterize how the basin vegetation productivity, distribution, and phenology have changed over the last 30+ years and what are the key climatic drivers of this change. This work makes use of a newly generated multi-sensor long-term land surface data set about vegetation and phenology. Vegetation indices derived from remotely sensed surface reflectance data are commonly used to characterize phenology or vegetation dynamics accurately and with enough spatial and temporal resolution to support change detection. We used more than 30 years of vegetation index and growing season data from AVHRR and MODIS sensors compiled by the Vegetation Index and Phenology laboratory (VIP LAB) at the University of Arizona. Available climate data about precipitation and temperature for the corresponding 30 years period is also used for this analysis. We looked at the changes in the vegetation index signal and to a lesser degree the change in land cover and land use over the last 30 years. Using the climate data record we looked at the drivers of this change. The sensitivity of the basin to climate change was assessed using the multi-linear regression analysis on the covariance of the change in key phenology parameters and the two climate drivers considered here. The overall response was very complex owing to the complicated climate regime and topography of the region. Vegetation response was mostly stable in high lands with a slightly decreasing trend over low and mid-elevations. Over the same period we also observed an intensification of agriculture production corresponding to an increase in percent cover and productivity. We also observed a decrease in forest cover associated with land use conversion. These changes were mostly driven by the precipitation regimes with little impact of the temperature. Climate models project an eventual decrease in precipitation and increase in temperature over the basin. Coupled with these results and observations these projected changes point to major challenges to the vegetation cover, productivity, and associated ecosystem services of the Nile basin.

Satellite Sounder-Based OLR-, Cloud- and Atmospheric Temperature Climatologies for Climate Analyses

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel

2006-01-01

Global energy balance of the Earth-atmosphere system may change due to natural and man-made climate variations. For example, changes in the outgoing longwave radiation (OLR) can be regarded as a crucial indicator of climate variations. Clouds play an important role -still insufficiently assessed in the global energy balance on all spatial and temporal scales, and satellites provide an ideal platform to measure cloud and large-scale atmospheric variables simultaneously. The TOVS series of satellites were the first to provide this type of information since 1979. OLR [Mehta and Susskind], cloud cover and cloud top pressure [Susskind et al] are among the key climatic parameters computed by the TOVS Pathfinder Path-A algorithm using mainly the retrieved temperature and moisture profiles. AIRS, regarded as the new and improved TOVS , has a much higher spectral resolution and greater S/N ratio, retrieving climatic parameters with higher accuracy. First we present encouraging agreements between MODIS and AIRS cloud top pressure (C(sub tp) and effective (A(sub eff), a product of infrared emissivity at 11 microns and physical cloud cover or A(sub c)) cloud fraction seasonal and interannual variabilities for selected months. Next we present validation efforts and preliminary trend analyses of TOVS-retrieved C(sub tp) and A(sub eff). For example, decadal global trends of the TOVS Path-A and ISCCP-D2 P(sub c), and A(sub eff)/A(sub c), values are similar. Furthermore, the TOVS Path-A and ISCCP-AVHRR [available since 19831 cloud fractions correlate even more strongly, including regional trends. We also present TOVS and AIRS OLR validation effort results and (for the longer-term TOVS Pathfinder Path-A dataset) trend analyses. OLR interannual spatial variabilities from the available state-of-the-art CERES measurements and both from the AIRS [Susskind et al] and TOVS OLR computations are in remarkably good agreement. Global monthly mean CERES and TOVS OLR time series show very good agreement in absolute values also. Finally, we will assess correlations among long-term trends of selected parameters, derived simultaneously from the TOVS Pathfinder Path-A datase

First global WCRP shortwave surface radiation budget dataset

NASA Technical Reports Server (NTRS)

Whitlock, C. H.; Charlock, T. P.; Staylor, W. F.; Pinker, R. T.; Laszlo, I.; Ohmura, A.; Gilgen, H.; Konzelman, T.; Dipasquale, R. C.; Moats, C. D.

1995-01-01

Shortwave radiative fluxes that reach the earth's surface are key factors that influence atmospheric and oceanic circulations as well as surface climate. Yet, information on these fluxes is meager. Surface site data are generally available from only a limited number of observing stations over land. Much less is known about the large-scale variability of the shortwave radiative fluxes over the oceans, which cover most of the globe. Recognizing the need to produce global-scale fields of such fluxes for use in climate research, the World Climate Research Program has initiated activities that led to the establishment of the Surface Radiation Budget Climatology Project with the ultimate goal to determine various components of the surface radiation budget from satellite data. In this paper, the first global products that resulted from this activity are described. Monthly and daily data on a 280-km grid scale are available. Samples of climate parameters obtainable from the dataset are presented. Emphasis is given to validation and limitations of the results. For most of the globe, satellite estimates have bias values between +/- 20 W/sq m and root mean square (rms) values are around 25 W/sq m. There are specific regions with much larger uncertainties however.

First global WCRP shortwave surface radiation budget dataset

NASA Technical Reports Server (NTRS)

Whitlock, C. H.; Charlock, T. P.; Staylor, W. F.; Pinker, R. T.; Laszlo, I.; Ohmura, A.; Gilgen, H.; Konzelman, T.; DiPasquale, R. C.; Moats, C. D.

1995-01-01

Shortwave radiative fluxes that reach the Earth's surface are key factors that influence atmospheric and oceanic circulations as well as surface climate. Yet, information on these fluxes is meager. Surface site data are generally available from only a limited number of observing stations over land. Much less is known about the large-scale variability of the shortwave radiative fluxes over the oceans, which cover most of the globe. Recognizing the need to produce global-scale fields of such fluxes for use in climate research, the World Climate Research Program has initiated activities that led to the establishment of the Surface Radiation Budget Climatology Project with the ultimate goal to determine various components of the surface radiation budget from satellite data. In this paper, the first global products that resulted from this activity are described. Monthly and daily data on a 280-km grid scale are available. Samples of climate parameters obtainable from the dataset are presented. Emphasis is given to validation and limitations of the results. For most of the globe, satellite estimates have bias values between +/- 20 W/sq m and rms values are around 25 W/sq m. There are specific regions with much larger uncertainties however.

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

Hong, Tao; Niu, Zhenbin; Hu, Xunxiang

The development of high performance materials for CO 2 separation and capture will significantly contribute to a solution for climate change. In this work, (bicycloheptenyl) ethyl terminated polydimethylsiloxane (PDMSPNB) membranes with varied cross-link densities were synthesized via ring-opening metathesis polymerization. The developed polymer membranes show higher permeability and better selectivity than those of conventional cross-linked PDMS membrane. The achieved performance (CO 2 permeability ~ 6800 Barrer and CO 2/N 2 selectivity ~ 14) is very promising for practical applications. The key to achieving this high performance is the use of an in-situ cross-linking method of the difunctional PDMS macromonomers, whichmore » provides lightly cross-linked membranes. By combining positron annihilation lifetime spectroscopy, broadband dielectric spectroscopy and gas solubility measurements, we have elucidated the key parameters necessary for achieving their excellent performance.« less

ENSO activity during the last climate cycle using IFA

NASA Astrophysics Data System (ADS)

Leduc, Guillaume; Vidal, Laurence; Thirumalai, Kaustubh

2017-04-01

The El Niño / Southern Oscillation (ENSO) is the principal mode of interannual climate variability and affects key climate parameters such as low-latitude rainfall variability. Anticipating future ENSO variability under anthropogenic forcing is vital due to its profound socioeconomic impact. Fossil corals suggest that 20th century ENSO variance is particularly high as compared to other time periods of the Holocene (Cobb et al., 2013, Science), the Last Glacial Maximum (Ford et al., 2015, Science) and the last glacial period (Tudhope et al., 2001, Science). Yet, recent climate modeling experiments suggest an increase in the frequency of both El Niño (Cai et al., 2014, Nature Climate Change) and La Niña (Cai et al., 2015, Nature Climate Change) events. We have expanded an Individual Foraminifera Analysis (IFA) dataset using the thermocline-dwelling N. dutertrei on a marine core collected in the Panama Basin (Leduc et al., 2009, Paleoceanography), that has proven to be a skillful way to reconstruct the ENSO (Thirumalai et al., 2013, Paleoceanography). Our new IFA dataset comprehensively covers the Holocene, the last deglaciation and Termination II (MIS5/6) time windows. We will also use previously published data from the Marine Isotope Stage 3 (MIS3). Our dataset confirms variable ENSO intensity during the Holocene and weaker activity during LGM than during the Holocene. As a next step, ENSO activity will be discussed with respect to the contrasting climatic background of the analysed time windows (millenial-scale variability, Terminations).

Air Pollution and Climate Change Effects on Allergies in the Anthropocene: Abundance, Interaction, and Modification of Allergens and Adjuvants.

PubMed

Reinmuth-Selzle, Kathrin; Kampf, Christopher J; Lucas, Kurt; Lang-Yona, Naama; Fröhlich-Nowoisky, Janine; Shiraiwa, Manabu; Lakey, Pascale S J; Lai, Senchao; Liu, Fobang; Kunert, Anna T; Ziegler, Kira; Shen, Fangxia; Sgarbanti, Rossella; Weber, Bettina; Bellinghausen, Iris; Saloga, Joachim; Weller, Michael G; Duschl, Albert; Schuppan, Detlef; Pöschl, Ulrich

2017-04-18

Air pollution and climate change are potential drivers for the increasing burden of allergic diseases. The molecular mechanisms by which air pollutants and climate parameters may influence allergic diseases, however, are complex and elusive. This article provides an overview of physical, chemical and biological interactions between air pollution, climate change, allergens, adjuvants and the immune system, addressing how these interactions may promote the development of allergies. We reviewed and synthesized key findings from atmospheric, climate, and biomedical research. The current state of knowledge, open questions, and future research perspectives are outlined and discussed. The Anthropocene, as the present era of globally pervasive anthropogenic influence on planet Earth and, thus, on the human environment, is characterized by a strong increase of carbon dioxide, ozone, nitrogen oxides, and combustion- or traffic-related particulate matter in the atmosphere. These environmental factors can enhance the abundance and induce chemical modifications of allergens, increase oxidative stress in the human body, and skew the immune system toward allergic reactions. In particular, air pollutants can act as adjuvants and alter the immunogenicity of allergenic proteins, while climate change affects the atmospheric abundance and human exposure to bioaerosols and aeroallergens. To fully understand and effectively mitigate the adverse effects of air pollution and climate change on allergic diseases, several challenges remain to be resolved. Among these are the identification and quantification of immunochemical reaction pathways involving allergens and adjuvants under relevant environmental and physiological conditions.

Climate in the absence of ocean heat transport

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2017-12-01

The energy transported by the oceans to mid- and high latitudes is small compared to the atmosphere, yet exerts an outsized influence on climate. A key reason is the strong interaction between ocean heat transport (OHT) and sea ice extent. I quantify the absolute climatic impact of OHT using the state-of-the-art CESM simulations by comparing a realistic control climate against a slab ocean simulation in which OHT is disabled. The absence of OHT leads to a massive expansion of sea ice into the subtropics in both hemispheres, and a 24 K global cooling. Analysis of the transient simulation after setting the OHT to zero reveals a global cooling process fueled by a runaway sea ice albedo feedback. This process is eventually self-limiting in the cold climate due to a combination of subtropical cloud feedbacks and surface wind effects that are both connected to a massive spin-up of the atmospheric Hadley circulation. A parameter sensitivity study shows that the simulated climate is far more sensitive to small changes in ice surface albedo in the absence of OHT. I conclude that the oceans are responsible for an enormous global warming by mitigating an otherwise very potent sea ice albedo feedback, but that the magnitude of this effect is rather uncertain. These simulations provide a graphic illustration of how the intimate coupling between sea ice and ocean circulation governs the present-day climate, and by extension, highlight the importance of modeling ocean - sea ice interaction with high fidelity.

Air Pollution and Climate Change Effects on Allergies in the Anthropocene: Abundance, Interaction, and Modification of Allergens and Adjuvants

PubMed Central

2017-01-01

Air pollution and climate change are potential drivers for the increasing burden of allergic diseases. The molecular mechanisms by which air pollutants and climate parameters may influence allergic diseases, however, are complex and elusive. This article provides an overview of physical, chemical and biological interactions between air pollution, climate change, allergens, adjuvants and the immune system, addressing how these interactions may promote the development of allergies. We reviewed and synthesized key findings from atmospheric, climate, and biomedical research. The current state of knowledge, open questions, and future research perspectives are outlined and discussed. The Anthropocene, as the present era of globally pervasive anthropogenic influence on planet Earth and, thus, on the human environment, is characterized by a strong increase of carbon dioxide, ozone, nitrogen oxides, and combustion- or traffic-related particulate matter in the atmosphere. These environmental factors can enhance the abundance and induce chemical modifications of allergens, increase oxidative stress in the human body, and skew the immune system toward allergic reactions. In particular, air pollutants can act as adjuvants and alter the immunogenicity of allergenic proteins, while climate change affects the atmospheric abundance and human exposure to bioaerosols and aeroallergens. To fully understand and effectively mitigate the adverse effects of air pollution and climate change on allergic diseases, several challenges remain to be resolved. Among these are the identification and quantification of immunochemical reaction pathways involving allergens and adjuvants under relevant environmental and physiological conditions. PMID:28326768

Automated parameter tuning applied to sea ice in a global climate model

NASA Astrophysics Data System (ADS)

Roach, Lettie A.; Tett, Simon F. B.; Mineter, Michael J.; Yamazaki, Kuniko; Rae, Cameron D.

2018-01-01

This study investigates the hypothesis that a significant portion of spread in climate model projections of sea ice is due to poorly-constrained model parameters. New automated methods for optimization are applied to historical sea ice in a global coupled climate model (HadCM3) in order to calculate the combination of parameters required to reduce the difference between simulation and observations to within the range of model noise. The optimized parameters result in a simulated sea-ice time series which is more consistent with Arctic observations throughout the satellite record (1980-present), particularly in the September minimum, than the standard configuration of HadCM3. Divergence from observed Antarctic trends and mean regional sea ice distribution reflects broader structural uncertainty in the climate model. We also find that the optimized parameters do not cause adverse effects on the model climatology. This simple approach provides evidence for the contribution of parameter uncertainty to spread in sea ice extent trends and could be customized to investigate uncertainties in other climate variables.

Uncertainty, Sensitivity Analysis, and Causal Identification in the Arctic using a Perturbed Parameter Ensemble of the HiLAT Climate Model

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

Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark

Coupled climate models have a large number of input parameters that can affect output uncertainty. We conducted a sensitivity analysis of sea ice proper:es and Arc:c related climate variables to 5 parameters in the HiLAT climate model: air-ocean turbulent exchange parameter (C), conversion of water vapor to clouds (cldfrc_rhminl) and of ice crystals to snow (micro_mg_dcs), snow thermal conduc:vity (ksno), and maximum snow grain size (rsnw_mlt). We used an elementary effect (EE) approach to rank their importance for output uncertainty. EE is an extension of one-at-a-time sensitivity analyses, but it is more efficient in sampling multi-dimensional parameter spaces. We lookedmore » for emerging relationships among climate variables across the model ensemble, and used causal discovery algorithms to establish potential pathways for those relationships.« less

Utilizing the social media data to validate 'climate change' indices

NASA Astrophysics Data System (ADS)

Molodtsova, T.; Kirilenko, A.; Stepchenkova, S.

2013-12-01

Reporting the observed and modeled changes in climate to public requires the measures understandable by the general audience. E.g., the NASA GISS Common Sense Climate Index (Hansen et al., 1998) reports the change in climate based on six practically observable parameters such as the air temperature exceeding the norm by one standard deviation. The utility of the constructed indices for reporting climate change depends, however, on an assumption that the selected parameters are felt and connected with the changing climate by a non-expert, which needs to be validated. Dynamic discussion of climate change issues in social media may provide data for this validation. We connected the intensity of public discussion of climate change in social networks with regional weather variations for the territory of the USA. We collected the entire 2012 population of Twitter microblogging activity on climate change topic, accumulating over 1.8 million separate records (tweets) globally. We identified the geographic location of the tweets and associated the daily and weekly intensity of twitting with the following parameters of weather for these locations: temperature anomalies, 'hot' temperature anomalies, 'cold' temperature anomalies, heavy rain/snow events. To account for non-weather related events we included the articles on climate change from the 'prestige press', a collection of major newspapers. We found that the regional changes in parameters of weather significantly affect the number of tweets published on climate change. This effect, however, is short-lived and varies throughout the country. We found that in different locations different weather parameters had the most significant effect on climate change microblogging activity. Overall 'hot' temperature anomalies had significant influence on climate change twitting intensity.

Impact of the time scale of model sensitivity response on coupled model parameter estimation

NASA Astrophysics Data System (ADS)

Liu, Chang; Zhang, Shaoqing; Li, Shan; Liu, Zhengyu

2017-11-01

That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.

Framework for a U.S. Geological Survey Hydrologic Climate-Response Program in Maine

USGS Publications Warehouse

Hodgkins, Glenn A.; Lent, Robert M.; Dudley, Robert W.; Schalk, Charles W.

2009-01-01

This report presents a framework for a U.S. Geological Survey (USGS) hydrologic climate-response program designed to provide early warning of changes in the seasonal water cycle of Maine. Climate-related hydrologic changes on Maine's rivers and lakes in the winter and spring during the last century are well documented, and several river and lake variables have been shown to be sensitive to air-temperature changes. Monitoring of relevant hydrologic data would provide important baseline information against which future climate change can be measured. The framework of the hydrologic climate-response program presented here consists of four major parts: (1) identifying homogeneous climate-response regions; (2) identifying hydrologic components and key variables of those components that would be included in a hydrologic climate-response data network - as an example, streamflow has been identified as a primary component, with a key variable of streamflow being winter-spring streamflow timing; the data network would be created by maintaining existing USGS data-collection stations and establishing new ones to fill data gaps; (3) regularly updating historical trends of hydrologic data network variables; and (4) establishing basins for process-based studies. Components proposed for inclusion in the hydrologic climate-response data network have at least one key variable for which substantial historical data are available. The proposed components are streamflow, lake ice, river ice, snowpack, and groundwater. The proposed key variables of each component have extensive historical data at multiple sites and are expected to be responsive to climate change in the next few decades. These variables are also important for human water use and (or) ecosystem function. Maine would be divided into seven climate-response regions that follow major river-basin boundaries (basins subdivided to hydrologic units with 8-digit codes or larger) and have relatively homogeneous climates. Key hydrologic variables within each climate-response region would be analyzed regularly to maintain up-to-date analyses of year-to-year variability, decadal variability, and longer term trends. Finally, one basin in each climate-response region would be identified for process-based hydrologic and ecological studies.

Association of parameter, software, and hardware variation with large-scale behavior across 57,000 climate models

PubMed Central

Knight, Christopher G.; Knight, Sylvia H. E.; Massey, Neil; Aina, Tolu; Christensen, Carl; Frame, Dave J.; Kettleborough, Jamie A.; Martin, Andrew; Pascoe, Stephen; Sanderson, Ben; Stainforth, David A.; Allen, Myles R.

2007-01-01

In complex spatial models, as used to predict the climate response to greenhouse gas emissions, parameter variation within plausible bounds has major effects on model behavior of interest. Here, we present an unprecedentedly large ensemble of >57,000 climate model runs in which 10 parameters, initial conditions, hardware, and software used to run the model all have been varied. We relate information about the model runs to large-scale model behavior (equilibrium sensitivity of global mean temperature to a doubling of carbon dioxide). We demonstrate that effects of parameter, hardware, and software variation are detectable, complex, and interacting. However, we find most of the effects of parameter variation are caused by a small subset of parameters. Notably, the entrainment coefficient in clouds is associated with 30% of the variation seen in climate sensitivity, although both low and high values can give high climate sensitivity. We demonstrate that the effect of hardware and software is small relative to the effect of parameter variation and, over the wide range of systems tested, may be treated as equivalent to that caused by changes in initial conditions. We discuss the significance of these results in relation to the design and interpretation of climate modeling experiments and large-scale modeling more generally. PMID:17640921

Harmonizing Access to Federal Data - Lessons Learned Through the Climate Data Initiative

NASA Astrophysics Data System (ADS)

Bugbee, K.; Pinheiro Privette, A. C.; Meyer, D. J.; Ramachandran, R.

2016-12-01

The Climate Data Initiative (CDI), launched by the Obama Administration in March of 2014, is an effort to leverage the extensive open Federal data to spur innovation and private-sector entrepreneurship in order to advance awareness of and preparedness for the impacts of climate change (see the White House fact sheet). The project includes an online catalog of climate-related datasets and data products in key areas of climate change risk and vulnerability from across the U.S. federal government through http://Climate.Data.gov. NASA was tasked with the implementation and management of the project and has been working closely with Subject Matter Experts (SMEs) and Data Curators (DCs) from across the Federal Government to identify and catalog federal datasets relevant for assessing climate risks and impacts. These datasets are organized around key themes and are framed by key climate questions. The current themes within CDI include: Arctic, Coastal Flooding, Ecosystem Vulnerability, Energy Infrastructure, Food Resilience, Human Health, Transportation, Tribal Nations and Water. This paper summarizes the main lessons learned from the last 2.5 years of CDI implementation.

Process evaluation of sea salt aerosol concentrations at remote marine locations

NASA Astrophysics Data System (ADS)

Struthers, H.; Ekman, A. M.; Nilsson, E. D.

2011-12-01

Sea salt, an important natural aerosol, is generated by bubbles bursting at the surface of the ocean. Sea salt aerosol contributes significantly to the global aerosol burden and radiative budget and are a significant source of cloud condensation nuclei in remote marine areas (Monahan et al., 1986). Consequently, changes in marine aerosol abundance is expected to impact on climate forcing. Estimates of the atmospheric burden of sea salt aerosol mass derived from chemical transport and global climate models vary greatly both in the global total and the spatial distribution (Texor et al. 2006). This large uncertainty in the sea salt aerosol distribution in turn contributes to the large uncertainty in the current estimates of anthropogenic aerosol climate forcing (IPCC, 2007). To correctly attribute anthropogenic climate change and to veraciously project future climate, natural aerosols including sea salt must be understood and accurately modelled. In addition, the physical processes that determine the sea salt aerosol concentration are susceptible to modification due to climate change (Carslaw et al., 2010) which means there is the potential for feedbacks within the climate/aerosol system. Given the large uncertainties in sea salt aerosol modelling, there is an urgent need to evaluate the process description of sea salt aerosols in global models. An extremely valuable source of data for model evaluation is the long term measurements of PM10 sea salt aerosol mass available from a number of remote marine observation sites around the globe (including the GAW network). Sea salt aerosol concentrations at remote marine locations depend strongly on the surface exchange (emission and deposition) as well as entrainment or detrainment to the free troposphere. This suggests that the key parameters to consider in any analysis include the sea surface water temperature, wind speed, precipitation rate and the atmospheric stability. In this study, the sea salt aerosol observations are analysed to quantify the key sensitivities of the processes connecting the physical drivers of sea salt aerosol to the mass tendency. The analysis employs a semi-empirical model based on the time-tendency of the aerosol mass. This approach of focusing on the time-tendency of the sea salt aerosol concentration provides a framework for the process evaluation of sea salt aerosol concentrations in global models. The same analysis methodology can be applied to output from global models. A process of comparing the sensitivity parameters derived from observations and models will reveal model inadequacies and thus guide model improvements. Carslaw, K. S., Boucher, O., Spracklen, D. V., Mann G. W., Rae, J. G. L, Woodward, S., Kulmala, M. (2010). Atmos. Chem. Phys., 10, 1701-1737 IPCC (2007). Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Solomon, S., D. Monahan, E. C., Spiel, D. E., Davidson, K. L. (1986) Oceanic Whitecaps ed. Monahan E. C. & MacNiochaill, D. Reidel, Norwell, Mass. Texor, C., et al. (2006) Atmos. Chem. Phys., 6, 1777-1813.

Climate Change Indicators in the United States, 2016 ...

EPA Pesticide Factsheets

EPA partners with over 40 data contributors from various government agencies, academic institutions, and other organizations to compile and communicate key indicators related to the causes and effects of climate change, the significance of these changes, and their possible consequences for people, the environment, and society. This is the fourth edition of the Climate Change Indicators in the United States report. To summarize and communicate key indicators related to the causes and effects of climate change.

Mineralogy and Geochemical Evidence of the Late Early Miocene Aridification Intensification in Xining Basin Caused By the Northeastern Tibetan Plateau Uplift

NASA Astrophysics Data System (ADS)

Zhang, C.; Xiao, G.; Wu, H.; Hao, Q.; Guo, Z.

2014-12-01

A typical inland aridification is present in Central Asia, global cooling, the retreat of Para-Tethys Sea and Tibetan Plateau uplift have been thought to be the main driving forces of the climate change in interior Asia during Cenozoic. However, only few terrestrial climate records from the Asian inland were extended to the late Oligocene-early Miocene, it is still unclear the evolution of aridification before the middle Miocene and which of these driving forces plays the key role. Here, a sedimentary, mineralogy and geochemical proxies record of the early Miocene sedimentary sequence (ca. 22.1 to 16.7 Ma) from Xining Basin was present in this paper, which locates in the northeastern side of Tibetan Plateau. Mineralogical and geochemical parameters show obvious two stages climate change. During ~ 22.1-19 Ma (Unit I), the enrichment of I/S (irregular mixed-layers of illite and smectite) content, high values of a*/L* and much stronger chemical weathering degree reveal a warm and humid climate condition. During 19-16.7 Ma (Unit II), the increase of chlorite and dolomite contents, the upward decrease of a*/L* and much weaker chemical weathering than Unit I suggest evidently increased aridity since ca. 19 Ma. Comprehensive comparisons among records from the central western China demonstrate that the aridification since ca. 19 Ma is widespread in northeastern of Tibetan Plateau. The early Miocene episodic uplift of the north and northeastern Tibetan Plateau, especially, the uplift of Laji Shan at ~22 Ma, possibly have played a key role in the aridification of the Xining Basin.

Ocean Heat and Carbon Uptake in Transient Climate Change: Identifying Model Uncertainty

NASA Technical Reports Server (NTRS)

Romanou, Anastasia; Marshall, John

2015-01-01

Global warming on decadal and centennial timescales is mediated and ameliorated by the oceansequestering heat and carbon into its interior. Transient climate change is a function of the efficiency by whichanthropogenic heat and carbon are transported away from the surface into the ocean interior (Hansen et al. 1985).Gregory and Mitchell (1997) and Raper et al. (2002) were the first to identify the importance of the ocean heat uptakeefficiency in transient climate change. Observational estimates (Schwartz 2012) and inferences from coupledatmosphere-ocean general circulation models (AOGCMs; Gregory and Forster 2008; Marotzke et al. 2015), suggest thatocean heat uptake efficiency on decadal timescales lies in the range 0.5-1.5 W/sq m/K and is thus comparable to theclimate feedback parameter (Murphy et al. 2009). Moreover, the ocean not only plays a key role in setting the timing ofwarming but also its regional patterns (Marshall et al. 2014), which is crucial to our understanding of regional climate,carbon and heat uptake, and sea-level change. This short communication is based on a presentation given by A.Romanou at a recent workshop, Oceans Carbon and Heat Uptake: Uncertainties and Metrics, co-hosted by US CLIVARand OCB. As briefly reviewed below, we have incomplete but growing knowledge of how ocean models used in climatechange projections sequester heat and carbon into the interior. To understand and thence reduce errors and biases inthe ocean component of coupled models, as well as elucidate the key mechanisms at work, in the final section we outlinea proposed model intercomparison project named FAFMIP. In FAFMIP, coupled integrations would be carried out withprescribed overrides of wind stress and freshwater and heat fluxes acting at the sea surface.

Identifying traits for genotypic adaptation using crop models.

PubMed

Ramirez-Villegas, Julian; Watson, James; Challinor, Andrew J

2015-06-01

Genotypic adaptation involves the incorporation of novel traits in crop varieties so as to enhance food productivity and stability and is expected to be one of the most important adaptation strategies to future climate change. Simulation modelling can provide the basis for evaluating the biophysical potential of crop traits for genotypic adaptation. This review focuses on the use of models for assessing the potential benefits of genotypic adaptation as a response strategy to projected climate change impacts. Some key crop responses to the environment, as well as the role of models and model ensembles for assessing impacts and adaptation, are first reviewed. Next, the review describes crop-climate models can help focus the development of future-adapted crop germplasm in breeding programmes. While recently published modelling studies have demonstrated the potential of genotypic adaptation strategies and ideotype design, it is argued that, for model-based studies of genotypic adaptation to be used in crop breeding, it is critical that modelled traits are better grounded in genetic and physiological knowledge. To this aim, two main goals need to be pursued in future studies: (i) a better understanding of plant processes that limit productivity under future climate change; and (ii) a coupling between genetic and crop growth models-perhaps at the expense of the number of traits analysed. Importantly, the latter may imply additional complexity (and likely uncertainty) in crop modelling studies. Hence, appropriately constraining processes and parameters in models and a shift from simply quantifying uncertainty to actually quantifying robustness towards modelling choices are two key aspects that need to be included into future crop model-based analyses of genotypic adaptation. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

NASA Astrophysics Data System (ADS)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2013-12-01

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.

Determining the effect of key climate drivers on global hydropower production

NASA Astrophysics Data System (ADS)

Galelli, S.; Ng, J. Y.; Lee, D.; Block, P. J.

2017-12-01

Accounting for about 17% of total global electrical power production, hydropower is arguably the world's main renewable energy source and a key asset to meet Paris climate agreements. A key component of hydropower production is water availability, which depends on both precipitation and multiple drivers of climate variability acting at different spatial and temporal scales. To understand how these drivers impact global hydropower production, we study the relation between four patterns of ocean-atmosphere climate variability (i.e., El Niño Southern Oscillation, Pacific Decadal Oscillation, North Atlantic Oscillation, and Atlantic Multidecadal Oscillation) and monthly time series of electrical power production for over 1,500 hydropower reservoirs—obtained via simulation with a high-fidelity dam model forced with 20th century climate conditions. Notably significant relationships between electrical power productions and climate variability are found in many climate sensitive regions globally, including North and South America, East Asia, West Africa, and Europe. Coupled interactions from multiple, simultaneous climate drivers are also evaluated. Finally, we highlight the importance of using these climate drivers as an additional source of information within reservoir operating rules where the skillful predictability of inflow exists.

Emperor penguins and climate change.

PubMed

Barbraud, C; Weimerskirch, H

2001-05-10

Variations in ocean-atmosphere coupling over time in the Southern Ocean have dominant effects on sea-ice extent and ecosystem structure, but the ultimate consequences of such environmental changes for large marine predators cannot be accurately predicted because of the absence of long-term data series on key demographic parameters. Here, we use the longest time series available on demographic parameters of an Antarctic large predator breeding on fast ice and relying on food resources from the Southern Ocean. We show that over the past 50 years, the population of emperor penguins (Aptenodytes forsteri) in Terre Adélie has declined by 50% because of a decrease in adult survival during the late 1970s. At this time there was a prolonged abnormally warm period with reduced sea-ice extent. Mortality rates increased when warm sea-surface temperatures occurred in the foraging area and when annual sea-ice extent was reduced, and were higher for males than for females. In contrast with survival, emperor penguins hatched fewer eggs when winter sea-ice was extended. These results indicate strong and contrasting effects of large-scale oceanographic processes and sea-ice extent on the demography of emperor penguins, and their potential high susceptibility to climate change.

Quantitative assessment of glacial fluctuations in the level of Lake Lisan, Dead Sea rift

NASA Astrophysics Data System (ADS)

Rohling, Eelco J.

2013-06-01

A quantitative understanding of climatic variations in the Levant during the last glacial cycle is needed to support archaeologists in assessing the drivers behind hominin migrations and cultural developments in this key region at the intersection between Africa and Europe. It will also foster a better understanding of the region's natural variability as context to projections of modern climate change. Detailed documentation of variations in the level of Lake Lisan - the lake that occupied the Dead Sea rift during the last glacial cycle - provides crucial climatic information for this region. Existing reconstructions suggest that Lake Lisan highstands during cold intervals of the last glacial cycle represent relatively humid conditions in the region, but these interpretations have remained predominantly qualitative. Here, I evaluate realistic ranges of the key climatological parameters that controlled lake level, based on the observed timing and amplitudes of lake-level variability. I infer that a mean precipitation rate over the wider catchment area of about 500 mm y-1, as proposed in the literature, would be consistent with observed lake levels if there was a concomitant 15-50% increase in wind speed during cold glacial stadials. This lends quantitative support to previous inferences of a notable increase in the intensity of Mediterranean (winter) storms during glacial periods, which tracked eastward into the Levant. In contrast to highstands during ‘regular’ stadials, lake level dropped during Heinrich Events. I demonstrate that this likely indicates a further intensification of the winds during those times.

Sensitivity studies for a space-based methane lidar mission

NASA Astrophysics Data System (ADS)

Kiemle, C.; Quatrevalet, M.; Ehret, G.; Amediek, A.; Fix, A.; Wirth, M.

2011-10-01

Methane is the third most important greenhouse gas in the atmosphere after water vapour and carbon dioxide. A major handicap to quantify the emissions at the Earth's surface in order to better understand biosphere-atmosphere exchange processes and potential climate feedbacks is the lack of accurate and global observations of methane. Space-based integrated path differential absorption (IPDA) lidar has potential to fill this gap, and a Methane Remote Lidar Mission (MERLIN) on a small satellite in polar orbit was proposed by DLR and CNES in the frame of a German-French climate monitoring initiative. System simulations are used to identify key performance parameters and to find an advantageous instrument configuration, given the environmental, technological, and budget constraints. The sensitivity studies use representative averages of the atmospheric and surface state to estimate the measurement precision, i.e. the random uncertainty due to instrument noise. Key performance parameters for MERLIN are average laser power, telescope size, orbit height, surface reflectance, and detector noise. A modest-size lidar instrument with 0.45 W average laser power and 0.55 m telescope diameter on a 506 km orbit could provide 50-km averaged methane column measurement along the sub-satellite track with a precision of about 1% over vegetation. The use of a methane absorption trough at 1.65 μm improves the near-surface measurement sensitivity and vastly relaxes the wavelength stability requirement that was identified as one of the major technological risks in the pre-phase A studies for A-SCOPE, a space-based IPDA lidar for carbon dioxide at the European Space Agency. Minimal humidity and temperature sensitivity at this wavelength position will enable accurate measurements in tropical wetlands, key regions with largely uncertain methane emissions. In contrast to actual passive remote sensors, measurements in Polar Regions will be possible and biases due to aerosol layers and thin ice clouds will be minimised.

Sensitivity studies for a space-based methane lidar mission

NASA Astrophysics Data System (ADS)

Kiemle, C.; Quatrevalet, M.; Ehret, G.; Amediek, A.; Fix, A.; Wirth, M.

2011-06-01

Methane is the third most important greenhouse gas in the atmosphere after water vapour and carbon dioxide. A major handicap to quantify the emissions at the Earth's surface in order to better understand biosphere-atmosphere exchange processes and potential climate feedbacks is the lack of accurate and global observations of methane. Space-based integrated path differential absorption (IPDA) lidar has potential to fill this gap, and a Methane Remote Lidar Mission (MERLIN) on a small satellite in Polar orbit was proposed by DLR and CNES in the frame of a German-French climate monitoring initiative. System simulations are used to identify key performance parameters and to find an advantageous instrument configuration, given the environmental, technological, and budget constraints. The sensitivity studies use representative averages of the atmospheric and surface state to estimate the measurement precision, i.e. the random uncertainty due to instrument noise. Key performance parameters for MERLIN are average laser power, telescope size, orbit height, surface reflectance, and detector noise. A modest-size lidar instrument with 0.45 W average laser power and 0.55 m telescope diameter on a 506 km orbit could provide 50-km averaged methane column measurement along the sub-satellite track with a precision of about 1 % over vegetation. The use of a methane absorption trough at 1.65 μm improves the near-surface measurement sensitivity and vastly relaxes the wavelength stability requirement that was identified as one of the major technological risks in the pre-phase A studies for A-SCOPE, a space-based IPDA lidar for carbon dioxide at the European Space Agency. Minimal humidity and temperature sensitivity at this wavelength position will enable accurate measurements in tropical wetlands, key regions with largely uncertain methane emissions. In contrast to actual passive remote sensors, measurements in Polar Regions will be possible and biases due to aerosol layers and thin ice clouds will be minimised.

Climate change and Ixodes tick-borne diseases of humans

PubMed Central

Ostfeld, Richard S.; Brunner, Jesse L.

2015-01-01

The evidence that climate warming is changing the distribution of Ixodes ticks and the pathogens they transmit is reviewed and evaluated. The primary approaches are either phenomenological, which typically assume that climate alone limits current and future distributions, or mechanistic, asking which tick-demographic parameters are affected by specific abiotic conditions. Both approaches have promise but are severely limited when applied separately. For instance, phenomenological approaches (e.g. climate envelope models) often select abiotic variables arbitrarily and produce results that can be hard to interpret biologically. On the other hand, although laboratory studies demonstrate strict temperature and humidity thresholds for tick survival, these limits rarely apply to field situations. Similarly, no studies address the influence of abiotic conditions on more than a few life stages, transitions or demographic processes, preventing comprehensive assessments. Nevertheless, despite their divergent approaches, both mechanistic and phenomenological models suggest dramatic range expansions of Ixodes ticks and tick-borne disease as the climate warms. The predicted distributions, however, vary strongly with the models' assumptions, which are rarely tested against reasonable alternatives. These inconsistencies, limited data about key tick-demographic and climatic processes and only limited incorporation of non-climatic processes have weakened the application of this rich area of research to public health policy or actions. We urge further investigation of the influence of climate on vertebrate hosts and tick-borne pathogen dynamics. In addition, testing model assumptions and mechanisms in a range of natural contexts and comparing their relative importance as competing models in a rigorous statistical framework will significantly advance our understanding of how climate change will alter the distribution, dynamics and risk of tick-borne disease. PMID:25688022

The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?

PubMed

Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J

2013-10-28

Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.

Effects of climate change on evapotranspiration over the Okavango Delta water resources

NASA Astrophysics Data System (ADS)

Moses, Oliver; Hambira, Wame L.

2018-06-01

In semi-arid developing countries, most poor people depend on contaminated surface or groundwater resources since they do not have access to safe and centrally supplied water. These water resources are threatened by several factors that include high evapotranspiration rates. In the Okavango Delta region in the north-western Botswana, communities facing insufficient centrally supplied water rely mainly on the surface water resources of the Delta. The Delta loses about 98% of its water through evapotranspiration. However, the 2% remaining water rescues the communities facing insufficient water from the main stream water supply. To understand the effects of climate change on evapotranspiration over the Okavango Delta water resources, this study analysed trends in the main climatic parameters needed as input variables in evapotranspiration models. The Mann Kendall test was used in the analysis. Trend analysis is crucial since it reveals the direction of trends in the climatic parameters, which is helpful in determining the effects of climate change on evapotranspiration. The main climatic parameters required as input variables in evapotranspiration models that were of interest in this study were wind speeds, solar radiation and relative humidity. Very little research has been conducted on these climatic parameters in the Okavango Delta region. The conducted trend analysis was more on wind speeds, which had relatively longer data records than the other two climatic parameters of interest. Generally, statistically significant increasing trends have been found, which suggests that climate change is likely to further increase evapotranspiration over the Okavango Delta water resources.

Solar influences on global change

NASA Technical Reports Server (NTRS)

1994-01-01

Monitoring of the Sun and the Earth has yielded new knowledge essential to this debate. There is now no doubt that the total radiative energy from the Sun that heats the Earth's surface changes over decadal time scales as a consequence of solar activity. Observations indicate as well that changes in ultraviolet radiation and energetic particles from the Sun, also connected with the solar activity, modulate the layer of ozone that protects the biosphere from the solar ultraviolet radiation. This report reassesses solar influences on global change in the light of this new knowledge of solar and atmospheric variability. Moreover, the report considers climate change to be encompassed within the broader concept of global change; thus the biosphere is recognized to be part of a larger, coupled Earth system. Implementing a program to continuously monitor solar irradiance over the next several decades will provide the opportunity to estimate solar influences on global change, assuming continued maintenance of observations of climate and other potential forcing mechanisms. In the lower atmosphere, an increase in solar radiation is expected to cause global warming. In the stratosphere, however, the two effects produce temperature changes of opposite sign. A monitoring program that would augment long term observations of tropospheric parameters with similar observations of stratospheric parameters could separate these diverse climate perturbations and perhaps isolate a greenhouse footprint of climate change. Monitoring global change in the troposphere is a key element of all facets of the United States Global Change Research Program (USGCRP), not just of the study of solar influences on global change. The need for monitoring the stratosphere is also important for global change research in its own right because of the stratospheric ozone layer.

A distributed atmosphere-sea ice-ocean observatory in the central Arctic Ocean: concept and first results

NASA Astrophysics Data System (ADS)

Hoppmann, Mario; Nicolaus, Marcel; Rabe, Benjamin; Wenzhöfer, Frank; Katlein, Christian; Scholz, Daniel; Valcic, Lovro

2017-04-01

To understand the current evolution of the Arctic Ocean towards a less extensive, thinner and younger sea ice cover is one of the biggest challenges in climate research. Especially the lack of simultaneous in-situ observations of sea ice, ocean and atmospheric properties leads to significant knowledge gaps in their complex interactions, and how the associated processes impact the polar marine ecosystem. Here we present a concept for the implementation of a long-term strategy to monitor the most essential climate- and ecosystem parameters in the central Arctic Ocean, year round and synchronously. The basis of this strategy is the development and enhancement of a number of innovative autonomous observational platforms, such as rugged weather stations, ice mass balance buoys, ice-tethered bio-optical buoys and upper ocean profilers. The deployment of those complementing platforms in a distributed network enables the simultaneous collection of physical and biogeochemical in-situ data on basin scales and year round, including the largely undersampled winter periods. A key advantage over other observatory systems is that the data is sent via satellite in near-real time, contributing to numerical weather predictions through the Global Telecommunication System (GTS) and to the International Arctic Buoy Programme (IABP). The first instruments were installed on ice floes in the Eurasian Basin in spring 2015 and 2016, yielding exceptional records of essential climate- and ecosystem-relevant parameters in one of the most inaccessible regions of this planet. Over the next 4 years, and including the observational periods of the Year of Polar Prediction (YOPP, 2017-2019) and the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC, 2020), the distributed observatory will be maintained by deployment of additional instruments in the central Arctic each year, benefitting from international logistical efforts.

Effect of climate variability and change on winter haze over eastern China in recent decades

NASA Astrophysics Data System (ADS)

Liao, Hong; Yang, Yang

2017-04-01

In recent years, eastern China has frequently experienced persistent and severe winter haze pollution episodes with high aerosol concentrations, which have affected half of the 1.3 billion people in China. In this work, the increases in wintertime aerosol concentrations and severe haze events in eastern China over 1985-2015 were quantified by using observed atmospheric visibility from the National Climatic Data Center Global Summary of Day database, observed PM2.5 concentrations from the network of China National Environmental Monitoring Centre (CNEMC), and simulated PM2.5 concentrations from the Goddard Earth-Observing System (GEOS) chemical transport model (GEOS-Chem). Observed winter haze days (defined as days with atmospheric visibility less than 10 km and relative humidity less than 80%) averaged over eastern China (105-122.5°E, 20-45°N) increased from 21 days in 1980 to 42 days in 2014. Observed severe haze days (defined as days with PM2.5 >150 μg m-3) occurred mainly over Northern China. Considering variations in both anthropogenic emissions and meteorological parameters, the GEOS-Chem model simulated an increasing trend in wintertime surface-layer PM2.5 concentrations of 10.5 (±6.2) μg m-3 decade-1 over eastern China in the past decades. Sensitivity studies showed that changes in anthropogenic emissions and in climate contributed 87% and 17% to this increasing trend, respectively. Wintertime severe haze events over eastern China showed large interannual variations, driven by climate variability. Process analyses were performed to identify the key meteorological parameters that determined the interannual variations of wintertime severe haze events.

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

NASA Astrophysics Data System (ADS)

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

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths.

Oceanic influence on seasonal malaria outbreaks over Senegal and Sahel. Predictability using S4CAST model

NASA Astrophysics Data System (ADS)

Diouf, Ibrahima; Deme, Abdoulaye; Rodriguez-Fonseca, Belen; Suárez-Moreno, Roberto; Cisse, Moustapha; Ndione, Jacques-André; Thierno Gaye, Amadou

2014-05-01

Senegal and, in general, West African regions are affected by important outbreaks of diseases with destructive consequences for human population, livestock and country's economy. The vector-borne diseases such as mainly malaria, Rift Valley Fever and dengue are affected by the interanual to decadal variability of climate. Analysis of the spatial and temporal variability of climate parameters and associated oceanic patterns is important in order to assess the climate impact on malaria transmission. In this study, the approach developed to study the malaria-climate link is predefined by the QWeCI project (Quantifying Weather and Climate Impacts on Health in Developing Countries). Preliminary observations and simulations results over Senegal Ferlo region, confirm that the risk of malaria transmission is mainly linked to climate parameters such as rainfall, temperature and relative humidity; and a lag of one to two months between the maximum of malaria and the maximum of climate parameters as rainfall is observed. As climate variables are able to be predicted from oceanic SST variability in remote regions, this study explores seasonal predictability of malaria incidence outbreaks from previous sea surface temperatures conditions in different ocean basins. We have found causal or coincident relationship between El Niño and malaria parameters by coupling LMM UNILIV malaria model and S4CAST statistiscal model with the aim of predicting the malaria parameters with more than 6 months in advance. In particular, El Niño is linked to an important decrease of the number of mosquitoes and the malaria incidence. Results from this research, after assessing the seasonal malaria parameters, are expected to be useful for decision makers to better access to climate forecasts and application on health in the framework of rolling back malaria transmission.

The public's belief in climate change and its human cause are increasing over time.

PubMed

Milfont, Taciano L; Wilson, Marc S; Sibley, Chris G

2017-01-01

Polls examining public opinion on the subject of climate change are now commonplace, and one-off public opinion polls provide a snapshot of citizen's opinions that can inform policy and communication strategies. However, cross-sectional polls do not track opinions over time, thus making it impossible to ascertain whether key climate change beliefs held by the same group of individuals are changing or not. Here we examine the extent to which individual's level of agreement with two key beliefs ("climate change is real" and "climate change is caused by humans") remain stable or increase/decrease over a six-year period in New Zealand using latent growth curve modelling (n = 10,436). Data were drawn from the New Zealand Attitudes and Values Study, a probabilistic national panel study, and indicated that levels of agreement to both beliefs have steadily increased over the 2009-2015 period. Given that climate change beliefs and concerns are key predictors of climate change action, our findings suggest that a combination of targeted endeavors, as well as serendipitous events, may successfully convey the emergency of the issue.

Development of key indicators to quantify the health impacts of climate change on Canadians.

PubMed

Cheng, June J; Berry, Peter

2013-10-01

This study aimed at developing a list of key human health indicators for quantifying the health impacts of climate change in Canada. A literature review was conducted in OVID Medline to identify health morbidity and mortality indicators currently used to quantify climate change impacts. Public health frameworks and other studies of climate change indicators were reviewed to identify criteria with which to evaluate the list of proposed key indicators and a rating scale was developed. Total scores for each indicator were calculated based on the rating scale. A total of 77 health indicators were identified from the literature. After evaluation using the chosen criteria, 8 indicators were identified as the best for use. They include excess daily all-cause mortality due to heat, premature deaths due to air pollution (ozone and particulate matter 2.5), preventable deaths from climate change, disability-adjusted life years lost from climate change, daily all-cause mortality, daily non-accidental mortality, West Nile Disease incidence, and Lyme borreliosis incidence. There is need for further data and research related to health effect quantification in the area of climate change.

Particle size distribution of the stratospheric aerosol from SCIAMACHY limb measurements

NASA Astrophysics Data System (ADS)

Rozanov, Alexei; Malinina, Elizaveta; Bovensmann, Heinrich; Burrows, John

2017-04-01

A crucial role of the stratospheric aerosols for the radiative budget of the Earth's atmosphere and the consequences for the climate change are widely recognized. A reliable knowledge on physical and optical properties of the stratospheric aerosols as well as on their vertical and spatial distributing is a key issue to assure a proper initialization and running conditions for climate models. On a global scale this information can only be gained from space borne measurements. While a series of past, present and future instruments provide extensive date sets of such aerosol characteristics as extinction coefficient or backscattering ratio, information on a size distribution of the stratospheric aerosols is sparse. One of the important sources on vertically and spatially resolved information on the particle size distribution of stratospheric aerosols is provided by space borne measurements of the scattered solar light in limb viewing geometry performed in visible, near-infrared and short-wave infrared spectral ranges. SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) instrument operated on the European satellite Envisat from 2002 to 2102 was capable of providing spectral information needed to retrieve parameters of aerosol particle size distributions. In this presentation we discuss the retrieval method, present first validation results with SAGE II data and analyze first data sets of stratospheric aerosol particle size distribution parameters obtained from SCIAMACHY limb measurements. The research work was performed in the framework of ROMIC (Role of the middle atmosphere in climate) project.

Implications of plant acclimation for future climate-carbon cycle feedbacks

NASA Astrophysics Data System (ADS)

Mercado, Lina; Kattge, Jens; Cox, Peter; Sitch, Stephen; Knorr, Wolfgang; Lloyd, Jon; Huntingford, Chris

2010-05-01

The response of land ecosystems to climate change and associated feedbacks are a key uncertainty in future climate prediction (Friedlingstein et al. 2006). However global models generally do not account for the acclimation of plant physiological processes to increased temperatures. Here we conduct a first global sensitivity study whereby we modify the Joint UK land Environment Simulator (JULES) to account for temperature acclimation of two main photosynthetic parameters, Vcmax and Jmax (Kattge and Knorr 2007) and plant respiration (Atkin and Tjoelker 2003). The model is then applied over the 21st Century within the IMOGEN framework (Huntingford et al. 2004). Model simulations will provide new and improved projections of biogeochemical cycling, forest resilience, and thus more accurate projections of climate-carbon cycle feedbacks and the future evolution of the Earth System. Friedlingstein P, Cox PM, Betts R et al. (2006) Climate-carbon cycle feedback analysis, results from the C4MIP model intercomparison. Journal of Climate, 19, 3337-3353. Kattge J and Knorr W (2007): Temperature acclimation in a biochemical model of photosynthesis: a reanalysis of data from 36 species. Plant, Cell and Environment 30, 1176-1190 Atkin O.K and Tjoelker, M. G. (2003): Thermal acclimation and the dynamic response of plant respiration to temperature. Trends in Plant Science 8 (7), 343-351 Huntingford C, et al. (2004) Using a GCM analogue model to investigate the potential for Amazonian forest dieback. Theoretical and Applied Climatology, 78, 177-185.

Climate in the Absence of Ocean Heat Transport

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2015-12-01

The energy transported by the oceans to mid- and high latitudes is small compared to the atmosphere, yet exerts an outsized influence on the climate. A key reason is the strong interaction between ocean heat transport (OHT) and sea ice extent. I quantify this by comparing a realistic control climate simulation with a slab ocean simulation in which OHT is disabled. Using the state-of-the-art CESM with a realistic present-day continental configuration, I show that the absence of OHT leads to a 23 K global cooling and massive expansion of sea ice to near 30º latitude in both hemisphere. The ice expansion is asymmetric, with greatest extent in the South Pacific and South Indian ocean basins. I discuss implications of this enormous and asymmetric climate change for atmospheric circulation, heat transport, and tropical precipitation. Parameter sensitivity studies show that the simulated climate is far more sensitive to small changes in ice surface albedo in the absence of OHT, with some perturbations sufficient to cause a runaway Snowball Earth glaciation. I conclude that the oceans are responsible for an enormous global warming by mitigating an otherwise very potent sea ice albedo feedback, but that the magnitude of this effect is still rather uncertain. I will also present some ideas on adapting the simple energy balance model to account for the enhanced sensitivity of sea ice to heating from the ocean.

Monitoring population and environmental parameters of invasive mosquito species in Europe

PubMed Central

2014-01-01

To enable a better understanding of the overwhelming alterations in the invasive mosquito species (IMS), methodical insight into the population and environmental factors that govern the IMS and pathogen adaptations are essential. There are numerous ways of estimating mosquito populations, and usually these describe developmental and life-history parameters. The key population parameters that should be considered during the surveillance of invasive mosquito species are: (1) population size and dynamics during the season, (2) longevity, (3) biting behaviour, and (4) dispersal capacity. Knowledge of these parameters coupled with vector competence may help to determine the vectorial capacity of IMS and basic disease reproduction number (R0) to support mosquito borne disease (MBD) risk assessment. Similarly, environmental factors include availability and type of larval breeding containers, climate change, environmental change, human population density, increased human travel and goods transport, changes in living, agricultural and farming habits (e.g. land use), and reduction of resources in the life cycle of mosquitoes by interventions (e.g. source reduction of aquatic habitats). Human population distributions, urbanisation, and human population movement are the key behavioural factors in most IMS-transmitted diseases. Anthropogenic issues are related to the global spread of MBD such as the introduction, reintroduction, circulation of IMS and increased exposure to humans from infected mosquito bites. This review addresses the population and environmental factors underlying the growing changes in IMS populations in Europe and confers the parameters selected by criteria of their applicability. In addition, overview of the commonly used and newly developed tools for their monitoring is provided. PMID:24739334

The Practical Integration of Action Research into Building Climate Literacy and Partnership with Key Influentials

NASA Astrophysics Data System (ADS)

Estrada, M.

2015-12-01

Climate Education Partners (CEP) has been using an action research approach to build climate literacy and partnership with key influential (KI) leaders in the San Diego community. After identifying 6 key sectors that either (a) could reduce green house gas emissions and adapt to impacts, or (b) would be highly vulnerable to the impacts of climate change, we conducted 89 interviews with KIs from the San Diego region -- including elected officials, academics, laborers, and representatives from local businesses, non-profits, ethnic and cultural communities, faith-based groups, and special interest groups -- to assess their science knowledge and opinions about climate change and the impacts of climate change. Other questions asked were about KIs' personal efficacy, identity, values and engagement in pro-environmental behaviors related to climate change. The results of the interviews contributed to CEP's action research approach in two ways: 1) it provided critical data regarding which leaders wanted further engagement with CEP and what that engagement should entail (e.g., being a connector to other leaders, a spokesperson, or a participant in future educational activities), and 2) it provided key information about the extent to which "knowledge deficit" is related to use of climate change knowledge to inform engagement in mitigation and adaptive behaviors. Practically, the results were used to create a database that is being used to inform the contact and education of KIs. We were able to show, consistent with previous research and identity theory, that liberal leaders were more likely than conservatives to believe in, feel concern for, and be knowledgeable about climate change. However, engagement in mitigation behaviors- specifically making decisions that would reduce electricity, gas, or water use- were similar for both groups. These results are being used to create resources and direct climate education activities going forward.

Avoiding dangerous climate change

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

Hans Joachim Schellnhuber; Wolfgang Cramer; Nebojsa Nakicenovic

2006-02-15

In 2005 the UK Government hosted the Avoiding Dangerous Climate Change conference to take an in-depth look at the scientific issues associated with climate change. This volume presents the most recent findings from the leading international scientists that attended the conference. The topics addressed include critical thresholds and key vulnerabilities of the climate system, impacts on human and natural systems, socioeconomic costs and benefits of emissions pathways, and technological options for meeting different stabilisation levels of greenhouse gases in the atmosphere. Contents are: Foreword from Prime Minister Tony Blair; Introduction from Rajendra Pachauri, Chairman of the IPCC; followed by 41more » papers arranged in seven sections entitled: Key Vulnerabilities of the Climate System and Critical Thresholds; General Perspectives on Dangerous Impacts; Key Vulnerabilities for Ecosystems and Biodiversity; Socio-Economic Effects; Regional Perspectives; Emission Pathways; and Technological Options. Four papers have been abstracted separately for the Coal Abstracts database.« less

Climate change and future fire regimes: Examples from California

USGS Publications Warehouse

Keeley, Jon E.; Syphard, Alexandra D.

2016-01-01

Climate and weather have long been noted as playing key roles in wildfire activity, and global warming is expected to exacerbate fire impacts on natural and urban ecosystems. Predicting future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Fuel structure plays a critical role in determining which climatic parameters are most influential on fire activity, and here, by focusing on the diversity of ecosystems in California, we illustrate some principles that need to be recognized in predicting future fire regimes. Spatial scale of analysis is important in that large heterogeneous landscapes may not fully capture accurate relationships between climate and fires. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned; however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models that predict future seasonal temperature changes are needed to improve fire regime projections. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited. Moreover, because they are closely juxtaposed with human habitations, fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science; it is far more complicated than that. Climate change is not relevant to some landscapes, but where climate is relevant, the relationship will change due to direct climate effects on vegetation trajectories, as well as by feedback processes of fire effects on vegetation distribution, plus policy changes in how we manage ecosystems.

Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

NASA Astrophysics Data System (ADS)

Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei

2018-04-01

Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.

Climate and predation dominate juvenile and adult recruitment in a turtle with temperature-dependent sex determination.

PubMed

Schwanz, Lisa E; Spencer, Ricky-John; Bowden, Rachel M; Janzen, Fredric J

2010-10-01

Conditions experienced early in life can influence phenotypes in ecologically important ways, as exemplified by organisms with environmental sex determination. For organisms with temperature-dependent sex determination (TSD), variation in nest temperatures induces phenotypic variation that could impact population growth rates. In environments that vary over space and time, how does this variation influence key demographic parameters (cohort sex ratio and hatchling recruitment) in early life stages of populations exhibiting TSD? We leverage a 17-year data set on a population of painted turtles, Chrysemys picta, to investigate how spatial variation in nest vegetation cover and temporal variation in climate influence early life-history demography. We found that spatial variation in nest cover strongly influenced nest temperature and sex ratio, but was not correlated with clutch size, nest predation, total nest failure, or hatching success. Temporal variation in climate influenced percentage of total nest failure and cohort sex ratio, but not depredation rate, mean clutch size, or mean hatching success. Total hatchling recruitment in a year was influenced primarily by temporal variation in climate-independent factors, number of nests constructed, and depredation rate. Recruitment of female hatchlings was determined by stochastic variation in nest depredation and annual climate and also by the total nest production. Overall population demography depends more strongly on annual variation in climate and predation than it does on the intricacies of nest-specific biology. Finally, we demonstrate that recruitment of female hatchlings translates into recruitment of breeding females into the population, thus linking climate (and other) effects on early life stages to adult demographics.

How can a climate change perspective be integrated into public health surveillance?

PubMed

Pascal, M; Viso, A C; Medina, S; Delmas, M C; Beaudeau, P

2012-08-01

Climate change may be considered as a key factor for environmental change, exposure to health risks and pathogens, consequently impairing the state of health among populations. Efficient health surveillance systems are required to support adaptation to climate change. However, despite a growing awareness, the public health surveillance sector has had very little involvement in the drafting of adaptation plans. This paper proposes a method to raise awareness about climate change in the public health community, to identify possible health risks and to assess the needs for reinforced health surveillance systems. A working group was set up comprising surveillance experts in the following fields: environmental health; chronic diseases and; infectious diseases. Their goal was to define common objectives, to propose a framework for risk analysis, and to apply it to relevant health risks in France. The framework created helped to organize available information on climate-sensitive health risks, making a distinction between three main determinants as follows: (1) environment; (2) individual and social behaviours; and (3) demography and health status. The process is illustrated using two examples: heatwaves and airborne allergens. Health surveillance systems can be used to trigger early warning systems, to create databases which improve scientific knowledge about the health impacts of climate change, to identify and prioritize needs for intervention and adaptation measures, and to evaluate these measures. Adaptation requires public health professionals to consider climate change as a concrete input parameter in their studies and to create partnerships with professionals from other disciplines. Copyright © 2012 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

NASA Astrophysics Data System (ADS)

Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

2016-12-01

One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

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

Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.

2013-12-01

With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning amore » wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.« less

Landscape structure affects distribution of potential disease vectors (Diptera: Culicidae).

PubMed

Zittra, Carina; Vitecek, Simon; Obwaller, Adelheid G; Rossiter, Heidemarie; Eigner, Barbara; Zechmeister, Thomas; Waringer, Johann; Fuehrer, Hans-Peter

2017-04-26

Vector-pathogen dynamics are controlled by fluctuations of potential vector communities, such as the Culicidae. Assessment of mosquito community diversity and, in particular, identification of environmental parameters shaping these communities is therefore of key importance for the design of adequate surveillance approaches. In this study, we assess effects of climatic parameters and habitat structure on mosquito communities in eastern Austria to deliver these highly relevant baseline data. Female mosquitoes were sampled twice a month from April to October 2014 and 2015 at 35 permanent and 23 non-permanent trapping sites using carbon dioxide-baited traps. Differences in spatial and seasonal abundance patterns of Culicidae taxa were identified using likelihood ratio tests; possible effects of environmental parameters on seasonal and spatial mosquito distribution were analysed using multivariate statistical methods. We assessed community responses to environmental parameters based on 14-day-average values that affect ontogenesis. Altogether 29,734 female mosquitoes were collected, and 21 of 42 native as well as two of four non-native mosquito species were reconfirmed in eastern Austria. Statistical analyses revealed significant differences in mosquito abundance between sampling years and provinces. Incidence and abundance patterns were found to be linked to 14-day mean sunshine duration, humidity, water-level maxima and the amount of precipitation. However, land cover classes were found to be the most important factor, effectively assigning both indigenous and non-native mosquito species to various communities, which responded differentially to environmental variables. These findings thus underline the significance of non-climatic variables for future mosquito prediction models and the necessity to consider these in mosquito surveillance programmes.

The contribution of NOAA/CMDL ground-based measurements to understanding long-term stratospheric changes

NASA Astrophysics Data System (ADS)

Montzka, S. A.; Butler, J. H.; Dutton, G.; Thompson, T. M.; Hall, B.; Mondeel, D. J.; Elkins, J. W.

2005-05-01

The El-Nino/Southern-Oscillation (ENSO) dominates interannual climate variability and plays, therefore, a key role in seasonal-to-interannual prediction. Much is known by now about the main physical mechanisms that give rise to and modulate ENSO, but the values of several parameters that enter these mechanisms are an important unknown. We apply Extended Kalman Filtering (EKF) for both model state and parameter estimation in an intermediate, nonlinear, coupled ocean--atmosphere model of ENSO. The coupled model consists of an upper-ocean, reduced-gravity model of the Tropical Pacific and a steady-state atmospheric response to the sea surface temperature (SST). The model errors are assumed to be mainly in the atmospheric wind stress, and assimilated data are equatorial Pacific SSTs. Model behavior is very sensitive to two key parameters: (i) μ, the ocean-atmosphere coupling coefficient between SST and wind stress anomalies; and (ii) δs, the surface-layer coefficient. Previous work has shown that δs determines the period of the model's self-sustained oscillation, while μ measures the degree of nonlinearity. Depending on the values of these parameters, the spatio-temporal pattern of model solutions is either that of a delayed oscillator or of a westward propagating mode. Estimation of these parameters is tested first on synthetic data and allows us to recover the delayed-oscillator mode starting from model parameter values that correspond to the westward-propagating case. Assimilation of SST data from the NCEP-NCAR Reanalysis-2 shows that the parameters can vary on fairly short time scales and switch between values that approximate the two distinct modes of ENSO behavior. Rapid adjustments of these parameters occur, in particular, during strong ENSO events. Ways to apply EKF parameter estimation efficiently to state-of-the-art coupled ocean--atmosphere GCMs will be discussed.

Atlas of Relations Between Climatic Parameters and Distributions of Important Trees and Shrubs in North America - Ecoregions of North America

USGS Publications Warehouse

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

2007-01-01

Climate is the primary factor controlling the continental-scale distribution of plant species, although the relations between climatic parameters and species' ranges are only now beginning to be quantified. This volume examines the relations between climate and the distributions of (1) Kuchler's 'potential natural vegetation' categories for the 48 contiguous States of the United States of America, (2) Bailey's ecoregions of North America, and (3) World Wildlife Fund's ecoregions of North America. For these analyses, we employed a 25-kilometer equal-area grid of modern climatic and bioclimatic parameters for North America, coupled with presence-absence data for the occurrence of each ecoregion under the three classification systems under consideration. The resulting relations between climate and ecoregion distributions are presented in graphical and tabular form. Presentation of ecoregion-climate relations here is intended to be useful for a greater understanding of ecosystem evolution, ecosystem dynamics, and potential effects of future climate change on ecoregions.

Reliability of regional climate simulations

NASA Astrophysics Data System (ADS)

Ahrens, W.; Block, A.; Böhm, U.; Hauffe, D.; Keuler, K.; Kücken, M.; Nocke, Th.

2003-04-01

Quantification of uncertainty becomes more and more a key issue for assessing the trustability of future climate scenarios. In addition to the mean conditions, climate impact modelers focus in particular on extremes. Before generating such scenarios using e.g. dynamic regional climate models, a careful validation of present-day simulations should be performed to determine the range of errors for the quantities of interest under recent conditions as a raw estimate of their uncertainty in the future. Often, multiple aspects shall be covered together, and the required simulation accuracy depends on the user's demand. In our approach, a massive parallel regional climate model shall be used on the one hand to generate "long-term" high-resolution climate scenarios for several decades, and on the other hand to provide very high-resolution ensemble simulations of future dry spells or heavy rainfall events. To diagnosis the model's performance for present-day simulations, we have recently developed and tested a first version of a validation and visualization chain for this model. It is, however, applicable in a much more general sense and could be used as a common test bed for any regional climate model aiming at this type of simulations. Depending on the user's interest, integrated quality measures can be derived for near-surface parameters using multivariate techniques and multidimensional distance measures in a first step. At this point, advanced visualization techniques have been developed and included to allow for visual data mining and to qualitatively identify dominating aspects and regularities. Univariate techniques that are especially designed to assess climatic aspects in terms of statistical properties can then be used to quantitatively diagnose the error contributions of the individual used parameters. Finally, a comprehensive in-depth diagnosis tool allows to investigate, why the model produces the obtained near-surface results to answer the question if the model performs well from the modeler's point of view. Examples will be presented for results obtained using this approach for assessing the risk of potential total agricultural yield loss under drought conditions in Northeast Brazil and for evaluating simulation results for a 10-year period for Europe. To support multi-run simulations and result evaluation, the model will be embedded into an already existing simulation environment that provides further postprocessing tools for sensitivity studies, behavioral analysis and Monte-Carlo simulations, but also for ensemble scenario analysis in one of the next steps.

Evaluating climatic and non-climatic stresses for declining surface water quality in Bagmati River of Nepal.

PubMed

Panthi, Jeeban; Li, Fengting; Wang, Hongtao; Aryal, Suman; Dahal, Piyush; Ghimire, Sheila; Kabenge, Martin

2017-06-01

Both climatic and non-climatic factors affect surface water quality. Similar to its effect across various sectors and areas, climate change has potential to affect surface water quality directly and indirectly. On the one hand, the rise in temperature enhances the microbial activity and decomposition of organic matter in the river system and changes in rainfall alter discharge and water flow in the river ultimately affecting pollution dilution level. On the other hand, the disposal of organic waste and channelizing municipal sewage into the rivers seriously worsen water quality. This study attempts to relate hydro-climatology, water quality, and impact of climatic and non-climatic stresses in affecting river water quality in the upper Bagmati basin in Central Nepal. The results showed that the key water quality indicators such as dissolved oxygen and chemical oxygen demand are getting worse in recent years. No significant relationships were found between the key water quality indicators and changes in key climatic variables. However, the water quality indicators correlated with the increase in urban population and per capita waste production in the city. The findings of this study indicate that dealing with non-climatic stressors such as reducing direct disposal of sewerage and other wastes in the river rather than emphasizing on working with the effects from climate change would largely help to improve water quality in the river flowing from highly populated urban areas.

How much will be economic impact of climate change on water resources? A Meta-Analytic Review of previous literature

NASA Astrophysics Data System (ADS)

Yoshikawa, S.; Iseri, Y.; Kanae, S.

2016-12-01

Water resources is vital in social and economic activities. Total global water use is increasing, mainly due to economic and population growth in developing countries. It has one of risk with high agreement and robust evidence that freshwater-related risks of climate change increase significantly with increasing greenhouse gas concentrations. It is difficult to compare the risk with other field risk (e.g. agriculture, forestry, sea level rise) for considering both adaptation and mitigation policy with the level of decision makers and public servants. Economic impacts of climate change on water scarcity has been estimated by economic researchers. We have no certainty at all about integration between hydrological and economical fields on global scale. In this study, we highlight key concerns about conventional estimations of economic impact on water resources through meta-analysis. The economic impact on water resource in same base year using consumer price index is shown with increase in the global mean temperature. We clarified four concerns which are involved in 1) classification of economic mechanism, 2) estimated items of economic impact, 3) difference in estimating equations, and 4) definition of parameters related with economic impact of climate change. This study would be essential to next challenge as transdisciplinary research between hydrologic and economic fields.

Climatic origins predict variation in photoprotective leaf pigments in response to drought and low temperatures in live oaks (Quercus series Virentes).

PubMed

Ramírez-Valiente, Jose A; Koehler, Kari; Cavender-Bares, Jeannine

2015-05-01

Climate is a major selective force in nature. Exploring patterns of inter- and intraspecific genetic variation in functional traits may explain how species have evolved and may continue evolving under future climate change. Photoprotective pigments play an important role in short-term responses to climate stress in plants but knowledge of their long-term role in adaptive processes is lacking. In this study, our goal was to determine how photoprotective mechanisms, morphological traits and their plasticity have evolved in live oaks (Quercus series Virentes) in response to different climatic conditions. For this purpose, seedlings originating from 11 populations from four live oak species (Quercus virginiana, Q. geminata, Q. fusiformis and Q. oleoides) were grown under contrasting common environmental conditions of temperature (tropical vs temperate) and water availability (droughted vs well-watered). Xanthophyll cycle pigments, anthocyanin accumulation, chlorophyll fluorescence parameters and leaf anatomical traits were measured. Seedlings originating from more mesic source populations of Q. oleoides and Q. fusiformis increased the xanthophyll de-epoxidation state under water-limiting conditions and showed higher phenotypic plasticity for this trait, suggesting adaptation to local climate. Likewise, seedlings originating from warmer climates had higher anthocyanin concentration in leaves under cold winter conditions but not higher de-epoxidation state. Overall, our findings suggest that (i) climate has been a key factor in shaping species and population differences in stress tolerance for live oaks, (ii) anthocyanins are used under cold stress in species with limited freezing tolerance and (iii) xanthophyll cycle pigments are used when photoprotection under drought conditions is needed. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Satellite remote sensing assessment of climate impact on forest vegetation dynamics

NASA Astrophysics Data System (ADS)

Zoran, M.

2009-04-01

Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modelling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2007 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

2017-11-01

Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize ( Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

Atlas of Relations Between Climatic Parameters and Distributions of Important Trees and Shrubs in North America - Alaska Species and Ecoregions

USGS Publications Warehouse

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

2006-01-01

Climate is the primary factor in controlling the continental-scale distribution of plant species, although the relations between climatic parameters and species' ranges is only now beginning to be quantified. Preceding volumes of this atlas explored the continental-scale relations between climatic parameters and the distributions of woody plant species across all of the continent of North America. This volume presents similar information for important woody species, groups of species, and ecoregions in more detail for the State of Alaska. For these analyses, we constructed a 25-kilometer equal-area grid of modern climatic and bioclimatic parameters for North America from instrumental weather records. We obtained a digital representation of the geographic distribution of each species or ecoregion, either from a published source or by digitizing the published distributions ourselves. The presence or absence of each species or ecoregion was then determined for each point on the 25-kilometer grid, thus providing a basis for comparison of the climatic data with the geographic distribution of each species or ecoregion. The relations between climate and these distributions are presented in graphical and tabular form.

Quantitative predictions of streamflow variability in the Susquehanna River Basin

NASA Astrophysics Data System (ADS)

Alexander, R.; Boyer, E. W.; Leonard, L. N.; Duffy, C.; Schwarz, G. E.; Smith, R. A.

2012-12-01

Hydrologic researchers and water managers have increasingly sought an improved understanding of the major processes that control fluxes of water and solutes across diverse environmental settings and large spatial scales. Regional analyses of observed streamflow data have led to advances in our knowledge of relations among land use, climate, and streamflow, with methodologies ranging from statistical assessments of multiple monitoring sites to the regionalization of the parameters of catchment-scale mechanistic simulation models. However, gaps remain in our understanding of the best ways to transfer the knowledge of hydrologic response and governing processes among locations, including methods for regionalizing streamflow measurements and model predictions. We developed an approach to predict variations in streamflow using the SPARROW (SPAtially Referenced Regression On Watershed attributes) modeling infrastructure, with mechanistic functions, mass conservation constraints, and statistical estimation of regional and sub-regional parameters. We used the model to predict discharge in the Susquehanna River Basin (SRB) under varying hydrological regimes that are representative of contemporary flow conditions. The resulting basin-scale water balance describes mean monthly flows in stream reaches throughout the entire SRB (represented at a 1:100,000 scale using the National Hydrologic Data network), with water supply and demand components that are inclusive of a range of hydrologic, climatic, and cultural properties (e.g., precipitation, evapotranspiration, soil and groundwater storage, runoff, baseflow, water use). We compare alternative models of varying complexity that reflect differences in the number and types of explanatory variables and functional expressions as well as spatial and temporal variability in the model parameters. Statistical estimation of the models reveals the levels of complexity that can be uniquely identified, subject to the information content and uncertainties of the hydrologic and climate measurements. Assessment of spatial variations in the model parameters and predictions provides an improved understanding of how much of the hydrologic response to land use, climate, and other properties is unique to specific locations versus more universally observed across catchments of the SRB. This approach advances understanding of water cycle variability at any location throughout the stream network, as a function of both landscape characteristics (e.g., soils, vegetation, land use) and external forcings (e.g., precipitation quantity and frequency). These improvements in predictions of streamflow dynamics will advance the ability to predict spatial and temporal variability in key solutes, such as nutrients, and their delivery to the Chesapeake Bay.

Uncertainty and the Social Cost of Methane Using Bayesian Constrained Climate Models

NASA Astrophysics Data System (ADS)

Errickson, F. C.; Anthoff, D.; Keller, K.

2016-12-01

Social cost estimates of greenhouse gases are important for the design of sound climate policies and are also plagued by uncertainty. One major source of uncertainty stems from the simplified representation of the climate system used in the integrated assessment models that provide these social cost estimates. We explore how uncertainty over the social cost of methane varies with the way physical processes and feedbacks in the methane cycle are modeled by (i) coupling three different methane models to a simple climate model, (ii) using MCMC to perform a Bayesian calibration of the three coupled climate models that simulates direct sampling from the joint posterior probability density function (pdf) of model parameters, and (iii) producing probabilistic climate projections that are then used to calculate the Social Cost of Methane (SCM) with the DICE and FUND integrated assessment models. We find that including a temperature feedback in the methane cycle acts as an additional constraint during the calibration process and results in a correlation between the tropospheric lifetime of methane and several climate model parameters. This correlation is not seen in the models lacking this feedback. Several of the estimated marginal pdfs of the model parameters also exhibit different distributional shapes and expected values depending on the methane model used. As a result, probabilistic projections of the climate system out to the year 2300 exhibit different levels of uncertainty and magnitudes of warming for each of the three models under an RCP8.5 scenario. We find these differences in climate projections result in differences in the distributions and expected values for our estimates of the SCM. We also examine uncertainty about the SCM by performing a Monte Carlo analysis using a distribution for the climate sensitivity while holding all other climate model parameters constant. Our SCM estimates using the Bayesian calibration are lower and exhibit less uncertainty about extremely high values in the right tail of the distribution compared to the Monte Carlo approach. This finding has important climate policy implications and suggests previous work that accounts for climate model uncertainty by only varying the climate sensitivity parameter may overestimate the SCM.

[Research on quality regionalization of cultivated Pseudostellaria heterophylla based on climate factors].

PubMed

Kang, Chuan-Zhi; Zhou, Tao; Jiang, Wei-Ke; Guo, Lan-Ping; Zhang, Xiao-Bo; Xiao, Cheng-Hong; Zhao, Dan

2016-07-01

Maxent model was applied in the study to filtering the climate factors layer by layer. Polysaccharides and pseudostellarin B the two internal quality evaluation index were combined to analyse the interlinkages between climate factors and chemical constituents in order to search for the critical climate factors of Pseudostellaria heterophylla. Then based on the key climate factors to explicit the quality spatial distribution of P. heterophylla. The results showed that polysaccharides and climatic factors had no significant correlation, suggesting that the indicator was not climate-driven metabolites. Pseudostellarin B could construct regression model with the precipitation. And quality regionalization results showed that pseudostellarin B content presented firstly increased and then decreased trend from southeast to northwest, which was the consistent change with precipitation. It clearly proposed that precipitation was the key climate factor, which affected the accumulation of cyclopeptide compound for Pseudostellariae Radix. Copyright© by the Chinese Pharmaceutical Association.

Methods for developing time-series climate surfaces to drive topographically distributed energy- and water-balance models

USGS Publications Warehouse

Susong, D.; Marks, D.; Garen, D.

1999-01-01

Topographically distributed energy- and water-balance models can accurately simulate both the development and melting of a seasonal snowcover in the mountain basins. To do this they require time-series climate surfaces of air temperature, humidity, wind speed, precipitation, and solar and thermal radiation. If data are available, these parameters can be adequately estimated at time steps of one to three hours. Unfortunately, climate monitoring in mountain basins is very limited, and the full range of elevations and exposures that affect climate conditions, snow deposition, and melt is seldom sampled. Detailed time-series climate surfaces have been successfully developed using limited data and relatively simple methods. We present a synopsis of the tools and methods used to combine limited data with simple corrections for the topographic controls to generate high temporal resolution time-series images of these climate parameters. Methods used include simulations, elevational gradients, and detrended kriging. The generated climate surfaces are evaluated at points and spatially to determine if they are reasonable approximations of actual conditions. Recommendations are made for the addition of critical parameters and measurement sites into routine monitoring systems in mountain basins.Topographically distributed energy- and water-balance models can accurately simulate both the development and melting of a seasonal snowcover in the mountain basins. To do this they require time-series climate surfaces of air temperature, humidity, wind speed, precipitation, and solar and thermal radiation. If data are available, these parameters can be adequately estimated at time steps of one to three hours. Unfortunately, climate monitoring in mountain basins is very limited, and the full range of elevations and exposures that affect climate conditions, snow deposition, and melt is seldom sampled. Detailed time-series climate surfaces have been successfully developed using limited data and relatively simple methods. We present a synopsis of the tools and methods used to combine limited data with simple corrections for the topographic controls to generate high temporal resolution time-series images of these climate parameters. Methods used include simulations, elevational gradients, and detrended kriging. The generated climate surfaces are evaluated at points and spatially to determine if they are reasonable approximations of actual conditions. Recommendations are made for the addition of critical parameters and measurement sites into routine monitoring systems in mountain basins.

(AC)3: A German Initiative to Study Arctic Amplification—Climate Relevant Atmospheric and Surface Processes and Feedback Mechanisms

NASA Astrophysics Data System (ADS)

Spreen, G.; Wendisch, M.; Brückner, M.

2016-12-01

Within the last 25 years a remarkable increase of the Arctic near-surface air temperature exceeding the global warming by a factor of at least two has been observed. This phenomenon is commonly referred to as Arctic Amplification. The warming results in rather dramatic changes of a variety of climate parameters. For example, the Arctic sea ice has declined significantly. This ice retreat has been well identified by satellite measurements. Over recent decades, significant progress has been made in two main scientific areas: (i) the capabilities of in-situ measurements and remote sensing techniques to observe key physico-chemical atmospheric constituents and surface parameters at high latitudes have advanced impressively, and (ii) the computational skills and power used to model individual feedback mechanisms on small scales have improved notably. It is, therefore, timely to exploit synergistically these new developments to enhance our knowledge of the origins of the observed Arctic climate changes. To achieve this aim a new Transregional Collaborative Research Center (TR 172) was launched in January 2016 called "ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms" with the acronym (AC)3. Observations from instrumentation on satellites, aircraft, tethered balloons, research vessels, and a selected set of ground-based sites will be integrated in dedicated campaigns, as well as being combined with long-term measurements. The field studies will be conducted in different seasons and meteorological conditions, covering a suitably wide range of spatial and temporal scales. They will be performed in an international context and in close collaboration with modelling activities. The latter utilize a hierarchy of process, meso-scale, regional, and global models to bridge the spatio-temporal scales from local individual processes to appropriate climate signals. The models will serve to guide the campaigns, to analyse the measurements and sensitivities, to facilitate the attribution of the origins of observed Arctic climate changes, and to test the ability of the models to reproduce observations. The presentation will give an overview of the scientific rationale, objectives, international links, and the work program of the (AC)³ project.

Uncertainty Quantification in Climate Modeling and Projection

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

Qian, Yun; Jackson, Charles; Giorgi, Filippo

The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change informationmore » for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.« less

Application of Unmanned Aircraft System Instrumentation to Study Coastal Geochemistry

NASA Astrophysics Data System (ADS)

Coffin, R. B.; Osburn, C. L.; Smith, J. P.

2016-02-01

Coastal evaluation of key geochemical cycles is in strong need for thorough spatial data to address diverse topics. In many field studies we find that fixed station data taken from ship operations does not provide complete understanding of key research questions. In complicated systems where there is a need to integrate physical, chemical and biological parameters data taken from research vessels needs to be interpreted across large spatial areas. New technology in Unmanned Aircraft System (UAS) instrumentation coupled with ship board data can provide the thorough spatial data needed for a thorough evaluation of coastal sciences. This presentation will provide field data related to UAS application in two diverse environments. One study focuses on the flux of carbon dioxide and methane from Alaskan Arctic tundra and shallow Beaufort Sea coastal region to the atmosphere. In this study gas chemistry from samples is used to predict the relative fluxes to the atmosphere. A second study applies bio-optical analyses to differentiate between Gulf of Mexico coastal water column DOC and Lignin. This wide range of parameters in diverse ecosystems is selected to show current capability for application of UAS and the potential for understanding large scale questions about climate change and carbon cycling in coastal waters.

Use of Climatic Information In Regional Water Resources Assessment

NASA Astrophysics Data System (ADS)

Claps, P.

Relations between climatic parameters and hydrological variables at the basin scale are investigated, with the aim of evaluating in a parsimonious way physical parameters useful both for a climatic classification of an area and for supporting statistical models of water resources assessment. With reference to the first point, literature methods for distributed evaluation of parameters such as temperature, global and net solar radiation, precipitation, have been considered at the annual scale with the aim of considering the viewpoint of the robust evaluation of parameters based on few basic physical variables of simple determination. Elevation, latitude and average annual number of sunny days have demonstrated to be the essential parameters with respect to the evaluation of climatic indices related to the soil water deficit and to the radiative balance. The latter term was evaluated at the monthly scale and validated (in the `global' term) with measured data. in questo caso riferite al bilancio idrico a scala annuale. Budyko, Thornthwaite and Emberger climatic indices were evaluated on the 10,000 km2 territory of the Basilicata region (southern Italy) based on a 1.1. km grid. They were compared in terms of spatial variability and sensitivity to the variation of the basic variables in humid and semi-arid areas. The use of the climatic index data with respect to statistical parameters of the runoff series in some gauging stations of the region demonstrated the possibility to support regionalisation of the annual runoff using climatic information, with clear distinction of the variability of the coefficient of variation in terms of the humidity-aridity of the basin.

University students as recipients of and contributors to information on climate change: insights from South Africa and implications for well-being.

PubMed

El Zoghbi, Mona Betour; El Ansari, Walid

2014-06-01

This study aimed to enhance the in-depth understanding of the contextual dimensions that shape the relationships between climate change communication approach and youth well-being. The study focused on university students who constitute the key stakeholders and future decision-makers and leaders for managing the long-term climate risks. A total of 10 focus group interviews were conducted with 117 undergraduate and graduate South African university students from over 12 universities located in different provinces of South Africa. In addition, another 16 interviews were also undertaken with university students, 10 interviews with key experts, and 3 youth national events were attended as participant-observation. As recipients of information on climate change, students' well-being was negatively affected by the media's pessimism of communicating risks and the inadequate or restricted networking of communicating solutions and strategies. As contributors to information on climate change, students faced key barriers to their efficacy and agency that entailed socio-cultural inequalities (e.g. race and language) and a lack of formal forums for community recognition, policy consultation and collaboration. In addition, for some students (e.g. journalism students), the lack of sufficient knowledge and skills on climate change and sustainability issues limited their ability to effectively communicate these issues to their audience. Platforms for interactive and reflective discussions, access to innovative technologies and social media, and opportunities for multi-stakeholder partnerships are keys to the success of youth-targeted and youth-initiated communication on climate change.

Global volcanic aerosol properties derived from emissions, 1990-2014, using CESM1(WACCM): VOLCANIC AEROSOLS DERIVED FROM EMISSIONS

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

Mills, Michael J.; Schmidt, Anja; Easter, Richard

Accurate representation of global stratospheric aerosol properties from volcanic and non-volcanic sulfur emissions is key to understanding the cooling effects and ozone-loss enhancements of recent volcanic activity. Attribution of climate and ozone variability to volcanic activity is of particular interest in relation to the post-2000 slowing in the apparent rate of global average temperature increases, and variable recovery of the Antarctic ozone hole. We have developed a climatology of global aerosol properties from 1990 to 2014 calculated based on volcanic and non-volcanic emissions of sulfur sources. We have complied a database of volcanic SO2 emissions and plume altitudes for eruptionsmore » between 1990 and 2014, and a new prognostic capability for simulating stratospheric sulfate aerosols in version 5 of the Whole Atmosphere Community Climate Model, a component of the Community Earth System Model. Our climatology shows remarkable agreement with ground-based lidar observations of stratospheric aerosol optical depth (SAOD), and with in situ measurements of aerosol surface area density (SAD). These properties are key parameters in calculating the radiative and chemical effects of stratospheric aerosols. Our SAOD climatology represents a significant improvement over satellite-based analyses, which ignore aerosol extinction below 15 km, a region that can contain the vast majority of stratospheric aerosol extinction at mid- and high-latitudes. Our SAD climatology significantly improves on that provided for the Chemistry-Climate Model Initiative, which misses 60% of the SAD measured in situ. Our climatology of aerosol properties is publicly available on the Earth System Grid.« less

The MIT IGSM-CAM framework for uncertainty studies in global and regional climate change

NASA Astrophysics Data System (ADS)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2011-12-01

The MIT Integrated Global System Model (IGSM) version 2.3 is an intermediate complexity fully coupled earth system model that allows simulation of critical feedbacks among its various components, including the atmosphere, ocean, land, urban processes and human activities. A fundamental feature of the IGSM2.3 is the ability to modify its climate parameters: climate sensitivity, net aerosol forcing and ocean heat uptake rate. As such, the IGSM2.3 provides an efficient tool for generating probabilistic distribution functions of climate parameters using optimal fingerprint diagnostics. A limitation of the IGSM2.3 is its zonal-mean atmosphere model that does not permit regional climate studies. For this reason, the MIT IGSM2.3 was linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM) version 3 and new modules were developed and implemented in CAM in order to modify its climate sensitivity and net aerosol forcing to match that of the IGSM. The IGSM-CAM provides an efficient and innovative framework to study regional climate change where climate parameters can be modified to span the range of uncertainty and various emissions scenarios can be tested. This paper presents results from the cloud radiative adjustment method used to modify CAM's climate sensitivity. We also show results from 21st century simulations based on two emissions scenarios (a median "business as usual" scenario where no policy is implemented after 2012 and a policy scenario where greenhouse-gas are stabilized at 660 ppm CO2-equivalent concentrations by 2100) and three sets of climate parameters. The three values of climate sensitivity chosen are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the observed 20th century climate change with simulations by the IGSM with a wide range of climate parameters values. The associated aerosol forcing values were chosen to ensure a good agreement of the simulations with the observed climate change over the 20th century. Because the concentrations of sulfate aerosols significantly decrease over the 21st century in both emissions scenarios, climate changes obtained in these six simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.

The Social Network of Tracer Variations and O(100) Uncertain Photochemical Parameters in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Labute, M.; Chowdhary, K.; Debusschere, B.; Cameron-Smith, P. J.

2014-12-01

Simulating the atmospheric cycles of ozone, methane, and other radiatively important trace gases in global climate models is computationally demanding and requires the use of 100's of photochemical parameters with uncertain values. Quantitative analysis of the effects of these uncertainties on tracer distributions, radiative forcing, and other model responses is hindered by the "curse of dimensionality." We describe efforts to overcome this curse using ensemble simulations and advanced statistical methods. Uncertainties from 95 photochemical parameters in the trop-MOZART scheme were sampled using a Monte Carlo method and propagated through 10,000 simulations of the single column version of the Community Atmosphere Model (CAM). The variance of the ensemble was represented as a network with nodes and edges, and the topology and connections in the network were analyzed using lasso regression, Bayesian compressive sensing, and centrality measures from the field of social network theory. Despite the limited sample size for this high dimensional problem, our methods determined the key sources of variation and co-variation in the ensemble and identified important clusters in the network topology. Our results can be used to better understand the flow of photochemical uncertainty in simulations using CAM and other climate models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and supported by the DOE Office of Science through the Scientific Discovery Through Advanced Computing (SciDAC).

The Evolution of Root Zone Storage Capacity after Land Use Change

NASA Astrophysics Data System (ADS)

Nijzink, Remko C.; Hutton, Christopher; Pechlivanidis, Ilias; Capell, René; Arheimer, Berit; Wagener, Thorsten; Savenije, Hubert H. G.; Hrachowitz, Markus

2016-04-01

Root zone storage capacity forms a crucial parameter in ecosystem functioning as it is the key parameter that determines the partitioning between runoff and transpiration. There is increasing evidence from several case studies for specific plants that vegetation adapts to the critical situation of droughts. For example, trees will, on the long term, try to improve their internal hydraulic conductivity after droughts, for example by allocating more biomass for roots. In spite of this understanding, the water storage capacity in the root zone is often treated as constant in hydrological models. In this study, it was hypothesized that root zone storage capacities are altered by deforestation and the regrowth of the ecosystem. Three deforested sub catchments as well as not affected, nearby control catchments of the experimental forests of HJ Andrews and Hubbard Brook were selected for this purpose. Root zone storage capacities were on the one hand estimated by a climate-based approach similar to Gao et al. (2014), making use of simple water balance considerations to determine the evaporative demand of the system. In this way, the maximum deficit between evaporative demand and precipitation allows a robust estimation of the root zone storage capacity. On the other hand, three conceptual hydrological models (FLEX, HYPE, HYMOD) were calibrated in a moving window approach for all catchments. The obtained model parameter values representing the root zone storage capacities of the individual catchments for each moving window period were then compared to the estimates derived from climate data for the same periods. Model- and climate-derived estimates of root zone storage capacities both showed a similar evolution. In the deforested catchments, considerable reductions of the root zone storage capacities, compared to the pre-treatment situation and control catchments, were observed. In addition, the years after forest clearing were characterized by a gradual recovery of the root zone storage capacities, converging to new equilibrium conditions and linked to forest regrowth. Further trend analysis suggested a relatively quick hydrological recovery between 5 and 15 years in the study catchments. The results lend evidence to the role of both, climate and vegetation dynamics for the development of root zone systems and their controlling influence on hydrological response dynamics.

Examining the recent climate through the lens of ecology: inferences from temporal pattern analysis.

Treesearch

Paul F. Hessburg; Ellen E. Kuhlmann; Thomas W. Swetnam

2005-01-01

Ecological theory asserts that the climate of a region exerts top-down controls on regional ecosystem patterns and processes, across space and time. To provide empirical evidence of climatic controls, it would be helpful to define climatic regions that minimized variance in key climate attributes, within climatic regions-define the periods and features of climatic...

Customized rating assessment of climate suitability (CRACS): climate satisfaction evaluation based on subjective perception.

PubMed

Lin, Tzu-Ping; Yang, Shing-Ru; Matzarakis, Andreas

2015-12-01

Climate not only influences the behavior of people in urban environments but also affects people's schedules and travel plans. Therefore, providing people with appropriate long-term climate evaluation information is crucial. Therefore, we developed an innovative climate assessment system based on field investigations conducted in three cities located in Northern, Central, and Southern Taiwan. The field investigations included the questionnaire surveys and climate data collection. We first analyzed the relationship between the participants and climate parameters comprising physiologically equivalent temperature, air temperature, humidity, wind speed, solar radiation, cloud cover, and precipitation. Second, we established the neutral value, comfort range, and dissatisfied range of each parameter. Third, after verifying that the subjects' perception toward the climate parameters vary based on individual preferences, we developed the customized rating assessment of climate suitability (CRACS) approach, which featured functions such as personalized and default climate suitability information to be used by users exhibiting varying demands. Finally, we performed calculations using the climate conditions of two cities during the past 10 years to demonstrate the performance of the CRACS approach. The results can be used as a reference when planning activities in the city or when organizing future travel plans. The flexibility of the assessment system enables it to be adjusted for varying regions and usage characteristics.

Customized rating assessment of climate suitability (CRACS): climate satisfaction evaluation based on subjective perception

NASA Astrophysics Data System (ADS)

Lin, Tzu-Ping; Yang, Shing-Ru; Matzarakis, Andreas

2015-12-01

Climate not only influences the behavior of people in urban environments but also affects people's schedules and travel plans. Therefore, providing people with appropriate long-term climate evaluation information is crucial. Therefore, we developed an innovative climate assessment system based on field investigations conducted in three cities located in Northern, Central, and Southern Taiwan. The field investigations included the questionnaire surveys and climate data collection. We first analyzed the relationship between the participants and climate parameters comprising physiologically equivalent temperature, air temperature, humidity, wind speed, solar radiation, cloud cover, and precipitation. Second, we established the neutral value, comfort range, and dissatisfied range of each parameter. Third, after verifying that the subjects' perception toward the climate parameters vary based on individual preferences, we developed the customized rating assessment of climate suitability (CRACS) approach, which featured functions such as personalized and default climate suitability information to be used by users exhibiting varying demands. Finally, we performed calculations using the climate conditions of two cities during the past 10 years to demonstrate the performance of the CRACS approach. The results can be used as a reference when planning activities in the city or when organizing future travel plans. The flexibility of the assessment system enables it to be adjusted for varying regions and usage characteristics.

Improving the Representation of Land in Climate Models by Application of EOS Observations

NASA Technical Reports Server (NTRS)

2004-01-01

The PI's IDS current and previous investigation has focused on the applications of the land data toward the improvement of climate models. The previous IDS research identified the key factors limiting the accuracy of climate models to be the representation of albedos, land cover, fraction of landscape covered by vegetation, roughness lengths, surface skin temperature and canopy properties such as leaf area index (LAI) and average stomatal conductance. Therefore, we assembled a team uniquely situated to focus on these key variables and incorporate the remotely sensed measures of these variables into the next generation of climate models.

Effect of cross-link density on carbon dioxide separation in polydimethylsiloxane-norbornene membranes

DOE PAGES

Hong, Tao; Niu, Zhenbin; Hu, Xunxiang; ...

2015-10-20

The development of high performance materials for CO 2 separation and capture will significantly contribute to a solution for climate change. In this work, (bicycloheptenyl) ethyl terminated polydimethylsiloxane (PDMSPNB) membranes with varied cross-link densities were synthesized via ring-opening metathesis polymerization. The developed polymer membranes show higher permeability and better selectivity than those of conventional cross-linked PDMS membrane. The achieved performance (CO 2 permeability ~ 6800 Barrer and CO 2/N 2 selectivity ~ 14) is very promising for practical applications. The key to achieving this high performance is the use of an in-situ cross-linking method of the difunctional PDMS macromonomers, whichmore » provides lightly cross-linked membranes. By combining positron annihilation lifetime spectroscopy, broadband dielectric spectroscopy and gas solubility measurements, we have elucidated the key parameters necessary for achieving their excellent performance.« less

Variation in skin biology to climate in Shanghai, China.

PubMed

Liu, Xiaoping; Gao, Yanrui; Zhang, Yiyi; Wang, Xuemin

2017-09-01

To explore the relationship between climate and skin condition, and to investigate the variation of skin biology to climatic change. In total, 2005 healthy Chinese volunteers living in Shanghai (aged 13-69 years) were recruited. Transepidermal water loss (TEWL) and SCH were tested on six sites (forehead, cheek, nasolabial, inner forearm, dorsal hand, and palm) by noninvasive devices between January 2005 and December 2012. The corresponding climate data were recorded by local Weather Bureau. TEWL was increased with atmospheric pressure and decreased with temperature, steam pressure, and relative humidity (p < 0.05). SCH was increased with steam pressure and decreased with atmospheric pressure (p < 0.05); there was no obvious trend between SCH and temperature and SCH and relative humidity. To investigate the climate parameters together, we introduced these correlated factors into the multivariate linear regression model which demonstrated that temperature and steam pressure were main factors related to skin biological parameters. At different sites, the effect of climatic factors on skin biology was diverse. Skin biological parameters are associated with climatic factors. Different sites have different sensitivity to climate factors.

Evolution of the Climate Continuum from the Mid-Miocene Climatic Optimum to the Present

NASA Astrophysics Data System (ADS)

Aswasereelert, W.; Meyers, S. R.; Hinnov, L. A.; Kelly, D.

2011-12-01

The recognition of orbital rhythms in paleoclimate data has led to a rich understanding of climate evolution during the Neogene and Quaternary. In contrast, changes in stochastic variability associated with the transition from unipolar to bipolar glaciation have received less attention, although the stochastic component likely preserves key insights about climate. In this study, we seek to evaluate the dominance and character of stochastic climate energy since the Middle Miocene Climatic Optimum (~17 Ma). These analyses extend a previous study that suggested diagnostic stochastic responses associated with Northern Hemisphere ice sheet development during the Plio-Pleistocene (Meyers and Hinnov, 2010). A critical and challenging step necessary to conduct the work is the conversion of depth data to time data. We investigate climate proxy datasets using multiple time scale hypotheses, including depth-derived time scales, sedimentologic/geochemical "tuning", minimal orbital tuning, and comprehensive orbital tuning. To extract the stochastic component of climate, and also explore potential relationships between the orbital parameters and paleoclimate response, a number of approaches rooted in Thomson's (1982) multi-taper spectral method (MTM) are applied. Importantly, the MTM technique is capable of separating the spectral "continuum" - a measure of stochastic variability - from the deterministic periodic orbital signals (spectral "lines") preserved in proxy data. Time series analysis of the proxy records using different chronologic approaches allows us to evaluate the sensitivity of our conclusion about stochastic and deterministic orbital processes during the Middle Miocene to present. Moreover, comparison of individual records permits examination of the spatial dependence of the identified climate responses. Meyers, S.R., and Hinnov, L.A. (2010), Northern Hemisphere glaciation and the evolution of Plio-Pleistocene climate noise: Paleoceanography, 25, PA3207, doi:10.1029/2009PA001834. Thomson, D.J. (1982), Spectrum estimation and harmonic analysis: IEEE Proceedings, v. 70, p. 1055-1096.

Climatic effects on mosquito abundance in Mediterranean wetlands

PubMed Central

2014-01-01

Background The impact of climate change on vector-borne diseases is highly controversial. One of the principal points of debate is whether or not climate influences mosquito abundance, a key factor in disease transmission. Methods To test this hypothesis, we analysed ten years of data (2003–2012) from biweekly surveys to assess inter-annual and seasonal relationships between the abundance of seven mosquito species known to be pathogen vectors (West Nile virus, Usutu virus, dirofilariasis and Plasmodium sp.) and several climatic variables in two wetlands in SW Spain. Results Within-season abundance patterns were related to climatic variables (i.e. temperature, rainfall, tide heights, relative humidity and photoperiod) that varied according to the mosquito species in question. Rainfall during winter months was positively related to Culex pipiens and Ochlerotatus detritus annual abundances. Annual maximum temperatures were non-linearly related to annual Cx. pipiens abundance, while annual mean temperatures were positively related to annual Ochlerotatus caspius abundance. Finally, we modelled shifts in mosquito abundances using the A2 and B2 temperature and rainfall climate change scenarios for the period 2011–2100. While Oc. caspius, an important anthropophilic species, may increase in abundance, no changes are expected for Cx. pipiens or the salt-marsh mosquito Oc. detritus. Conclusions Our results highlight that the effects of climate are species-specific, place-specific and non-linear and that linear approaches will therefore overestimate the effect of climate change on mosquito abundances at high temperatures. Climate warming does not necessarily lead to an increase in mosquito abundance in natural Mediterranean wetlands and will affect, above all, species such as Oc. caspius whose numbers are not closely linked to rainfall and are influenced, rather, by local tidal patterns and temperatures. The final impact of changes in vector abundance on disease frequency will depend on the direct and indirect effects of climate and other parameters related to pathogen amplification and spillover on humans and other vertebrates. PMID:25030527

The I.A.G. / A.I.G. SEDIBUD Book Project: Source-to-Sink Fluxes in Undisturbed Cold Environments

NASA Astrophysics Data System (ADS)

Beylich, Achim A.; Dixon, John C.; Zwolinski, Zbigniew

2015-04-01

The currently prepared SEDIBUD Book on "Source-to-Sink Fluxes in Undisturbed Cold Environments" (edited by Achim A. Beylich, John C. Dixon and Zbigniew Zwolinski and published by Cambridge University Press) is summarizing and synthesizing the achievements of the International Association of Geomorphologists` (I.A.G./A.I.G.) Working Group SEDIBUD (Sediment Budgets in Cold Environments), which has been active since 2005 (http://www.geomorph.org/wg/wgsb.html). Amplified climate change and ecological sensitivity of largely undisturbed polar and high-altitude cold climate environments have been highlighted as key global environmental issues. The effects of projected climate change will change surface environments in cold regions and will alter the fluxes of sediments, nutrients and solutes, but the absence of quantitative data and coordinated geomorphic process monitoring and analysis to understand the sensitivity of the Earth surface environment in these largely undisturbed environments is acute. Our book addresses this existing key knowledge gap. The applied approach of integrating comparable and longer-term field datasets on contemporary solute and sedimentary fluxes from a number of different defined cold climate catchment geosystems for better understanding (i) the environmental drivers and rates of contemporary denudational surface processes and (ii) possible effects of projected climate change in cold regions is unique in the field of geomorphology. Largely undisturbed cold climate environments can provide baseline data for modeling the effects of environmental change. The book synthesizes work carried out by numerous SEDIBUD Members over the last decade in numerous cold climate catchment geosystems worldwide. For reaching a global cover of different cold climate environments the book is - after providing an introduction part and a basic part on climate change in cold environments and general implications for solute and sedimentary fluxes - dealing in different defined parts with Sub-Arctic and Arctic Environments, Sub-Antarctic and Antarctic Environments, and Alpine / Mountain Environments. The book includes a synthesis key chapter where comparable datasets on contemporary solute and sedimentary fluxes generated during the conducted coordinated research efforts in different cold climate catchment geosystems are integrated with the key goals to (i) identify the main environmental drivers and rates of contemporary solute and sedimentary fluxes, and (ii) model possible effects of projected climate change on solute and sedimentary fluxes in cold climate environments. The SEDIBUD Book provides new key findings on environmental drivers and rates of contemporary solute and sedimentary fluxes, and on spatial variability within global cold climate environments. The book will go in production in July 2015.

Influences of removing linear and nonlinear trends from climatic variables on temporal variations of annual reference crop evapotranspiration in Xinjiang, China.

PubMed

Li, Yi; Yao, Ning; Chau, Henry Wai

2017-08-15

Reference crop evapotranspiration (ET o ) is a key parameter in field irrigation scheduling, drought assessment and climate change research. ET o uses key prescribed (or fixed or reference) land surface parameters for crops. The linear and nonlinear trends in different climatic variables (CVs) affect ET o change. This research aims to reveal how ET o responds after the related CVs were linearly and nonlinearly detrended over 1961-2013 in Xinjiang, China. The ET o -related CVs included minimum (T min ), average (T ave ), and maximum air temperatures (T max ), wind speed at 2m (U 2 ), relative humidity (RH) and sunshine hour (n). ET o was calculated using the Penman-Monteith equation. A total of 29 ET o scenarios, including the original scenario, 14 scenarios in Group I (ET o was recalculated after removing linear trends from single or more CVs) and 14 scenarios in Group II (ET o was recalculated after removing nonlinear trends from the CVs), were generated. The influence of U 2 was stronger than influences of the other CVs on ET o for both Groups I and II either in northern, southern or the entirety of Xinjiang. The weak influences of increased T min , T ave and T max on increasing ET o were masked by the strong effects of decreased U 2 &n and increased RH on decreasing ET o . The effects of the trends in CVs, especially U 2 , on changing ET o were clearly shown. Without the general decreases of U 2 , ET o would have increased in the past 53years. Due to the non-monotone variations of the CVs and ET o , the results of nonlinearly detrending CVs on changing ET o in Group II should be more plausible than the results of linearly detrending CVs in Group I. The decreasing ET o led to a general relief in drought, which was indicated by the recalculated aridity index. Therefore, there would be a slightly lower risk of water utilization in Xinjiang, China. Copyright © 2017 Elsevier B.V. All rights reserved.

An analysis of carbon and radiocarbon profiles across a range ecosystems types

NASA Astrophysics Data System (ADS)

Heckman, K. A.; Gallo, A.; Hatten, J. A.; Swanston, C.; Strahm, B. D.; Sanclements, M.

2016-12-01

Soil carbon stocks have become recognized as increasingly important in the context of climate change and global C cycle modeling. As modelers seek to identify key parameters affecting the size and stability of belowground C stocks, attention has been drawn to the mineral matrix and the soil physiochemical factors influenced by it. Though clay content has often been utilized as a convenient and key explanatory variable for soil C dynamics, its utility has recently come under scrutiny as new paradigms of soil organic matter stabilization have been developed. We utilized soil cores from a range of National Ecological Observatory Network (NEON) experimental plots to examine the influence of mineralogical parameters on soil C stocks and turnover and their relative importance in comparison to climatic variables. Results are presented for a total of 11 NEON sites, spanning Alfisols, Entisols, Mollisols and Spodosols. Soils were sampled by genetic horizon, density separated according to density fractionation: light fractions (particulate organics neither occluded within aggregates nor associated with mineral surfaces), occluded fractions (particulate organics occluded within aggregates), and heavy fractions (organics associated with mineral surfaces). Bulk soils and density fractions were measured for % C and radiocarbon abundance (as a measure of C stability). Carbon and radiocarbon abundances were examined among fractions and in the context of climatic variables (temperature, precipitation, elevation) and soil physiochemical variables (% clay and pH). No direct relationships between temperature and soil C or radiocarbon abundances were found. As a whole, soil radiocarbon abundance in density fractions decreased in the order of light>heavy>occluded, highlighting the importance of both surface sorption and aggregation to the preservation of organics. Radiocarbon concentrations of the heavy fraction (mineral adsorbed) were significantly, though weakly, correlated with pH (r2 = 0.35, p = 0.02), though C concentrations were not. Data suggest an important role for both aggregation and soil chemistry in regulating soil C cycling across a diversity of soil orders. The current presented results serve as a preliminary report on a project spanning 40 NEON sites and a range of physiochemical analyses.

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.

Assessment of catchments' flooding potential: a physically-based analytical tool

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Schirmer, M.

2016-12-01

The assessment of the flooding potential of river catchments is critical in many research and applied fields, ranging from river science and geomorphology to urban planning and the insurance industry. Predicting magnitude and frequency of floods is key to prevent and mitigate the negative effects of high flows, and has therefore long been the focus of hydrologic research. Here, the recurrence intervals of seasonal flow maxima are estimated through a novel physically-based analytic approach, which links the extremal distribution of streamflows to the stochastic dynamics of daily discharge. An analytical expression of the seasonal flood-frequency curve is provided, whose parameters embody climate and landscape attributes of the contributing catchment and can be estimated from daily rainfall and streamflow data. Only one parameter, which expresses catchment saturation prior to rainfall events, needs to be calibrated on the observed maxima. The method has been tested in a set of catchments featuring heterogeneous daily flow regimes. The model is able to reproduce characteristic shapes of flood-frequency curves emerging in erratic and persistent flow regimes and provides good estimates of seasonal flow maxima in different climatic regions. Performances are steady when the magnitude of events with return times longer than the available sample size is estimated. This makes the approach especially valuable for regions affected by data scarcity.

Time to refine key climate policy models

NASA Astrophysics Data System (ADS)

Barron, Alexander R.

2018-05-01

Ambition regarding climate change at the national level is critical but is often calibrated with the projected costs — as estimated by a small suite of energy-economic models. Weaknesses in several key areas in these models will continue to distort policy design unless collectively addressed by a diversity of researchers.

The uncertainty of crop yield projections is reduced by improved temperature response functions

USDA-ARS?s Scientific Manuscript database

Increasing the accuracy of crop productivity estimates is a key Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on cr...

Climate change effects on central New Mexico's land use, transportation system and key natural resources : task 1.1 memo.

DOT National Transportation Integrated Search

2014-12-01

This report summarizes potential climate change effects on the availability of water, land use, transportation infrastructure, and key natural resources in central New Mexico. This work is being done as part of the Interagency Transportation, Land Us...

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

PubMed

Wang, Junpeng; Liu, Xiaotong; Shen, Han-Wei; Lin, Guang

2017-01-01

Due to the uncertain nature of weather prediction, climate simulations are usually performed multiple times with different spatial resolutions. The outputs of simulations are multi-resolution spatial temporal ensembles. Each simulation run uses a unique set of values for multiple convective parameters. Distinct parameter settings from different simulation runs in different resolutions constitute a multi-resolution high-dimensional parameter space. Understanding the correlation between the different convective parameters, and establishing a connection between the parameter settings and the ensemble outputs are crucial to domain scientists. The multi-resolution high-dimensional parameter space, however, presents a unique challenge to the existing correlation visualization techniques. We present Nested Parallel Coordinates Plot (NPCP), a new type of parallel coordinates plots that enables visualization of intra-resolution and inter-resolution parameter correlations. With flexible user control, NPCP integrates superimposition, juxtaposition and explicit encodings in a single view for comparative data visualization and analysis. We develop an integrated visual analytics system to help domain scientists understand the connection between multi-resolution convective parameters and the large spatial temporal ensembles. Our system presents intricate climate ensembles with a comprehensive overview and on-demand geographic details. We demonstrate NPCP, along with the climate ensemble visualization system, based on real-world use-cases from our collaborators in computational and predictive science.

GAIA - A New Approach To Decision Making on Climate Disruption Issues

NASA Astrophysics Data System (ADS)

Paxton, L. J.; Weiss, M.; Schaefer, R. K.; Swartz, W. H.; Nix, M.; Strong, S. B.; Fountain, G. H.; Babin, S. M.; Pikas, C. K.; Parker, C. L.; Global Assimilation of InformationAction

2011-12-01

GAIA - the Global Assimilation of Information for Action program - provides a broadly extensible framework for enabling the development of a deeper understanding of the issues associated with climate disruption. The key notion of GAIA is that the global climate problem is so complex that a "system engineering" approach is needed in order to make it understandable. The key tenet of system engineering is to focus on requirements and to develop a cost-effective process for satisfying those requirements. To demonstrate this approach we focused first on the impact of climate disruption on public health. GAIA is described in some detail on our website (http://gaia.jhuapl.edu). Climate disruption is not just a scientific problem; one of the key issues that our community has is that of translating scientific results into knowledge that can be used to make informed decisions. In order to support decision makers we have to understand their issues and how to communicate with them. In this talk, we describe how we have built a community of interest that combines subject matter experts from diverse communities (public health, climate change, government, public policy, industry, etc) with policy makers and representatives from industry to develop, on a "level playing field", an understanding of each other's points of view and issues. The first application of this technology was the development of a workshop on Climate, Climate Change and Public Health held April 12-14, 2011. This paper describes our approach to going beyond the workshop environment to continue to engage the decision maker's community in a variety of ways that translate abstract scientific data into actionable information. Key ideas we will discuss include the development of social media, simulations of global/national/local environments affected by climate disruption, and visualizations of the monetary and health impacts of choosing not to address mitigation or adaptation to climate disruption.

Generating relevant climate adaptation science tools in concert with local natural resource agencies

NASA Astrophysics Data System (ADS)

Micheli, L.; Flint, L. E.; Veloz, S.; Heller, N. E.

2015-12-01

To create a framework for adapting to climate change, decision makers operating at the urban-wildland interface need to define climate vulnerabilities in the context of site-specific opportunities and constraints relative to water supply, land use suitability, wildfire risks, ecosystem services and quality of life. Pepperwood's TBC3.org is crafting customized climate vulnerability assessments with selected water and natural resource agencies of California's Sonoma, Marin, Napa and Mendocino counties under the auspices of Climate Ready North Bay, a public-private partnership funded by the California Coastal Conservancy. Working directly with managers from the very start of the process to define resource-specific information needs, we are developing high-resolution, spatially-explicit data products to help local governments and agency staff implement informed and effective climate adaptation strategies. Key preliminary findings for the region using the USGS' Basin Characterization Model (at a 270 m spatial resolution) include a unidirectional trend, independent of greater or lesser precipitation, towards increasing climatic water deficits across model scenarios. Therefore a key message is that managers will be facing an increasingly arid environment. Companion models translate the impacts of shifting climate and hydrology on vegetation composition and fire risks. The combination of drought stress on water supplies and native vegetation with an approximate doubling of fire risks may demand new approaches to watershed planning. Working with agencies we are exploring how to build capacity for protection and enhancement of key watershed functions with a focus on groundwater recharge, facilitating greater drought tolerance in forest and rangeland systems, and considering more aggressive approaches to management of fuel loads. Lessons learned about effective engagement include the need for extended in-depth dialog, translation of key climate adaptation questions into deliverable metrics and indicators, and the need to take time to digest and formulate results in terms of adaptive management actions. Agencies also express a benefit in using Climate Ready results to raise public awareness of the resource challenges that may lay ahead.

Theoretical electron scattering amplitudes and spin polarizations. Electron energies 100 to 1500 eV Part II. Be, N, O, Al, Cl, V, Co, Cu, As, Nb, Ag, Sn, Sb, I, and Ta targets

NASA Astrophysics Data System (ADS)

Wildhaber, M. L.; Wikle, C. K.; Anderson, C. J.; Franz, K. J.; Moran, E. H.; Dey, R.

2012-12-01

Recent decades have brought substantive changes in land use and climate across the earth, prompting a need to think of population and community ecology not as a static entity, but as a dynamic process. Increasingly there is evidence of ecological changes due to climate change. Although much of this evidence comes from ground-truth observations of biogeographic data, there is increasing reliance on models that relate climate variables to biological systems. Such models can then be used to explore potential changes to population and community level ecological systems in response to climate scenarios as obtained from global climate models (GCMs). A key issue associated with modeling ecosystem response to climate is GCM downscaling to regional and local ecological/biological response models that can be used in vulnerability and risk assessments of the potential effects of climate change. The need is for an explicit means for scaling results up or down multiple hierarchical levels and an effective assessment of the level of uncertainty surrounding current knowledge, data, and data collection methods with these goals identified as in need of acceleration in the U.S. Climate Change Science Program FY2009 Implementation Priorities. In the end, such work should provide the information needed to develop adaptation and mitigation methodologies to minimize the effects of directional and nonlinear climate change on the Nation's land, water, ecosystems, and biological populations. We are working to develop an approach that includes multi-scale and hierarchical Bayesian modeling of Missouri River sturgeon population dynamics. Statistical linkages are defined to quantify implications of climate on fish populations of the Missouri River ecosystem. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. The model must include linkages between climate and habitat, and between habitat and population. A key advantage of the hierarchical approach used in this study is that it incorporates various sources of observations and includes established scientific knowledge, and associated uncertainties. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. The predictive modeling system being developed will be a powerful tool for evaluating management options for coping with global change consequences and assessing uncertainty of those evaluations. Specifically for the endangered pallid sturgeon (Scaphirhynchus albus), we are already able to assess potential effects of any climate scenario on growth and population size distribution. Future models will incorporate survival and reproduction. Ultimately, these models provide guidance for successful recovery and conservation of the pallid sturgeon. Here we present a basic outline of the approach we are developing and a simple pallid sturgeon example to demonstrate how multiple scales and parameter uncertainty are incorporated.

The Art and Science of Climate Model Tuning

DOE PAGES

Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew; ...

2017-03-31

The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less

The Art and Science of Climate Model Tuning

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

Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew

The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less

Climate Change? A Comparison of Language and Literacy Practices Relating to the Teaching of Science across the Key Stage 2/3 Interface in Two School Clusters

ERIC Educational Resources Information Center

McCullagh, John; Jarman, Ruth

2009-01-01

This paper reports the findings of a study of the literacy perceptions and practices of general primary teachers (Key Stage 2) and post-primary science teachers (Key Stage 3) within two clusters of schools. The study also explores the possible impact on pupils of any difference in the language climate which may accompany them on their journey…

A simple, single-substrate model to interpret intra-annual stable isotope signals in tree-ring cellulose

NASA Astrophysics Data System (ADS)

Ogée, J.; Barbour, M. M.; Wingate, L.; Bert, D.; Bosc, A.; Stievenard, M.; Lambrot, C.; Pierre, M.; Bariac, T.; Dewar, R. C.

2009-04-01

High-resolution intra-annual measurements of the carbon and oxygen stable isotope composition of cellulose in annual tree rings (δ13Ccellulose and δ18Ocellulose, respectively) reveal well-defined seasonal patterns that could contain valuable records of past climate and tree function. Interpreting these signals is nonetheless complex because they not only record the signature of current assimilates, but also depend on carbon allocation dynamics within the trees. Here, we present a simple, single-substrate model for wood growth containing only 12 main parameters. The model is used to interpret an isotopic intra-annual chronology collected in an even-aged maritime pine plantation growing in the South-West of France, where climate, soil and flux variables were also monitored. The empirical δ13Ccellulose and δ18Ocellulose exhibit dynamic seasonal patterns, with clear differences between years and individuals, that are mostly captured by the model. In particular, the amplitude of both signals is reproduced satisfactorily as well as the sharp 18O enrichment at the beginning of 1997 and the less pronounced 13C and 18O depletion observed at the end of the latewood. Our results suggest that the single-substrate hypothesis is a good approximation for tree ring studies on Pinus pinaster, at least for the environmental conditions covered by this study. A sensitivity analysis revealed that, in the early wood, the model was particularly sensitive to the date when cell wall thickening begins (twt). We therefore propose to use the model to reconstruct time series of twt and explore how climate influences this key parameter of xylogenesis.

EcoPAD, an interactive platform for near real-time ecological forecasting by assimilating data into model

NASA Astrophysics Data System (ADS)

MA, S.; Huang, Y.; Stacy, M.; Jiang, J.; Sundi, N.; Ricciuto, D. M.; Hanson, P. J.; Luo, Y.; Saruta, V.

2017-12-01

Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our study presents a smart system - Ecological Platform for Assimilation of Data (EcoPAD) - which streamlines web request-response, data management, model execution, result storage and visualization. EcoPAD allows users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, (v) conduct ecological forecasting, and (vi) detect ecosystem acclimation to climate change. One of the key innovations of the web-based EcoPAD is the automated near- or real-time forecasting of ecosystem dynamics with uncertainty fully quantified. The user friendly webpage enables non-modelers to explore their data for simulation and data assimilation. As a case study, we applied EcoPAD to the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment project in the northern peatland, assimilated multiple data streams into a process based ecosystem model, enhanced timely feedback between modelers and experimenters, ultimately improved ecosystem forecasting and made better use of current knowledge. Built in a framework with flexible API, EcoPAD is easily portable and will benefit scientific communities, policy makers as well as the general public.

Slow science: the value of long ocean biogeochemistry records.

PubMed

Henson, Stephanie A

2014-09-28

Sustained observations (SOs) have provided invaluable information on the ocean's biology and biogeochemistry for over 50 years. They continue to play a vital role in elucidating the functioning of the marine ecosystem, particularly in the light of ongoing climate change. Repeated, consistent observations have provided the opportunity to resolve temporal and/or spatial variability in ocean biogeochemistry, which has driven exploration of the factors controlling biological parameters and processes. Here, I highlight some of the key breakthroughs in biological oceanography that have been enabled by SOs, which include areas such as trophic dynamics, understanding variability, improved biogeochemical models and the role of ocean biology in the global carbon cycle. In the near future, SOs are poised to make progress on several fronts, including detecting climate change effects on ocean biogeochemistry, high-resolution observations of physical-biological interactions and greater observational capability in both the mesopelagic zone and harsh environments, such as the Arctic. We are now entering a new era for biological SOs, one in which our motivations have evolved from the need to acquire basic understanding of the ocean's state and variability, to a need to understand ocean biogeochemistry in the context of increasing pressure in the form of climate change, overfishing and eutrophication.

Global warming and South Indian monsoon rainfall-lessons from the Mid-Miocene.

PubMed

Reuter, Markus; Kern, Andrea K; Harzhauser, Mathias; Kroh, Andreas; Piller, Werner E

2013-04-01

Precipitation over India is driven by the Indian monsoon. Although changes in this atmospheric circulation are caused by the differential seasonal diabatic heating of Asia and the Indo-Pacific Ocean, it is so far unknown how global warming influences the monsoon rainfalls regionally. Herein, we present a Miocene pollen flora as the first direct proxy for monsoon over southern India during the Middle Miocene Climate Optimum. To identify climatic key parameters, such as mean annual temperature, warmest month temperature, coldest month temperature, mean annual precipitation, mean precipitation during the driest month, mean precipitation during the wettest month and mean precipitation during the warmest month the Coexistence Approach is applied. Irrespective of a ~ 3-4 °C higher global temperature during the Middle Miocene Climate Optimum, the results indicate a modern-like monsoonal precipitation pattern contrasting marine proxies which point to a strong decline of Indian monsoon in the Himalaya at this time. Therefore, the strength of monsoon rainfall in tropical India appears neither to be related to global warming nor to be linked with the atmospheric conditions over the Tibetan Plateau. For the future it implies that increased global warming does not necessarily entail changes in the South Indian monsoon rainfall.

Environmental Drivers of West Nile Fever Epidemiology in Europe and Western Asia—A Review

PubMed Central

Paz, Shlomit; Semenza, Jan C.

2013-01-01

Abiotic and biotic conditions are both important determinants of West Nile Fever (WNF) epidemiology. Ambient temperature plays an important role in the growth rates of vector populations, the interval between blood meals, viral replication rates and transmission of West Nile Virus (WNV). The contribution of precipitation is more complex and less well understood. In this paper we discuss impacts of climatic parameters (temperature, relative humidity, precipitation) and other environmental drivers (such as bird migration, land use) on WNV transmission in Europe. WNV recently became established in southeastern Europe, with a large outbreak in the summer of 2010 and recurrent outbreaks in 2011 and 2012. Abundant competent mosquito vectors, bridge vectors, infected (viremic) migrating and local (amplifying) birds are all important characteristics of WNV transmission. In addition, certain key climatic factors, such as increased ambient temperatures, and by extension climate change, may also favor WNF transmission, and they should be taken into account when evaluating the risk of disease spread in the coming years. Monitoring epidemic precursors of WNF, such as significant temperature deviations in high risk areas, could be used to trigger vector control programs and public education campaigns. PMID:23939389

Ocean acidification ameliorates harmful effects of warming in primary consumer.

PubMed

Pedersen, Sindre Andre; Hanssen, Anja Elise

2018-01-01

Climate change-induced warming and ocean acidification are considered two imminent threats to marine biodiversity and current ecosystem structures. Here, we have for the first time examined an animal's response to a complete life cycle of exposure to co-occurring warming (+3°C) and ocean acidification (+1,600 μatm CO 2 ), using the key subarctic planktonic copepod, Calanus finmarchicus , as a model species. The animals were generally negatively affected by warming, which significantly reduced the females' energy status and reproductive parameters (respectively, 95% and 69%-87% vs. control). Unexpectedly, simultaneous acidification partially offset the negative effect of warming in an antagonistic manner, significantly improving reproductive parameters and hatching success (233%-340% improvement vs. single warming exposure). The results provide proof of concept that ocean acidification may partially offset negative effects caused by warming in some species. Possible explanations and ecological implications for the observed antagonistic effect are discussed.

Parametric Sensitivity Analysis for the Asian Summer Monsoon Precipitation Simulation in the Beijing Climate Center AGCM Version 2.1

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

Yang, Ben; Zhang, Yaocun; Qian, Yun

In this study, we apply an efficient sampling approach and conduct a large number of simulations to explore the sensitivity of the simulated Asian summer monsoon (ASM) precipitation, including the climatological state and interannual variability, to eight parameters related to the cloud and precipitation processes in the Beijing Climate Center AGCM version 2.1 (BCC_AGCM2.1). Our results show that BCC_AGCM2.1 has large biases in simulating the ASM precipitation. The precipitation efficiency and evaporation coefficient for deep convection are the most sensitive parameters in simulating the ASM precipitation. With optimal parameter values, the simulated precipitation climatology could be remarkably improved, e.g. increasedmore » precipitation over the equator Indian Ocean, suppressed precipitation over the Philippine Sea, and more realistic Meiyu distribution over Eastern China. The ASM precipitation interannual variability is further analyzed, with a focus on the ENSO impacts. It shows the simulations with better ASM precipitation climatology can also produce more realistic precipitation anomalies during El Niño decaying summer. In the low-skill experiments for precipitation climatology, the ENSO-induced precipitation anomalies are most significant over continents (vs. over ocean in observation) in the South Asian monsoon region. More realistic results are derived from the higher-skill experiments with stronger anomalies over the Indian Ocean and weaker anomalies over India and the western Pacific, favoring more evident easterly anomalies forced by the tropical Indian Ocean warming and stronger Indian Ocean-western Pacific tele-connection as observed. Our model results reveal a strong connection between the simulated ASM precipitation climatological state and interannual variability in BCC_AGCM2.1 when key parameters are perturbed.« less

Extinction vulnerability of coral reef fishes.

PubMed

Graham, Nicholas A J; Chabanet, Pascale; Evans, Richard D; Jennings, Simon; Letourneur, Yves; Aaron Macneil, M; McClanahan, Tim R; Ohman, Marcus C; Polunin, Nicholas V C; Wilson, Shaun K

2011-04-01

With rapidly increasing rates of contemporary extinction, predicting extinction vulnerability and identifying how multiple stressors drive non-random species loss have become key challenges in ecology. These assessments are crucial for avoiding the loss of key functional groups that sustain ecosystem processes and services. We developed a novel predictive framework of species extinction vulnerability and applied it to coral reef fishes. Although relatively few coral reef fishes are at risk of global extinction from climate disturbances, a negative convex relationship between fish species locally vulnerable to climate change vs. fisheries exploitation indicates that the entire community is vulnerable on the many reefs where both stressors co-occur. Fishes involved in maintaining key ecosystem functions are more at risk from fishing than climate disturbances. This finding is encouraging as local and regional commitment to fisheries management action can maintain reef ecosystem functions pending progress towards the more complex global problem of stabilizing the climate. © 2011 Blackwell Publishing Ltd/CNRS.

Extinction vulnerability of coral reef fishes

PubMed Central

Graham, Nicholas A J; Chabanet, Pascale; Evans, Richard D; Jennings, Simon; Letourneur, Yves; Aaron MacNeil, M; McClanahan, Tim R; Öhman, Marcus C; Polunin, Nicholas V C; Wilson, Shaun K

2011-01-01

With rapidly increasing rates of contemporary extinction, predicting extinction vulnerability and identifying how multiple stressors drive non-random species loss have become key challenges in ecology. These assessments are crucial for avoiding the loss of key functional groups that sustain ecosystem processes and services. We developed a novel predictive framework of species extinction vulnerability and applied it to coral reef fishes. Although relatively few coral reef fishes are at risk of global extinction from climate disturbances, a negative convex relationship between fish species locally vulnerable to climate change vs. fisheries exploitation indicates that the entire community is vulnerable on the many reefs where both stressors co-occur. Fishes involved in maintaining key ecosystem functions are more at risk from fishing than climate disturbances. This finding is encouraging as local and regional commitment to fisheries management action can maintain reef ecosystem functions pending progress towards the more complex global problem of stabilizing the climate. PMID:21320260

Vulnerability of southern plains agriculture to climate change

USDA-ARS?s Scientific Manuscript database

Climate is a key driver for all ecological and economic systems; therefore, climate change introduces additional uncertainty and vulnerability into these systems. Agriculture represents a major land use that is critical to the survival of human societies and it is highly vulnerable to climate. Clima...

Health impacts of climate change and health and social inequalities in the UK.

PubMed

Paavola, Jouni

2017-12-05

This article examines how social and health inequalities shape the health impacts of climate change in the UK, and what the implications are for climate change adaptation and health care provision. The evidence generated by the other articles of the special issue were interpreted using social justice reasoning in light of additional literature, to draw out the key implications of health and social inequalities for health outcomes of climate change. Exposure to heat and cold, air pollution, pollen, food safety risks, disruptions to access to and functioning of health services and facilities, emerging infections and flooding are examined as the key impacts of climate change influencing health outcomes. Age, pre-existing medical conditions and social deprivation are found to be the key (but not only) factors that make people vulnerable and to experience more adverse health outcomes related to climate change impacts. In the future, climate change, aging population and decreasing public spending on health and social care may aggravate inequality of health outcomes related to climate change. Health education and public preparedness measures that take into account differential exposure, sensitivity and adaptive capacity of different groups help address health and social inequalities to do with climate change. Adaptation strategies based on individual preparedness, action and behaviour change may aggravate health and social inequalities due to their selective uptake, unless they are coupled with broad public information campaigns and financial support for undertaking adaptive measures.

Assessing adaptation to the health risks of climate change: what guidance can existing frameworks provide?

PubMed

Füssel, Hans-Martin

2008-02-01

Climate change adaptation assessments aim at assisting policy-makers in reducing the health risks associated with climate change and variability. This paper identifies key characteristics of the climate-health relationship and of the adaptation decision problem that require consideration in climate change adaptation assessments. It then analyzes whether these characteristics are appropriately considered in existing guidelines for climate impact and adaptation assessment and in pertinent conceptual models from environmental epidemiology. The review finds three assessment guidelines based on a generalized risk management framework to be most useful for guiding adaptation assessments of human health. Since none of them adequately addresses all key challenges of the adaptation decision problem, actual adaptation assessments need to combine elements from different guidelines. Established conceptual models from environmental epidemiology are found to be of limited relevance for assessing and planning adaptation to climate change since the prevailing toxicological model of environmental health is not applicable to many climate-sensitive health risks.

Sensitivity of ring growth and carbon allocation to climatic variation vary within ponderosa pine trees.

PubMed

Kerhoulas, Lucy P; Kane, Jeffrey M

2012-01-01

Most dendrochronological studies focus on cores sampled from standard positions (main stem, breast height), yet vertical gradients in hydraulic constraints and priorities for carbon allocation may contribute to different growth sensitivities with position. Using cores taken from five positions (coarse roots, breast height, base of live crown, mid-crown branch and treetop), we investigated how radial growth sensitivity to climate over the period of 1895-2008 varies by position within 36 large ponderosa pines (Pinus ponderosa Dougl.) in northern Arizona. The climate parameters investigated were Palmer Drought Severity Index, water year and monsoon precipitation, maximum annual temperature, minimum annual temperature and average annual temperature. For each study tree, we generated Pearson correlation coefficients between ring width indices from each position and six climate parameters. We also investigated whether the number of missing rings differed among positions and bole heights. We found that tree density did not significantly influence climatic sensitivity to any of the climate parameters investigated at any of the sample positions. Results from three types of analyses suggest that climatic sensitivity of tree growth varied with position height: (i) correlations of radial growth and climate variables consistently increased with height; (ii) model strength based on Akaike's information criterion increased with height, where treetop growth consistently had the highest sensitivity and coarse roots the lowest sensitivity to each climatic parameter; and (iii) the correlation between bole ring width indices decreased with distance between positions. We speculate that increased sensitivity to climate at higher positions is related to hydraulic limitation because higher positions experience greater xylem tensions due to gravitational effects that render these positions more sensitive to climatic stresses. The low sensitivity of root growth to all climatic variables measured suggests that tree carbon allocation to coarse roots is independent of annual climate variability. The greater number of missing rings in branches highlights the fact that canopy development is a low priority for carbon allocation during poor growing conditions.

Representation of micrometeorological and physiological parameters with numerical models influencing the vineyard ecosystem: the case of Piemonte (Italy).

NASA Astrophysics Data System (ADS)

Andreoli, Valentina; Cassardo, Claudio; Cavalletto, Silvia; Ferrarese, Silvia; Guidoni, Silvia; Mania, Elena; Spanna, Federico

2017-04-01

Grapevine represents worldwide key economic activities, with Europe representing the largest vineyard area in the world (38%). This is also true both for Italy and for its Piemonte region, in which famous and renowned wines (such as Barolo and Barbaresco) are produced. Grapevine productivity depends on several factors including soil fertility, management practices, climate and meteorology. In particular, concerning the latter, there is a need for a reliable assessment of the effects of a changing climate on its yield and quality. However, in this respect, it is essential to understand how and how much climate and meteorology affect grape productivity and quality, since only few studies related to few regions in the world have been produced. In this context, crop models are essential tools for investigating the effects of climate change on crop development and growth via the integration of existing knowledge of crop physiology relating to changing environmental conditions. Nevertheless, crop models were developed and applied mainly for studying the responses to climate change of annual crops (e.g. cereals); whilst appropriate crop models and application of these are still limited for tree crops such as grapevine. The rationale of the study, included in the MACSUR2 JPI FACCE project, is to use the third generation land surface model UTOPIA (University of TOrino model of land Process Interaction with Atmosphere) [1], in order to evaluate all components of hydrological and energy budget, as well as soil and canopy parameters, on a specific subset of land use, the vineyards. A preliminary step of this work has been to compare the datasets resulted from the calculations made by the UTOPIA and some experimental datasets acquired within vineyards by our team in the past experiments. The reason for such control is to ensure that UTOPIA outputs could be considered as sufficiently representative of the climatology of vineyards. Thus, some Piedmontese vineyards were selected, each one characterized by same climatic but different microclimatic conditions, in which measurements of a wide number of variables were performed in the vegetative seasons (such as in the experiment MASGRAPE). Subsequently, in this study, the results of additional simulations performed using the freely available global database GLDAS (Global Land Data Assimilation System) were compared with those of the simulations driven by observations, in order to check if the model was still able to reproduce the microclimatic characteristics of the vineyards. This preliminary part of the study gave satisfactory results; thus, we could pass to the phase two of the project. In this phase, using GLDAS database, long term simulations will be carried out with the UTOPIA in order to have output data available on a period of climatic interest (30 years or more). This database could be used in order to perform climatic statistics and assess possible trends in some parameters, eventually to be correlated with grape production. In the talk, the preliminary aspects of this work will be illustrated.

A new approach to modeling aerosol effects on East Asian climate: Parametric uncertainties associated with emissions, cloud microphysics, and their interactions: AEROSOL EFFECTS ON EAST ASIAN CLIMATE

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

Yan, Huiping; Qian, Yun; Zhao, Chun

2015-09-09

In this study, we adopt a parametric sensitivity analysis framework that integrates the quasi-Monte Carlo parameter sampling approach and a surrogate model to examine aerosol effects on the East Asian Monsoon climate simulated in the Community Atmosphere Model (CAM5). A total number of 256 CAM5 simulations are conducted to quantify the model responses to the uncertain parameters associated with cloud microphysics parameterizations and aerosol (e.g., sulfate, black carbon (BC), and dust) emission factors and their interactions. Results show that the interaction terms among parameters are important for quantifying the sensitivity of fields of interest, especially precipitation, to the parameters. Themore » relative importance of cloud-microphysics parameters and emission factors (strength) depends on evaluation metrics or the model fields we focused on, and the presence of uncertainty in cloud microphysics imposes an additional challenge in quantifying the impact of aerosols on cloud and climate. Due to their different optical and microphysical properties and spatial distributions, sulfate, BC, and dust aerosols have very different impacts on East Asian Monsoon through aerosol-cloud-radiation interactions. The climatic effects of aerosol do not always have a monotonic response to the change of emission factors. The spatial patterns of both sign and magnitude of aerosol-induced changes in radiative fluxes, cloud, and precipitation could be different, depending on the aerosol types, when parameters are sampled in different ranges of values. We also identify the different cloud microphysical parameters that show the most significant impact on climatic effect induced by sulfate, BC and dust, respectively, in East Asia.« less

Satellite Remote Sensing is Key to Water Cycle Integrator

NASA Astrophysics Data System (ADS)

Koike, T.

2016-12-01

To promote effective multi-sectoral, interdisciplinary collaboration based on coordinated and integrated efforts, the Global Earth Observation System of Systems (GEOSS) is now developing a "GEOSS Water Cycle Integrator (WCI)", which integrates "Earth observations", "modeling", "data and information", "management systems" and "education systems". GEOSS/WCI sets up "work benches" by which partners can share data, information and applications in an interoperable way, exchange knowledge and experiences, deepen mutual understanding and work together effectively to ultimately respond to issues of both mitigation and adaptation. (A work bench is a virtual geographical or phenomenological space where experts and managers collaborate to use information to address a problem within that space). GEOSS/WCI enhances the coordination of efforts to strengthen individual, institutional and infrastructure capacities, especially for effective interdisciplinary coordination and integration. GEOSS/WCI archives various satellite data to provide various hydrological information such as cloud, rainfall, soil moisture, or land-surface snow. These satellite products were validated using land observation in-situ data. Water cycle models can be developed by coupling in-situ and satellite data. River flows and other hydrological parameters can be simulated and validated by in-situ data. Model outputs from weather-prediction, seasonal-prediction, and climate-prediction models are archived. Some of these model outputs are archived on an online basis, but other models, e.g., climate-prediction models are archived on an offline basis. After models are evaluated and biases corrected, the outputs can be used as inputs into the hydrological models for predicting the hydrological parameters. Additionally, we have already developed a data-assimilation system by combining satellite data and the models. This system can improve our capability to predict hydrological phenomena. The WCI can provide better predictions of the hydrological parameters for integrated water resources management (IWRM) and also assess the impact of climate change and calculate adaptation needs.

Enhanced light absorption by mixed source black and brown carbon particles in UK winter

PubMed Central

Liu, Shang; Aiken, Allison C.; Gorkowski, Kyle; Dubey, Manvendra K.; Cappa, Christopher D.; Williams, Leah R.; Herndon, Scott C.; Massoli, Paola; Fortner, Edward C.; Chhabra, Puneet S.; Brooks, William A.; Onasch, Timothy B.; Jayne, John T.; Worsnop, Douglas R.; China, Swarup; Sharma, Noopur; Mazzoleni, Claudio; Xu, Lu; Ng, Nga L.; Liu, Dantong; Allan, James D.; Lee, James D.; Fleming, Zoë L.; Mohr, Claudia; Zotter, Peter; Szidat, Sönke; Prévôt, André S. H.

2015-01-01

Black carbon (BC) and light-absorbing organic carbon (brown carbon, BrC) play key roles in warming the atmosphere, but the magnitude of their effects remains highly uncertain. Theoretical modelling and laboratory experiments demonstrate that coatings on BC can enhance BC's light absorption, therefore many climate models simply assume enhanced BC absorption by a factor of ∼1.5. However, recent field observations show negligible absorption enhancement, implying models may overestimate BC's warming. Here we report direct evidence of substantial field-measured BC absorption enhancement, with the magnitude strongly depending on BC coating amount. Increases in BC coating result from a combination of changing sources and photochemical aging processes. When the influence of BrC is accounted for, observationally constrained model calculations of the BC absorption enhancement can be reconciled with the observations. We conclude that the influence of coatings on BC absorption should be treated as a source and regionally specific parameter in climate models. PMID:26419204

Abrupt warming of the Red Sea

NASA Astrophysics Data System (ADS)

Raitsos, D. E.; Hoteit, I.; Prihartato, P. K.; Chronis, T.; Triantafyllou, G.; Abualnaja, Y.

2011-07-01

Coral reef ecosystems, often referred to as “marine rainforests,” concentrate the most diverse life in the oceans. Red Sea reef dwellers are adapted in a very warm environment, fact that makes them vulnerable to further and rapid warming. The detection and understanding of abrupt temperature changes is an important task, as ecosystems have more chances to adapt in a slowly rather than in a rapid changing environment. Using satellite derived sea surface and ground based air temperatures, it is shown that the Red Sea is going through an intense warming initiated in the mid-90s, with evidence for an abrupt increase after 1994 (0.7°C difference pre and post the shift). The air temperature is found to be a key parameter that influences the Red Sea marine temperature. The comparisons with Northern Hemisphere temperatures revealed that the observed warming is part of global climate change trends. The hitherto results also raise additional questions regarding other broader climatic impacts over the area.

Martian atmospheric O3 retrieval development for the NOMAD-UVIS spectrometer

NASA Astrophysics Data System (ADS)

Hewson, W.; Mason, J. P.; Leese, M.; Hathi, B.; Holmes, J.; Lewis, S. R.; Iriwin, P. G. J.; Patel, M. R.

2017-09-01

The composition of atmospheric trace gases and aerosols is a highly variable and poorly constrained component of the martian atmosphere, and by affecting martian climate and UV surface dose, represents a key parameter in the assessment of suitability for martian habitability. The ExoMars Trace Gas Orbiter (TGO) carries the Open University (OU) designed Ultraviolet and VIsible Spectrometer (UVIS) instrument as part of the Belgian-led Nadir and Occultation for MArs Discovery (NOMAD) spectrometer suite. NOMAD will begin transmitting science observations of martian surface and atmosphere back-scattered UltraViolet (UV) and visible radiation in Spring 2018, which will be processed to derive spatially and temporally averaged atmospheric trace gas and aerosol concentrations, intended to provide a better understanding of martian atmospheric photo-chemistry and dynamics, and will also improve models of martian atmospheric chemistry, climate and habitability. Work presented here illustrates initial development and testing of the OU's new retrieval algorithm for determining O3 and aerosol concentrations from the UVIS instrument.

Enhanced light absorption by mixed source black and brown carbon particles in UK winter

DOE PAGES

Liu, Shang; Aiken, Allison C.; Gorkowski, Kyle; ...

2015-09-30

We report that black carbon (BC) and light-absorbing organic carbon (brown carbon, BrC) play key roles in warming the atmosphere, but the magnitude of their effects remains highly uncertain. Theoretical modelling and laboratory experiments demonstrate that coatings on BC can enhance BC’s light absorption, therefore many climate models simply assume enhanced BC absorption by a factor of ~1.5. However, recent field observations show negligible absorption enhancement, implying models may overestimate BC’s warming. Here we report direct evidence of substantial field-measured BC absorption enhancement, with the magnitude strongly depending on BC coating amount. Increases in BC coating result from a combinationmore » of changing sources and photochemical aging processes. When the influence of BrC is accounted for, observationally constrained model calculations of the BC absorption enhancement can be reconciled with the observations. In conclusion, we find that the influence of coatings on BC absorption should be treated as a source and regionally specific parameter in climate models.« less

Convection and the Soil-Moisture Precipitation Feedback

NASA Astrophysics Data System (ADS)

Schar, C.; Froidevaux, P.; Keller, M.; Schlemmer, L.; Langhans, W.; Schmidli, J.

2014-12-01

The soil moisture - precipitation (SMP) feedback is of key importance for climate and climate change. A positive SMP feedback tends to amplify the hydrological response to external forcings (and thereby fosters precipitation and drought extremes), while a negative SMP feedback tends to moderate the influence of external forcings (and thereby stabilizes the hydrological cycle). The sign of the SMP feedback is poorly constrained by the current literature. Theoretical, modeling and observational studies partly disagree, and have suggested both negative and positive feedback loops. Can wet soil anomalies indeed result in either an increase or a decrease of precipitation (positive or negative SMP feedback, respectively)? Here we investigate the local SMP feedback using real-case and idealized convection-resolving simulations. An idealized simulation strategy is developed, which is able to replicate both signs of the feedback loop, depending on the environmental parameters. The mechanism relies on horizontal soil moisture variations, which may develop and intensify spontaneously. The positive expression of the feedback is associated with the initiation of convection over dry soil patches, but the convective cells then propagate over wet patches, where they strengthen and preferentially precipitate. The negative feedback may occur when the wind profile is too weak to support the propagation of convective features from dry to wet areas. Precipitation is then generally weaker and falls preferentially over dry patches. The results highlight the role of the mid-tropospheric flow in determining the sign of the feedback. A key element of the positive feedback is the exploitation of both low convective inhibition (CIN) over dry patches (for the initiation of convection), and high CAPE over wet patches (for the generation of precipitation). The results of this study will also be discussed in relation to climate change scenarios that exhibit large biases in surface temperature and interannual variability over mid-latitude summer climates, both over Europe and North America. It is argued that parameterized convection may contribute towards such biases by overemphasizing a positive SMP feedback.

Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

NASA Astrophysics Data System (ADS)

Xiong, Wei; Skalský, Rastislav; Porter, Cheryl H.; Balkovič, Juraj; Jones, James W.; Yang, Di

2016-09-01

Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

School Climate Improvement Action Guide for Working with Families. School Climate Improvement Resource Package

ERIC Educational Resources Information Center

National Center on Safe Supportive Learning Environments, 2017

2017-01-01

Improving school climate takes time and commitment from a variety of people in a variety of roles. This document outlines how family members--including guardians of students--can support school climate improvements. Key action steps are provided for the following strategies: (1) Participate in planning for school climate improvements; (2) Engage…

Reconstructed Historical Land Cover and Biophysical Parameters for Studies of Land-Atmosphere Interactions within the Eastern United States

NASA Technical Reports Server (NTRS)

Steyaert, Louis T.; Knox, Robert G.

2007-01-01

The local environment where we live within the Earth's biosphere is often taken for granted. This environment can vary depending on whether the land cover is a forest, grassland, wetland, water body, bare soil, pastureland, agricultural field, village, residential suburb, or an urban complex with concrete, asphalt, and large buildings. In general, the type and characteristics of land cover influence surface temperatures, sunlight exposure and duration, relative humidity, wind speed and direction, soil moisture amount, plant life, birds, and other wildlife in our backyards. The physical and biological properties (biophysical characteristics) of land cover help to determine our surface environment because they directly affect surface radiation, heat, and soil moisture processes, and also feedback to regional weather and climate. Depending on the spatial scale and land use intensity, land cover changes can have profound impacts on our local and regional environment. Over the past 350 years, the eastern half of the United States, an area extending from the grassland prairies of the Great Plains to the Gulf and Atlantic coasts, has experienced extensive land cover and land use changes that began with land clearing in the 1600s, led to extensive deforestation and intensive land use practices by 1920, and then evolved to the present-day landscape. Determining the consequences of such land cover changes on regional and global climate is a major research issue. Such research requires detailed historical land cover data and modeling experiments simulating historical climates. Given the need to understand the effects of historical land cover changes in the eastern United States, some questions include: - What were the most important land cover transformations and how did they alter biophysical characteristics of the land cover at key points in time since the mid-1600s? - How have land cover and land use changes over the past 350 years affected the land surface environment including surface weather, hydrologic, and climatic variability? - How do the potential effects of regional human-induced land cover change on the environment compare to similar changes that are caused by the natural variations of the Earth's climate system? To help answer these questions, we reconstructed a fractional land cover and biophysical parameter dataset for the eastern United States at 1650, 1850, 1920, and 1992 time-slices. Each land cover fraction is associated with a biophysical parameter class, a suite of parameters defining the biophysical characteristics of that kind of land cover. This new dataset is designed for use in computer models of land-atmosphere interactions, to understand and quantify the effects of historical land cover changes on the water, energy, and carbon cycles

Analysis of agro-climatic parameters and their influence on maize production in South Africa

NASA Astrophysics Data System (ADS)

Adisa, Omolola M.; Botai, Christina M.; Botai, Joel O.; Hassen, Abubeker; Darkey, Daniel; Tesfamariam, Eyob; Adisa, Alex F.; Adeola, Abiodun M.; Ncongwane, Katlego P.

2017-11-01

This study analyzed the variability of the agro-climatic parameters that impact maize production across different seasons in South Africa. To achieve this, four agro-climatic variables (precipitation, potential evapotranspiration, minimum, and maximum temperatures) were considered for the period spanning 1986-2015, covering the North West, Free State, Mpumalanga, and KwaZulu-Natal (KZN) provinces. Results illustrate that there is a negative trend in precipitation for North West and Free State provinces and positive trend in maximum temperature for all the provinces over the study period. Furthermore, the results showed that among other agro-climatic parameters, minimum temperature had the most influence on maize production in North West, potential evapotranspiration (combination of the agro-climatic parameters), minimum and maximum temperature influenced maize production in KZN while maximum temperature influenced maize production in Mpumalanga and Free State. In general, the agro-climatic parameters were found to contribute 7.79, 21.85, 32.52, and 44.39% to variation in maize production during the study period in North West, Free State, Mpumalanga, and KZN, respectively. The variation in maize production among the provinces under investigation could most likely attribute to the variation in the size of the cultivated land among other factors including soil type and land tenure system. There were also difference in yield per hectare between the provinces; KZN and Mpumalanga being located in the humid subtropical areas of South Africa had the highest yield per hectare 5.61 and 4.99 tons, respectively, while Free State and North West which are in the semi-arid region had the lowest yield per hectare 3.86 and 3.03 tons, respectively. Understanding the nature and interaction of the dominant agro-climatic parameters discussed in the present study as well as their impact on maize production will help farmers and agricultural policy makers to understand how climate change exerts its influence on maize production within the study area so as to better adapt to the major climate element that either increases or decreases maize production in their respective provinces.

Disentangling synergistic climate drivers on the evolution of two species of planktonic foraminifera on regional and global scales

NASA Astrophysics Data System (ADS)

Brombacher, A.; Wilson, P. A.; Bailey, I.; Ezard, T. H. G.

2016-02-01

Evolution is driven by a combination of biotic and abiotic factors. When quantifying the effects of abiotic drivers, evolutionary change is generally described as a response to a single environmental parameter assumed to represent global climate. However, climate is a complex system of many interacting factors and characterized by high regional variability. Therefore, to understand the role of climate in evolutionary change, we need to consider multiple environmental parameters, across local, regional and global scales, as well as their interactions. The deep-sea microfossil record is sufficiently complete that sufficiently continuous multivariate climatic and multivariate trait data can be obtained from the same samples. Here we present morphological records of the planktonic foraminifera species Globoconella puncticulata and Truncorotalia crassaformis over a 500,000-year interval directly preceding the extinction of G. puncticulata (2.41 Ma). Material was collected from five North Atlantic sites (ODP Sites 659 [18° N], 925 [3° N] and 981 [55° N], IODP Site U1313 [41° N] and DSDP Site 606 [37° N]). Test size and shape of over 35,000 individuals were measured and compared to site-specific records of sea surface temperature, primary productivity and marine aeolian dust deposition, as well as to global records of ice volume, ocean circulation and atmospheric CO2, and all two-way interactions. Morphological parameters respond weakly to individual climate parameters. Once interactions among all studied climate parameters were incorporated, abiotic change explained around 35% of the evolutionary variance. Observed covariances between environmental parameters vary strongly with glacial-interglacial cyclicity, implying that the relationships among climate variables and their relative influences on evolutionary change varied through time. This time dependence cautions against unfettered use of dimension reduction techniques, such as principal components analysis, to extract a single, supposedly dominant, proxy. Furthermore species' responses differed between geographic locations, impressing the need to test how interactions among multiple climate variables at different regional settings shape the biotic microevolutionary response to local and global abiotic change.

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-08-01

Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Assessment of Climate Impact Changes on Forest Vegetation Dynamics by Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Zoran, Maria

Climate variability represents the ensemble of net radiation, precipitation, wind and temper-ature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Forest vegetation phenology constitutes an efficient bio-indicator of climate and anthropogenic changes impacts and a key parameter for understanding and modelling vegetation-climate in-teractions. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vege-tation Index (NDVIs), which requires NDVI time-series with good time resolution, over homo-geneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2008 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and to-pography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Identifying data gaps and prioritizing restoration strategies for Fremont cottonwood using linked geomorphic and population models

NASA Astrophysics Data System (ADS)

Harper, E. B.; Stella, J. C.; Fremier, A. K.

2009-12-01

Fremont cottonwood (Populus fremontii) is an important component of semi-arid riparian ecosystems throughout western North America, but its populations are in decline due to flow regulation. Achieving a balance between human resource needs and riparian ecosystem function requires a mechanistic understanding of the multiple geomorphic and biological factors affecting tree recruitment and survival, including the timing and magnitude of river flows, and the concomitant influence on suitable habitat creation and mortality from scour and sedimentation burial. Despite a great deal of empirical research on some components of the system, such as factors affecting cottonwood recruitment, other key components are less studied. Yet understanding the relative influence of the full suite of physical and life-history drivers is critical to modeling whole-population dynamics under changing environmental conditions. We addressed these issues for the Fremont cottonwood population along the Sacramento River, CA using a sensitivity analysis approach to quantify uncertainty in parameters on the outcomes of a patch-based, dynamic population model. Using a broad range of plausible values for 15 model parameters that represent key physical, biological and climatic components of the ecosystem, we ran 1,000 population simulations that consisted of a subset of 14.3 million possible combinations of parameter estimates to predict the frequency of patch colonization and total forest habitat predicted to occur under current hydrologic conditions after 175 years. Results indicate that Fremont cottonwood populations are highly sensitive to the interactions among flow regime, sedimentation rate and the depth of the capillary fringe (Fig. 1). Estimates of long-term floodplain sedimentation rate would substantially improve model accuracy. Spatial variation in sediment texture was also important to the extent that it determines the depth of the capillary fringe, which regulates the availability of water for germination and adult tree growth. Our sensitivity analyses suggest that models of future scenarios should incorporate regional climate change projections because changes in temperature and the timing and volume of precipitation affects sensitive aspects of the system, including the timing of seed release and spring snowmelt runoff. Figure 1. The relative effects on model predictions of uncertainty around each parameter included in the patch-based population model for Fremont cottonwood.

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.

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

DOE PAGES

Bennett, Katrina Eleanor; Urrego Blanco, Jorge Rolando; Jonko, Alexandra; ...

2017-11-20

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model.more » Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.« less

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

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

Bennett, Katrina Eleanor; Urrego Blanco, Jorge Rolando; Jonko, Alexandra

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model.more » Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.« less

Algorithm of dynamic regulation of a system of duct, for a high accuracy climatic system

NASA Astrophysics Data System (ADS)

Arbatskiy, A. A.; Afonina, G. N.; Glazov, V. S.

2017-11-01

Currently, major part of climatic system, are stationary in projected mode only. At the same time, many modern industrial sites, require constant or periodical changes in technological process. That is 80% of the time, the industrial site is not require ventilation system in projected mode and high precision of climatic parameters must maintain. While that not constantly is in use for climatic systems, which use in parallel for different rooms, we will be have a problem for balance of duct system. For this problem, was created the algorithm for quantity regulation, with minimal changes. Dynamic duct system: Developed of parallel control system of air balance, with high precision of climatic parameters. The Algorithm provide a permanent pressure in main duct, in different a flow of air. Therefore, the ending devises air flow have only one parameter for regulation - flaps open area. Precision of regulation increase and the climatic system provide high precision for temperature and humidity (0,5C for temperature, 5% for relative humidity). Result: The research has been made in CFD-system - PHOENICS. Results for velocity of air in duct, for pressure of air in duct for different operation mode, has been obtained. Equation for air valves positions, with different parameters for climate in room’s, has been obtained. Energy saving potential for dynamic duct system, for different types of a rooms, has been calculated.

The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment

EPA Science Inventory

This assessment strengthens and expands our understanding of climate-related health impacts by providing a more definitive description of climate-related health burdens in the United States. It builds on the 2014 USGCRP National Climate Assessment and reviews and synthesizes key ...

Aligning climate policy with finance ministers' G20 agenda

NASA Astrophysics Data System (ADS)

Edenhofer, Ottmar; Knopf, Brigitte; Bak, Céline; Bhattacharya, Amar

2017-07-01

There is no longer a choice between climate policy and no climate policy. G20 finance ministers have to play a key role in implementing smart climate policies like carbon pricing. Yet they remain reluctant to take advantage of the merits of carbon pricing for sound fiscal policy.

Measures of GCM Performance as Functions of Model Parameters Affecting Clouds and Radiation

NASA Astrophysics Data System (ADS)

Jackson, C.; Mu, Q.; Sen, M.; Stoffa, P.

2002-05-01

This abstract is one of three related presentations at this meeting dealing with several issues surrounding optimal parameter and uncertainty estimation of model predictions of climate. Uncertainty in model predictions of climate depends in part on the uncertainty produced by model approximations or parameterizations of unresolved physics. Evaluating these uncertainties is computationally expensive because one needs to evaluate how arbitrary choices for any given combination of model parameters affects model performance. Because the computational effort grows exponentially with the number of parameters being investigated, it is important to choose parameters carefully. Evaluating whether a parameter is worth investigating depends on two considerations: 1) does reasonable choices of parameter values produce a large range in model response relative to observational uncertainty? and 2) does the model response depend non-linearly on various combinations of model parameters? We have decided to narrow our attention to selecting parameters that affect clouds and radiation, as it is likely that these parameters will dominate uncertainties in model predictions of future climate. We present preliminary results of ~20 to 30 AMIPII style climate model integrations using NCAR's CCM3.10 that show model performance as functions of individual parameters controlling 1) critical relative humidity for cloud formation (RHMIN), and 2) boundary layer critical Richardson number (RICR). We also explore various definitions of model performance that include some or all observational data sources (surface air temperature and pressure, meridional and zonal winds, clouds, long and short-wave cloud forcings, etc...) and evaluate in a few select cases whether the model's response depends non-linearly on the parameter values we have selected.

Mapping Surface Cover Parameters Using Aggregation Rules and Remotely Sensed Cover Classes. Version 1.9

NASA Technical Reports Server (NTRS)

Arain, Altaf M.; Shuttleworth, W. James; Yang, Z-Liang; Michaud, Jene; Dolman, Johannes

1997-01-01

A coupled model, which combines the Biosphere-Atmosphere Transfer Scheme (BATS) with an advanced atmospheric boundary-layer model, was used to validate hypothetical aggregation rules for BATS-specific surface cover parameters. The model was initialized and tested with observations from the Anglo-Brazilian Amazonian Climate Observational Study and used to simulate surface fluxes for rain forest and pasture mixes at a site near Manaus in Brazil. The aggregation rules are shown to estimate parameters which give area-average surface fluxes similar to those calculated with explicit representation of forest and pasture patches for a range of meteorological and surface conditions relevant to this site, but the agreement deteriorates somewhat when there are large patch-to-patch differences in soil moisture. The aggregation rules, validated as above, were then applied to remotely sensed 1 km land cover data set to obtain grid-average values of BATS vegetation parameters for 2.8 deg x 2.8 deg and 1 deg x 1 deg grids within the conterminous United States. There are significant differences in key vegetation parameters (aerodynamic roughness length, albedo, leaf area index, and stomatal resistance) when aggregate parameters are compared to parameters for the single, dominant cover within the grid. However, the surface energy fluxes calculated by stand-alone BATS with the 2-year forcing, data from the International Satellite Land Surface Climatology Project (ISLSCP) CDROM were reasonably similar using aggregate-vegetation parameters and dominant-cover parameters, but there were some significant differences, particularly in the western USA.

Scientific Uncertainties in Climate Change Detection and Attribution Studies

NASA Astrophysics Data System (ADS)

Santer, B. D.

2017-12-01

It has been claimed that the treatment and discussion of key uncertainties in climate science is "confined to hushed sidebar conversations at scientific conferences". This claim is demonstrably incorrect. Climate change detection and attribution studies routinely consider key uncertainties in observational climate data, as well as uncertainties in model-based estimates of natural variability and the "fingerprints" in response to different external forcings. The goal is to determine whether such uncertainties preclude robust identification of a human-caused climate change fingerprint. It is also routine to investigate the impact of applying different fingerprint identification strategies, and to assess how detection and attribution results are impacted by differences in the ability of current models to capture important aspects of present-day climate. The exploration of the uncertainties mentioned above will be illustrated using examples from detection and attribution studies with atmospheric temperature and moisture.

Global climate change implications for coastal and offshore oil and gas development

USGS Publications Warehouse

Burkett, V.

2011-01-01

The discussion and debate about climate change and oil and gas resource development has generally focused on how fossil fuel use affects the Earth's climate. This paper explores how the changing climate is likely to affect oil and gas operations in low-lying coastal areas and the outer continental shelf. Oil and gas production in these regions comprises a large sector of the economies of many energy producing nations. Six key climate change drivers in coastal and marine regions are characterized with respect to oil and gas development: changes in carbon dioxide levels and ocean acidity, air and water temperature, precipitation patterns, the rate of sea level rise, storm intensity, and wave regime. These key drivers have the potential to independently and cumulatively affect coastal and offshore oil and gas exploration, production, and transportation, and several impacts of climate change have already been observed in North America. ?? 2011.

ESA Earth Observation missions at the service of geoscience

NASA Astrophysics Data System (ADS)

Aschbacher, Josef

2017-04-01

The intervention will present ESA's Earth Observation programmes and their relevance to geoscience. ESA's Earth observation missions are mainly grouped into three categories: The Sentinel satellites in the context of the European Copernicus Programme, the scientific Earth Explorers and the meteorological missions. Developments, applications and scientific results for the different mission types will be addressed, along with overall trends and boundary conditions. The Earth Explorers, who form the science and research element of ESA's Living Planet Programme, focus on the atmosphere, biosphere, hydrosphere, cryosphere and Earth's interior. The Earth Explorers also aim at learning more about the interactions between these components and the impact that human activity is having on natural Earth processes. The Sentinel missions provide accurate, timely, long term and uninterrupted data to provide key information services, improving the way the environment is managed, and helping to mitigate the effects of climate change. The operational Sentinel satellites can also be exploited for scientific endeavours. Meteorological satellites help to predict the weather and feature the most mature application of Earth observation. Over the last four decades satellites have been radically improving the accuracy of weather forecasts by providing unique and indispensable input data to numerical computation models. In addition, Essential Climate Variables (ECV) are constantly monitored within ESA's Climate Change Initiative in order to create a long-term record of key geophysical parameters. All of these activities can only be carried out in international cooperation. Accordingly, ESA maintains long-standing partnerships with other space agencies and relevant institutions worldwide. In running its Earth observation programmes, ESA responds to societal needs and challenges as well as to requirements resulting from political priorities, such as the United Nations' Sustainable Development Goals.

Assessment of climate variability of the Greenland Ice Sheet: Integration of in situ and satellite data

NASA Technical Reports Server (NTRS)

Steffen, K.; Abdalati, W.; Stroeve, J.; Key, J.

1994-01-01

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland Ice Sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meteorological data sets. Operational satellite sensors are calibrated based on ground measurements and atmospheric modeling prior to large scale analysis to ensure the quality of the satellite data. Further, several satellite sensors of different spatial and spectral resolution are intercompared to access the parameter accuracy. Proposed parameterization schemes to derive key component of the energy balance from satellite data are validated. For the understanding of the surface processes a field program was designed to collect information on spectral albedo, specular reflectance, soot content, grain size and the physical properties of different snow types. Further, the radiative and turbulent fluxes at the ice/snow surface are monitored for the parameterization and interpretation of the satellite data. The expected results include several baseline data sets of albedo, surface temperature, radiative fluxes, and different snow types of the entire Greenland Ice Sheet. These climatological data sets will be of potential use for climate sensitivity studies in the context of future climate change.

Olive cultivars adaptability in Southern Italy in present and future climate

NASA Astrophysics Data System (ADS)

Riccardi, M.; Alfieri, S.; Bonfante, A.; Basile, A.; Di Tommasi, P.; Menenti, M.; De Lorenzi, F.

2012-04-01

The intra-specific biodiversity of agricultural crops is very significant and likely to provide the single major opportunity to cope with the effects of the changing climate on agricultural ecosystems. Assessment of adaptive capacity must rely on quantitative descriptions of plant responses to environmental factors (e.g. soil water availability, temperature). Moreover climate scenario needs to be downscaled to the spatial scale relevant to crop and farm management. Distributed models of crop response to environmental forcing might be used for this purpose, but severely constrained by the very scarce knowledge on variety-specific values of model parameters, thus limiting the potential exploitation of intra-specific biodiversity towards adaptation. We have developed an approach towards this objective that relies on two complementary elements: a)a distributed model of the soil plant atmosphere system to downscale climate scenarios to landscape units, where generic model parameters for each species are used; b)a data base on climatic requirements of as many varieties as feasible for each species relevant to the agricultural production system of a given region. By means of this approach, the adaptability of some olive cultivars was evaluated in a composite (hills and plains) area of Southern Italy (Valle Telesina, Campania Region, about 20.000 ha). The yearly average temperature is 22.5 °C and rainfall ranges between 600 and 900 mm. Two different climate scenarios were considered: current climate (1961-1990) and future climate (2021-2050). Future climate scenarios at low spatial resolution were generated with general circulation models (AOGCM) and down-scaled by means of a statistical model (Tomozeiu et al., 2007). The climate was represented by daily observations of minimum, maximum temperature and precipitation on a regular grid with a spatial resolution of 35 km; 50 realizations were used for future climate. The soil water regime of 45 soil units was described for the two climate scenarios by using an hydrological distributed model (SWAP). For 11 olive cultivars, the yield response function to soil water regime was determined through the re-analysis of experimental data (unpublished or derived from scientific literature). According to these responses, cultivar-specific threshold values of soil water (or evapotranspiration) deficit were defined. The soil water regime calculated by the distributed model was compared with the threshold values to identify cultivars compatible with present and expected climates. The operation is repeated for a set of realizations of each climate scenario. This analysis is performed in a distributed manner, i.e. using the time series for each model grid to assess possible variations in the extent and spatial distribution of cultivated area of olive cultivars. In the study area future climate scenarios predict an increase of monthly minimum and maximum air temperature of about 2°C during the summer (June, July and August) and a reduction of rainfall in autumn. Spatial pattern of cultivars distribution, according their threshold values and soil water regime, was determined in the present and future climate scenarios, thus assessing variations in cultivars adaptability to future climate with respect to the present. Key words: climate change, biodiversity, water availability, yield response. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008).

Climate Change Impact Assessment of Food- and Waterborne Diseases.

PubMed

Semenza, Jan C; Herbst, Susanne; Rechenburg, Andrea; Suk, Jonathan E; Höser, Christoph; Schreiber, Christiane; Kistemann, Thomas

2012-04-01

The PubMed and ScienceDirect bibliographic databases were searched for the period of 1998-2009 to evaluate the impact of climatic and environmental determinants on food- and waterborne diseases. The authors assessed 1,642 short and concise sentences (key facts), which were extracted from 722 relevant articles and stored in a climate change knowledge base. Key facts pertaining to temperature, precipitation, water, and food for 6 selected pathogens were scrutinized, evaluated, and compiled according to exposure pathways. These key facts (corresponding to approximately 50,000 words) were mapped to 275 terminology terms identified in the literature, which generated 6,341 connections. These relationships were plotted on semantic network maps to examine the interconnections between variables. The risk of campylobacteriosis is associated with mean weekly temperatures, although this link is shown more strongly in the literature relating to salmonellosis. Irregular and severe rain events are associated with Cryptosporidium sp. outbreaks, while noncholera Vibrio sp. displays increased growth rates in coastal waters during hot summers. In contrast, for Norovirus and Listeria sp. the association with climatic variables was relatively weak, but much stronger for food determinants. Electronic data mining to assess the impact of climate change on food- and waterborne diseases assured a methodical appraisal of the field. This climate change knowledge base can support national climate change vulnerability, impact, and adaptation assessments and facilitate the management of future threats from infectious diseases. In the light of diminishing resources for public health this approach can help balance different climate change adaptation options.

Climate Change Impact Assessment of Food- and Waterborne Diseases

PubMed Central

Semenza, Jan C.; Herbst, Susanne; Rechenburg, Andrea; Suk, Jonathan E.; Höser, Christoph; Schreiber, Christiane; Kistemann, Thomas

2011-01-01

The PubMed and ScienceDirect bibliographic databases were searched for the period of 1998–2009 to evaluate the impact of climatic and environmental determinants on food- and waterborne diseases. The authors assessed 1,642 short and concise sentences (key facts), which were extracted from 722 relevant articles and stored in a climate change knowledge base. Key facts pertaining to temperature, precipitation, water, and food for 6 selected pathogens were scrutinized, evaluated, and compiled according to exposure pathways. These key facts (corresponding to approximately 50,000 words) were mapped to 275 terminology terms identified in the literature, which generated 6,341 connections. These relationships were plotted on semantic network maps to examine the interconnections between variables. The risk of campylobacteriosis is associated with mean weekly temperatures, although this link is shown more strongly in the literature relating to salmonellosis. Irregular and severe rain events are associated with Cryptosporidium sp. outbreaks, while noncholera Vibrio sp. displays increased growth rates in coastal waters during hot summers. In contrast, for Norovirus and Listeria sp. the association with climatic variables was relatively weak, but much stronger for food determinants. Electronic data mining to assess the impact of climate change on food- and waterborne diseases assured a methodical appraisal of the field. This climate change knowledge base can support national climate change vulnerability, impact, and adaptation assessments and facilitate the management of future threats from infectious diseases. In the light of diminishing resources for public health this approach can help balance different climate change adaptation options. PMID:24808720

Key Findings from the U.S.-India Partnership for Climate Resilience Workshop on Development and Application of Downscaling Climate Projections

NASA Astrophysics Data System (ADS)

Kunkel, K.; Dissen, J.; Easterling, D. R.; Kulkarni, A.; Akhtar, F. H.; Hayhoe, K.; Stoner, A. M. K.; Swaminathan, R.; Thrasher, B. L.

2017-12-01

s part of the Department of State U.S.-India Partnership for Climate Resilience (PCR), scientists from NOAA NCEI, CICS-NC, Texas Tech University (TTU), Stanford University (SU), and the Indian Institute of Tropical Meteorology (IITM) held a workshop at IITM in Pune, India during 7-9 March 2017 on the development, techniques and applications of downscaled climate projections. Workshop participants from TTU, SU, and IITM presented state-of-the-art climate downscaling techniques using the ARRM method, NASA NEX climate products, CORDEX-South Asia and analysis tools for resilience planning and sustainable development. PCR collaborators in attendance included Indian practitioners, researchers and other NGO including the WRI Partnership for Resilience and Preparedness (PREP), The Energy and Resources Institute (TERI), and NIH. The scientific techniques were provided to workshop participants in a software package written in R by TTU scientists and several sessions were devoted to hands-on experience with the software package. The workshop further examined case studies on the use of downscaled climate data for decision making in a range of sectors, including human health, agriculture, and water resources management as well as to inform the development of the India State Action Plans. This talk will discuss key outcomes including information needs for downscaling climate projections, importance of QA/QC of the data, key findings from select case studies, and the importance of collaborations and partnerships to apply downscaling projections to help inform the development of the India State Action Plans.

The Role of Health in Climate Litigation

PubMed Central

Simmens, Samuel J.; Glicksman, Robert; Paddock, LeRoy; Kim, Daniel; Whited, Brittany

2018-01-01

Objectives. To examine how the courts, which play a critical role in shaping public policy, consider public health in climate change and coal-fired power plant lawsuits. Methods. We coded US local, state, and federal court decisions relating to climate change and coal-fired power plants from 1990 to 2016 (n = 873) and qualitatively investigated 139 cases in which litigants raised issues concerning the health impacts of climate change. We also conducted 78 interviews with key litigants, advocates, industry representatives, advising scientists, and legal experts. Results. Health has been a critical consideration in key climate lawsuits, but in a minority of cases. Litigants have presented health arguments most frequently and effectively in terms of airborne exposures. Health impacts have typically been used to gain standing and argue that the evidence for government actions is insufficient. Conclusions. The courts represent a pivotal branch of government in shaping climate policy. Increasing inclusion of health concerns in emergent areas of litigation could help drive more effective climate policymaking. PMID:29698089

Global volcanic aerosol properties derived from emissions, 1990-2014, using CESM1(WACCM)

NASA Astrophysics Data System (ADS)

Mills, Michael J.; Schmidt, Anja; Easter, Richard; Solomon, Susan; Kinnison, Douglas E.; Ghan, Steven J.; Neely, Ryan R.; Marsh, Daniel R.; Conley, Andrew; Bardeen, Charles G.; Gettelman, Andrew

2016-03-01

Accurate representation of global stratospheric aerosols from volcanic and nonvolcanic sulfur emissions is key to understanding the cooling effects and ozone losses that may be linked to volcanic activity. Attribution of climate variability to volcanic activity is of particular interest in relation to the post-2000 slowing in the rate of global average temperature increases. We have compiled a database of volcanic SO2 emissions and plume altitudes for eruptions from 1990 to 2014 and developed a new prognostic capability for simulating stratospheric sulfate aerosols in the Community Earth System Model. We used these combined with other nonvolcanic emissions of sulfur sources to reconstruct global aerosol properties from 1990 to 2014. Our calculations show remarkable agreement with ground-based lidar observations of stratospheric aerosol optical depth (SAOD) and with in situ measurements of stratospheric aerosol surface area density (SAD). These properties are key parameters in calculating the radiative and chemical effects of stratospheric aerosols. Our SAOD calculations represent a clear improvement over available satellite-based analyses, which generally ignore aerosol extinction below 15 km, a region that can contain the vast majority of stratospheric aerosol extinction at middle and high latitudes. Our SAD calculations greatly improve on that provided for the Chemistry-Climate Model Initiative, which misses about 60% of the SAD measured in situ on average during both volcanically active and volcanically quiescent periods.

Challenges of model transferability to data-scarce regions (Invited)

NASA Astrophysics Data System (ADS)

Samaniego, L. E.

2013-12-01

Developing the ability to globally predict the movement of water on the land surface at spatial scales from 1 to 5 km constitute one of grand challenges in land surface modelling. Copying with this grand challenge implies that land surface models (LSM) should be able to make reliable predictions across locations and/or scales other than those used for parameter estimation. In addition to that, data scarcity and quality impose further difficulties in attaining reliable predictions of water and energy fluxes at the scales of interest. Current computational limitations impose also seriously limitations to exhaustively investigate the parameter space of LSM over large domains (e.g. greater than half a million square kilometers). Addressing these challenges require holistic approaches that integrate the best techniques available for parameter estimation, field measurements and remotely sensed data at their native resolutions. An attempt to systematically address these issues is the multiscale parameterisation technique (MPR) that links high resolution land surface characteristics with effective model parameters. This technique requires a number of pedo-transfer functions and a much fewer global parameters (i.e. coefficients) to be inferred by calibration in gauged basins. The key advantage of this technique is the quasi-scale independence of the global parameters which enables to estimate global parameters at coarser spatial resolutions and then to transfer them to (ungauged) areas and scales of interest. In this study we show the ability of this technique to reproduce the observed water fluxes and states over a wide range of climate and land surface conditions ranging from humid to semiarid and from sparse to dense forested regions. Results of transferability of global model parameters in space (from humid to semi-arid basins) and across scales (from coarser to finer) clearly indicate the robustness of this technique. Simulations with coarse data sets (e.g. EOBS forcing 25x25 km2, FAO soil map 1:5000000) using parameters obtained with high resolution information (REGNIE forcing 1x1 km2, BUEK soil map 1:1000000) in different climatic regions indicate the potential of MPR for prediction in data-scarce regions. In this presentation, we will also discuss how the transferability of global model parameters across scales and locations helps to identify deficiencies in model structure and regionalization functions.

The complex relationship between climate and sugar maple health: Climate change implications in Vermont for a key northern hardwood species

Treesearch

Evan M. Oswald; Jennifer Pontius; Shelly A. Rayback; Paul G. Schaberg; Sandra H. Wilmot; Lesley-Ann Dupigny-Giroux

2018-01-01

This study compared 141 ecologically relevant climate metrics to field assessments of sugar maple (Acer saccharum Marsh.) canopy condition across Vermont, USA from 1988 to 2012. After removing the influence of disturbance events during this time period to isolate the impact of climate, we identified five climate metrics that were significantly...

Indicators of climate impacts for forests: recommendations for the US National Climate Assessment indicators system

Treesearch

Linda S. Heath; Sarah M. Anderson; Marla R. Emery; Jeffrey A. Hicke; Jeremy Littell; Alan Lucier; Jeffrey G. Masek; David L. Peterson; Richard Pouyat; Kevin M. Potter; Guy Robertson; Jinelle Sperry; Andrzej Bytnerowicz; Sarah Jovan; Miranda H. Mockrin; Robert Musselman; Bethany K. Schulz; Robert J. Smith; Susan I. Stewart

2015-01-01

The Third National Climate Assessment (NCA) process for the United States focused in part on developing a system of indicators to communicate key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness to inform decisionmakers and the public. Initially, 13 active teams were formed to recommend indicators in a range of categories, including...

Regional climate model assessment of the urban land-surface forcing over central Europe

NASA Astrophysics Data System (ADS)

Huszar, P.; Halenka, T.; Belda, M.; Zak, M.; Sindelarova, K.; Miksovsky, J.

2014-07-01

For the purpose of qualifying and quantifying the climate impact of cities and urban surfaces in general on climate of central Europe, the surface parameterization in regional climate model RegCM4 has been extended with the Single Layer Urban Canopy Model (SLUCM). A set of experiments was performed over the period of 2005-2009 for central Europe, either without considering urban surfaces or with the SLUCM treatment. Results show a statistically significant impact of urbanized surfaces on temperature (up to 1.5 K increase in summer) as well as on the boundary layer height (increases up to 50 m). Urbanization further influences surface wind with a winter decrease up to -0.6 m s-1, though both increases and decreases were detected in summer depending on the location relative to the cities and daytime (changes up to 0.3 m s-1). Urban surfaces significantly reduce evaporation and thus the humidity over the surface. This impacts the simulated summer precipitation rate, showing decrease over cities up to -2 mm day-1. Significant temperature increases are simulated over higher elevations as well, not only within the urban canopy layer. With the urban parameterization, the climate model better describes the diurnal temperature variation, reducing the cold afternoon and evening bias of RegCM4. Sensitivity experiments were carried out to quantify the response of the meteorological conditions to changes in the parameters specific to the urban environment such as street width, building height, albedo of the roofs and anthropogenic heat release. The results proved to be rather robust and the choice of the key SLUCM parameters impacts them only slightly (mainly temperature, boundary layer height and wind velocity). Statistically significant impacts are modeled not only over large urbanized areas, but the influence of the cities is also evident over rural areas without major urban surfaces. It is shown that this is the result of the combined effect of the distant influence of the cities and the influence of the minor local urban surface coverage.

Regional climate model assessment of the urban land-surface forcing over central Europe

NASA Astrophysics Data System (ADS)

Huszar, P.; Halenka, T.; Belda, M.; Zak, M.; Sindelarova, K.; Miksovsky, J.

2014-11-01

For the purpose of qualifying and quantifying the climate impact of cities and urban surfaces in general on climate of central Europe, the surface parameterization in regional climate model RegCM4 has been extended with the Single-layer Urban Canopy Model (SLUCM). A set of experiments was performed over the period of 2005-2009 for central Europe, either without considering urban surfaces or with the SLUCM treatment. Results show a statistically significant impact of urbanized surfaces on temperature (up to 1.5 K increase in summer) as well as on the boundary layer height (increases up to 50 m). Urbanization further influences surface wind with a winter decrease up to -0.6 m s-1, though both increases and decreases were detected in summer depending on the location relative to the cities and daytime (changes up to 0.3 m s-1). Urban surfaces significantly reduce the humidity over the surface. This impacts the simulated summer precipitation rate, showing a decrease over cities of up to -2 mm day-1. Significant temperature increases are simulated over higher altitudes as well, not only within the urban canopy layer. With the urban parameterization, the climate model better describes the diurnal temperature variation, reducing the cold afternoon and evening bias of RegCM4. Sensitivity experiments were carried out to quantify the response of the meteorological conditions to changes in the parameters specific to the urban environment, such as street width, building height, albedo of the roofs and anthropogenic heat release. The results proved to be rather robust and the choice of the key SLUCM parameters impacts them only slightly (mainly temperature, boundary layer height and wind velocity). Statistically significant impacts are modelled not only over large urbanized areas, but the influence of the cities is also evident over rural areas without major urban surfaces. It is shown that this is the result of the combined effect of the distant influence of the cities and the influence of the minor local urban surface coverage.

Importance of determining the climatic domains of sheep breeds.

PubMed

Petit, D; Boujenane, I

2018-07-01

The main purpose of the study was to compare the capacity of the major sheep breeds in Morocco to cope with climate changes through the ranges of several climate parameters in which they can be found. We first delimitated the climatic 'domains' of each breed by constructing a database including altitude and climatic parameters (minima mean of the coldest month, maxima mean of the hottest month, annual rainfall, pluviothermic coefficient of Emberger Q 2, annual minima mean and annual maxima mean) on a 30-year period using the representative stations of each breed distribution. The overlap between each breed combination was quantified through a canonical analysis that extracted the most discriminant parameters. The variance analysis of each climatic parameter evidenced two breeds remarkable by their tolerance. The first one is the Timahdite, mainly settled in areas over 1100 m, which can tolerate the greatest variations in annual rainfall and pluviothermic coefficient. In spite of this feature, this breed is endangered owing to the decreasing quality of pastures. The second one is the D'man which apparently can support high variations in extreme temperatures. In fact, this breed is not well adapted to pastures and requires a special microclimate offered by oases. The information reported in this study will be the basis for the establishment of characterization and selection strategies for Moroccan sheep.

Rough parameter dependence in climate models and the role of Ruelle-Pollicott resonances.

PubMed

Chekroun, Mickaël David; Neelin, J David; Kondrashov, Dmitri; McWilliams, James C; Ghil, Michael

2014-02-04

Despite the importance of uncertainties encountered in climate model simulations, the fundamental mechanisms at the origin of sensitive behavior of long-term model statistics remain unclear. Variability of turbulent flows in the atmosphere and oceans exhibits recurrent large-scale patterns. These patterns, while evolving irregularly in time, manifest characteristic frequencies across a large range of time scales, from intraseasonal through interdecadal. Based on modern spectral theory of chaotic and dissipative dynamical systems, the associated low-frequency variability may be formulated in terms of Ruelle-Pollicott (RP) resonances. RP resonances encode information on the nonlinear dynamics of the system, and an approach for estimating them--as filtered through an observable of the system--is proposed. This approach relies on an appropriate Markov representation of the dynamics associated with a given observable. It is shown that, within this representation, the spectral gap--defined as the distance between the subdominant RP resonance and the unit circle--plays a major role in the roughness of parameter dependences. The model statistics are the most sensitive for the smallest spectral gaps; such small gaps turn out to correspond to regimes where the low-frequency variability is more pronounced, whereas autocorrelations decay more slowly. The present approach is applied to analyze the rough parameter dependence encountered in key statistics of an El-Niño-Southern Oscillation model of intermediate complexity. Theoretical arguments, however, strongly suggest that such links between model sensitivity and the decay of correlation properties are not limited to this particular model and could hold much more generally.

Rough parameter dependence in climate models and the role of Ruelle-Pollicott resonances

PubMed Central

Chekroun, Mickaël David; Neelin, J. David; Kondrashov, Dmitri; McWilliams, James C.; Ghil, Michael

2014-01-01

Despite the importance of uncertainties encountered in climate model simulations, the fundamental mechanisms at the origin of sensitive behavior of long-term model statistics remain unclear. Variability of turbulent flows in the atmosphere and oceans exhibits recurrent large-scale patterns. These patterns, while evolving irregularly in time, manifest characteristic frequencies across a large range of time scales, from intraseasonal through interdecadal. Based on modern spectral theory of chaotic and dissipative dynamical systems, the associated low-frequency variability may be formulated in terms of Ruelle-Pollicott (RP) resonances. RP resonances encode information on the nonlinear dynamics of the system, and an approach for estimating them—as filtered through an observable of the system—is proposed. This approach relies on an appropriate Markov representation of the dynamics associated with a given observable. It is shown that, within this representation, the spectral gap—defined as the distance between the subdominant RP resonance and the unit circle—plays a major role in the roughness of parameter dependences. The model statistics are the most sensitive for the smallest spectral gaps; such small gaps turn out to correspond to regimes where the low-frequency variability is more pronounced, whereas autocorrelations decay more slowly. The present approach is applied to analyze the rough parameter dependence encountered in key statistics of an El-Niño–Southern Oscillation model of intermediate complexity. Theoretical arguments, however, strongly suggest that such links between model sensitivity and the decay of correlation properties are not limited to this particular model and could hold much more generally. PMID:24443553

Parameterisation of Biome BGC to assess forest ecosystems in Africa

NASA Astrophysics Data System (ADS)

Gautam, Sishir; Pietsch, Stephan A.

2010-05-01

African forest ecosystems are an important environmental and economic resource. Several studies show that tropical forests are critical to society as economic, environmental and societal resources. Tropical forests are carbon dense and thus play a key role in climate change mitigation. Unfortunately, the response of tropical forests to environmental change is largely unknown owing to insufficient spatially extensive observations. Developing regions like Africa where records of forest management for long periods are unavailable the process-based ecosystem simulation model - BIOME BGC could be a suitable tool to explain forest ecosystem dynamics. This ecosystem simulation model uses descriptive input parameters to establish the physiology, biochemistry, structure, and allocation patterns within vegetation functional types, or biomes. Undocumented parameters for larger-resolution simulations are currently the major limitations to regional modelling in African forest ecosystems. This study was conducted to document input parameters for BIOME-BGC for major natural tropical forests in the Congo basin. Based on available literature and field measurements updated values for turnover and mortality, allometry, carbon to nitrogen ratios, allocation of plant material to labile, cellulose, and lignin pools, tree morphology and other relevant factors were assigned. Daily climate input data for the model applications were generated using the statistical weather generator MarkSim. The forest was inventoried at various sites and soil samples of corresponding stands across Gabon were collected. Carbon and nitrogen in the collected soil samples were determined from soil analysis. The observed tree volume, soil carbon and soil nitrogen were then compared with the simulated model outputs to evaluate the model performance. Furthermore, the simulation using Congo Basin specific parameters and generalised BIOME BGC parameters for tropical evergreen broadleaved tree species were also executed and the simulated results compared. Once the model was optimised for forests in the Congo basin it was validated against observed tree volume, soil carbon and soil nitrogen from a set of independent plots.

Detecting seasonal variations of soil parameters via field measurements and stochastic simulations in the hillslope

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; An, Hyunuk; Kim, Sanghyun

2015-04-01

Soil moisture, a critical factor in hydrologic systems, plays a key role in synthesizing interactions among soil, climate, hydrological response, solute transport and ecosystem dynamics. The spatial and temporal distribution of soil moisture at a hillslope scale is essential for understanding hillslope runoff generation processes. In this study, we implement Monte Carlo simulations in the hillslope scale using a three-dimensional surface-subsurface integrated model (3D model). Numerical simulations are compared with multiple soil moistures which had been measured using TDR(Mini_TRASE) for 22 locations in 2 or 3 depths during a whole year at a hillslope (area: 2100 square meters) located in Bongsunsa Watershed, South Korea. In stochastic simulations via Monte Carlo, uncertainty of the soil parameters and input forcing are considered and model ensembles showing good performance are selected separately for several seasonal periods. The presentation will be focused on the characterization of seasonal variations of model parameters based on simulations with field measurements. In addition, structural limitations of the contemporary modeling method will be discussed.

Assessing and Upgrading Ocean Mixing for the Study of Climate Change

NASA Astrophysics Data System (ADS)

Howard, A. M.; Fells, J.; Lindo, F.; Tulsee, V.; Canuto, V.; Cheng, Y.; Dubovikov, M. S.; Leboissetier, A.

2016-12-01

Climate is critical. Climate variability affects us all; Climate Change is a burning issue. Droughts, floods, other extreme events, and Global Warming's effects on these and problems such as sea-level rise and ecosystem disruption threaten lives. Citizens must be informed to make decisions concerning climate such as "business as usual" vs. mitigating emissions to keep warming within bounds. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. To make useful predictions we must realistically model each component of the climate system, including the ocean, whose critical role includes transporting&storing heat and dissolved CO2. We need physically based parameterizations of key ocean processes that can't be put explicitly in a global climate model, e.g. vertical&lateral mixing. The NASA-GISS turbulence group uses theory to model mixing including: 1) a comprehensive scheme for small scale vertical mixing, including convection&shear, internal waves & double-diffusion, and bottom tides 2) a new parameterization for the lateral&vertical mixing by mesoscale eddies. For better understanding we write our own programs. To assess the modelling MATLAB programs visualize and calculate statistics, including means, standard deviations and correlations, on NASA-GISS OGCM output with different mixing schemes and help us study drift from observations. We also try to upgrade the schemes, e.g. the bottom tidal mixing parameterizations' roughness, calculated from high resolution topographic data using Gaussian weighting functions with cut-offs. We study the effects of their parameters to improve them. A FORTRAN program extracts topography data subsets of manageable size for a MATLAB program, tested on idealized cases, to visualize&calculate roughness on. Students are introduced to modeling a complex system, gain a deeper appreciation of climate science, programming skills and familiarity with MATLAB, while furthering climate science by improving our mixing schemes. We are incorporating climate research into our college curriculum. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, an urban minority serving institution in central Brooklyn. Supported by NSF Award AGS-1359293.

Water Availability in Indus River at the Upper Indus Basin under Different Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Khan, Firdos; Pilz, Jürgen

2015-04-01

The last decade of the 20th century and the first decade of the 21st century showed that climate change or global warming is happening and the latter one is considered as the warmest decade over Pakistan ever in history where temperature reached 53 0C on May 26, 2010. The changing climate has impact on various areas including agriculture, water, health, among others. There are two main forces which have central role in changing climate: one is natural variability and the other one is human evoked changes, increasing the density of green house gases. The elements in the bunch of Energy-Food-Water are interlinked with one another and among them water plays a crucial role for the existence of the other two parts. This nexus is the central environmental issue around the globe generally, and is of particular importance in the developing countries. The study evaluated the importance and the availability of water in Indus River under different emission scenarios. Four emission scenarios are included, that is, the A2, B2, RCP4.5 and RCP8.5. One way coupling of regional climate models (RCMs) and Hydrological model have been implemented in this study. The PRECIS (Providing Regional Climate for Impact Studies) and CCAM (Conformal-Cubic Atmospheric Model) climate models and UBCWM (University of British Columbia Watershed Model) hydrological model are used for this purpose. It is observed that Indus River contributes 80 % of the hydro-power generation and contributes 44 % to available water annually in Pakistan. It is further investigated whether sufficient water will be available in the Indus River under climate change scenarios. Toward this goal, Tarbela Reservoir is used as a measurement tool using the parameters of the reservoir like maximum operating storage, dead level storage, discharge capacity of tunnels and spillways. The results of this study are extremely important for the economy of Pakistan in various key areas like agriculture, energy, industries and ecosystem. The analyses show that there will be much more water available in future under the considered emission scenarios but in some months there will be scarcity of water. However, by proper management and optimum utilization of the available water, the scarcity of water can be minimized considerably. Finally, a meta-analysis has been performed to present a combined picture of all scenarios considered in this study. One way to avoid water scarcity is to upgrade and install new reservoirs and water storage capacities to reserve the extra water during high river flow in Indus River, which will then be utilized during low river flow. __________________________________________________________________________________ KEY WORDS: Agriculture, Climate Change, Hydro-power, Indus River, Tarbela Reservoir, Upper Indus Basin, Meta-analysis, Hydrological model.

A conceptual model of oceanic heat transport in the Snowball Earth scenario

NASA Astrophysics Data System (ADS)

Comeau, Darin; Kurtze, Douglas A.; Restrepo, Juan M.

2016-12-01

Geologic evidence suggests that the Earth may have been completely covered in ice in the distant past, a state known as Snowball Earth. This is still the subject of controversy, and has been the focus of modeling work from low-dimensional models up to state-of-the-art general circulation models. In our present global climate, the ocean plays a large role in redistributing heat from the equatorial regions to high latitudes, and as an important part of the global heat budget, its role in the initiation a Snowball Earth, and the subsequent climate, is of great interest. To better understand the role of oceanic heat transport in the initiation of Snowball Earth, and the resulting global ice covered climate state, the goal of this inquiry is twofold: we wish to propose the least complex model that can capture the Snowball Earth scenario as well as the present-day climate with partial ice cover, and we want to determine the relative importance of oceanic heat transport. To do this, we develop a simple model, incorporating thermohaline dynamics from traditional box ocean models, a radiative balance from energy balance models, and the more contemporary "sea glacier" model to account for viscous flow effects of extremely thick sea ice. The resulting model, consisting of dynamic ocean and ice components, is able to reproduce both Snowball Earth and present-day conditions through reasonable changes in forcing parameters. We find that including or neglecting oceanic heat transport may lead to vastly different global climate states, and also that the parameterization of under-ice heat transfer in the ice-ocean coupling plays a key role in the resulting global climate state, demonstrating the regulatory effect of dynamic ocean heat transport.

Toward a Last Interglacial Compilation Using a Tephra-based Chronology: a Future Reference For Model-data Comparison

NASA Astrophysics Data System (ADS)

Bazin, L.; Govin, A.; Capron, E.; Nomade, S.; Lemieux-Dudon, B.; Landais, A.

2017-12-01

The Last Interglacial (LIG, 129-116 ka) is a key period to decipher the interactions between the different components of the climate system under warmer-than-preindustrial conditions. Modelling the LIG climate is now part of the CMIP6/PMIP4 targeted simulations. As a result, recent efforts have been made to propose surface temperature compilations focusing on the spatio-temporal evolution of the LIG climate, and not only on its peak warmth as previously proposed. However, the major limitation of these compilations remains in the climatic alignment of records (e.g. temperature, foraminiferal δ18O) that is performed to define the sites' chronologies. Such methods prevent the proper discussion of phase relationship between the different sites. Thanks to recent developments of the Bayesian Datice dating tool, we are now able to build coherent multi-archive chronologies with a proper propagation of the associated uncertainties. We make the best use of common tephra layers identified in well-dated continental archives and marine sediment cores of the Mediterranean region to propose a coherent chronological framework for the LIG independent of any climatic assumption. We then extend this precise chronological context to the North Atlantic as a first step toward a global coherent compilation of surface temperature and stable isotope records. Based on this synthesis, we propose guidelines for the interpretation of different proxies measured from different archives that will be compared with climate model parameters. Finally, we present time-slices (e.g. 127 ka) of the preliminary regional synthesis of temperature reconstructions and stable isotopes to serve as reference for future model-data comparison of the up-coming CMIP6/PMIP4 LIG simulations.

Dengue Vector Dynamics (Aedes aegypti) Influenced by Climate and Social Factors in Ecuador: Implications for Targeted Control

PubMed Central

Stewart Ibarra, Anna M.; Ryan, Sadie J.; Beltrán, Efrain; Mejía, Raúl; Silva, Mercy; Muñoz, Ángel

2013-01-01

Background Dengue fever, a mosquito-borne viral disease, is now the fastest spreading tropical disease globally. Previous studies indicate that climate and human behavior interact to influence dengue virus and vector (Aedes aegypti) population dynamics; however, the relative effects of these variables depends on local ecology and social context. We investigated the roles of climate and socio-ecological factors on Ae. aegypti population dynamics in Machala, a city in southern coastal Ecuador where dengue is hyper-endemic. Methods/Principal findings We studied two proximate urban localities where we monitored weekly Ae. aegypti oviposition activity (Nov. 2010-June 2011), conducted seasonal pupal surveys, and surveyed household to identify dengue risk factors. The results of this study provide evidence that Ae. aegypti population dynamics are influenced by social risk factors that vary by season and lagged climate variables that vary by locality. Best-fit models to predict the presence of Ae. aegypti pupae included parameters for household water storage practices, access to piped water, the number of households per property, condition of the house and patio, and knowledge and perceptions of dengue. Rainfall and minimum temperature were significant predictors of oviposition activity, although the effect of rainfall varied by locality due to differences in types of water storage containers. Conclusions These results indicate the potential to reduce the burden of dengue in this region by conducting focused vector control interventions that target high-risk households and containers in each season and by developing predictive models using climate and non-climate information. These findings provide the region's public health sector with key information for conducting time and location-specific vector control campaigns, and highlight the importance of local socio-ecological studies to understand dengue dynamics. See Text S1 for an executive summary in Spanish. PMID:24324542

Simulating the effects of climate change on the distribution of an invasive plant, using a high resolution, local scale, mechanistic approach: challenges and insights.

PubMed

Fennell, Mark; Murphy, James E; Gallagher, Tommy; Osborne, Bruce

2013-04-01

The growing economic and ecological damage associated with biological invasions, which will likely be exacerbated by climate change, necessitates improved projections of invasive spread. Generally, potential changes in species distribution are investigated using climate envelope models; however, the reliability of such models has been questioned and they are not suitable for use at local scales. At this scale, mechanistic models are more appropriate. This paper discusses some key requirements for mechanistic models and utilises a newly developed model (PSS[gt]) that incorporates the influence of habitat type and related features (e.g., roads and rivers), as well as demographic processes and propagule dispersal dynamics, to model climate induced changes in the distribution of an invasive plant (Gunnera tinctoria) at a local scale. A new methodology is introduced, dynamic baseline benchmarking, which distinguishes climate-induced alterations in species distributions from other potential drivers of change. Using this approach, it was concluded that climate change, based on IPCC and C4i projections, has the potential to increase the spread-rate and intensity of G. tinctoria invasions. Increases in the number of individuals were primarily due to intensification of invasion in areas already invaded or in areas projected to be invaded in the dynamic baseline scenario. Temperature had the largest influence on changes in plant distributions. Water availability also had a large influence and introduced the most uncertainty in the projections. Additionally, due to the difficulties of parameterising models such as this, the process has been streamlined by utilising methods for estimating unknown variables and selecting only essential parameters. © 2012 Blackwell Publishing Ltd.

Java Climate Model: a tool for interaction between science, policy and citizens, to avoid dangerous anthropogenic interference in the climate system

NASA Astrophysics Data System (ADS)

Matthews, B.

2003-04-01

To reach an effective global agreement to help avoid "dangerous anthropogenic interference in the climate system" (UNFCCC article 2) we must balance many complex interacting issues, and also inspire the active engagement of citizens around the world. So we have to transfer understanding back from computers and experts, into the ultimate "integrated assessment model" which remains the global network of human heads. The Java Climate Model (JCM) tries to help provide a quantitative framework for this global dialogue, by enabling anybody to explore many mitigation policy options and scientific uncertainties simply by adjusting parameter controls with a mouse in a web browser. The instant response on linked plots helps to demonstrate cause and effect, and the sensitivity to various assumptions, risk and value judgements. JCM implements the same simple models and formulae as used by IPCC for the TAR projections, in efficient modular structure, including carbon cycle and atmospheric chemistry, radiative forcing, changes in temperature and sealevel, including some feedbacks. As well as explore the SRES scenarios, the user can create a wide variety of inverse scenarios for stabilising CO2, forcing, or temperature. People ask how local emissions which they can control, may influence the vast global natural and human systems, and change local climate impacts which affect them directly. JCM includes regional emissions and socioeconomic data, and scaled climate impact maps. However to complete this loop in a fast interactive model is a challenge! For transparency and accessibility, pop-up information is provided in ten languages, and documentation ranges from key cross-cutting questions, to them details of the model formulae, including all source code.

How do the methodological choices of your climate change study affect your results? A hydrologic case study across the Pacific Northwest

NASA Astrophysics Data System (ADS)

Chegwidden, O.; Nijssen, B.; Rupp, D. E.; Kao, S. C.; Clark, M. P.

2017-12-01

We describe results from a large hydrologic climate change dataset developed across the Pacific Northwestern United States and discuss how the analysis of those results can be seen as a framework for other large hydrologic ensemble investigations. This investigation will better inform future modeling efforts and large ensemble analyses across domains within and beyond the Pacific Northwest. Using outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we provide projections of hydrologic change for the domain through the end of the 21st century. The dataset is based upon permutations of four methodological choices: (1) ten global climate models (2) two representative concentration pathways (3) three meteorological downscaling methods and (4) four unique hydrologic model set-ups (three of which entail the same hydrologic model using independently calibrated parameter sets). All simulations were conducted across the Columbia River Basin and Pacific coastal drainages at a 1/16th ( 6 km) resolution and at a daily timestep. In total, the 172 distinct simulations offer an updated, comprehensive view of climate change projections through the end of the 21st century. The results consist of routed streamflow at 400 sites throughout the domain as well as distributed spatial fields of relevant hydrologic variables like snow water equivalent and soil moisture. In this presentation, we discuss the level of agreement with previous hydrologic projections for the study area and how these projections differ with specific methodological choices. By controlling for some methodological choices we can show how each choice affects key climatic change metrics. We discuss how the spread in results varies across hydroclimatic regimes. We will use this large dataset as a case study for distilling a wide range of hydroclimatological projections into useful climate change assessments.

Climate Literacy Partnership in the Southeast (CLiPSE): A Focus on Climate Change-related Dialogs with Faith-Based Groups as a form of Network Building in the Southeast United States - Lessons Learned

NASA Astrophysics Data System (ADS)

Carroll, F. J.; McNeal, K. S.; Hammerman, J.; Christiansen, J.

2013-05-01

The Climate Literacy Partnership in the Southeast (CLiPSE, http://CLiPSE-project.org), funded through the National Science Foundation Climate Change Education Partnership program, is dedicated to improving climate literacy in the Southeastern United States (SE US). By promoting science-based formal and informal educational resources, CLiPSE works through a diverse network of key partner organizations in the SE US to conduct effective public dialogues that address diverse audiences and support learning about climate, climate change, and its impact on human and environmental systems. The CLiPSE project successfully created partnerships with more than fifty key stakeholders, including agriculture, education, leisure, and religious organizations, along with culturally diverse communities. This presentation will explain the CLiPSE model for reaching key publics who hold traditional ideologies typically perceived as incompatible with climate change science. We will discuss the results of our interactions with the leaders of our partnering organizations, their knowledge, perceptions, needs, and input in crafting effective messages for their audiences, through addressing both learners' affective and cognitive domains. For the informal education sector, CLiPSE utilized several open discussion and learning forums aimed to promote critical thinking and civil conversation about climate change. Focusing on Faith-based audiences, a key demographic, in the Southeast US, CLiPSE also conducted an online, moderated, author-attended book study, discussing the thoughts and ideas contained in the work, "Green Like God," by Jonathan Merritt. We will share the questions we faced as we focused on and learned about faith-based audiences, such as: What are the barriers and opportunities?; How do we break out of the assumptions that we have to find the common ground?; How do the audiences understand the issues?; How do we understand the issues?; What common language can we find?; What happens when we bringing the multiple the multiple identities of faith and science together within ourselves and those we are trying to build relationships with? We will also share the lessons we learned while attempting to answer these questions, such as the role of trust and key influentials/leaders in talking with target audiences, the importance of face-to-face dialog and relationships in trust building.

State Wildlife Action Plans as Tools for Adapting to a Continuously Changing Climate

NASA Astrophysics Data System (ADS)

Metivier, D. W.; Yocum, H.; Ray, A. J.

2015-12-01

Public land management plans are potentially powerful policies for building sustainability and adaptive capacity. Land managers are recognizing the need to respond to numerous climate change impacts on natural and human systems. For the first time, in 2015, the federal government required each state to incorporate climate change into their State Wildlife Action Plans (SWAP) as a condition for funding. As important land management tools, SWAPs have the potential to guide state agencies in shaping and implementing practices for climate change adaptation. Intended to be revised every ten years, SWAPs can change as conditions and understanding of climate change evolves. This study asks what practices are states using to integrate climate change, and how does this vary between states? To answer this question, we conducted a broad analysis among seven states (CO, MT, NE, ND, SD, UT, WY) and a more in-depth analysis of four states (CO, ND, SD, WY). We use seven key factors that represent best practices for incorporating climate change identified in the literature. These best practices are species prioritization, key habitats, threats, monitoring, partnerships and participation, identification of management options, and implementation of management options. The in-depth analysis focuses on how states are using climate change information for specific habitats addressed in the plans. We find that states are integrating climate change in many different ways, showing varying degrees of sophistication and preparedness. We summarize different practices and highlight opportunities to improve the effectiveness of plans through: communication tools across state lines and stakeholders, explicit targeting of key habitats, enforcement and monitoring progress and success, and conducting vulnerability analyses that incorporate topics beyond climate and include other drivers, trajectories, and implications of historic and future land-use change.

Evaluating the distribution of terrestrial dissolved organic matter in a complex coastal ecosystem using fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Yamashita, Youhei; Boyer, Joseph N.; Jaffé, Rudolf

2013-09-01

The coastal zone of the Florida Keys features the only living coral reef in the continental United States and as such represents a unique regional environmental resource. Anthropogenic pressures combined with climate disturbances such as hurricanes can affect the biogeochemistry of the region and threaten the health of this unique ecosystem. As such, water quality monitoring has historically been implemented in the Florida Keys, and six spatially distinct zones have been identified. In these studies however, dissolved organic matter (DOM) has only been studied as a quantitative parameter, and DOM composition can be a valuable biogeochemical parameter in assessing environmental change in coastal regions. Here we report the first data of its kind on the application of optical properties of DOM, in particular excitation emission matrix fluorescence with parallel factor analysis (EEM-PARAFAC), throughout these six Florida Keys regions in an attempt to assess spatial differences in DOM sources. Our data suggests that while DOM in the Florida Keys can be influenced by distant terrestrial environments such as the Everglades, spatial differences in DOM distribution were also controlled in part by local surface runoff/fringe mangroves, contributions from seasgrass communities, as well as the reefs and waters from the Florida Current. Application of principal component analysis (PCA) of the relative abundance of EEM-PARAFAC components allowed for a clear distinction between the sources of DOM (allochthonous vs. autochthonous), between different autochthonous sources and/or the diagenetic status of DOM, and further clarified contribution of terrestrial DOM in zones where levels of DOM were low in abundance. The combination between EEM-PARAFAC and PCA proved to be ideally suited to discern DOM composition and source differences in coastal zones with complex hydrology and multiple DOM sources.

The I.A.G./A.I.G. SEDIBUD (Sediment Budgets in Cold Environments) Program (2005 - 2017): Key activities and outcomes

NASA Astrophysics Data System (ADS)

Beylich, Achim A.

2017-04-01

Amplified climate change and ecological sensitivity of high-latitude and high-altitude cold climate environments has been highlighted as a key global environmental issue. Projected climate change in largely undisturbed cold regions is expected to alter melt-season duration and intensity, along with the number of extreme rainfall events, total annual precipitation and the balance between snowfall and rainfall. Similarly, changes to the thermal balance are expected to reduce the extent of permafrost and seasonal ground frost and increase active-layer depths. These combined effects will undoubtedly change Earth surface environments in cold regions and will alter the fluxes of sediments, solutes and nutrients. However, the absence of quantitative data and coordinated analysis to understand the sensitivity of the Earth surface environment are acute in cold regions. Contemporary cold climate environments generally provide the opportunity to identify solute and sedimentary systems where anthropogenic impacts are still less important than the effects of climate change. Accordingly, it is still possible to develop a library of baseline fluvial yields and sedimentary budgets before the natural environment is completely transformed. The SEDIBUD (Sediment Budgets in Cold Environments) Program, building on the European Science Foundation (ESF) Network SEDIFLUX (Sedimentary Source-to-Sink Fluxes in Cold Environments, since 2004) was formed in 2005 as a new Program (Working Group) of the International Association of Geomorphologists (I.A.G./A.I.G.) to address this still existing key knowledge gap. SEDIBUD (2005-2017) has currently about 400 members worldwide and the Steering Committee of this international program is composed of eleven scientists from ten different countries. The central research question of this global program is to: Assess and model the contemporary sedimentary fluxes in cold climates, with emphasis on both particulate and dissolved components. Research carried out at 56 defined SEDIBUD key test sites (selected catchment systems) varies by scientific program, logistics and available resources, but typically represent interdisciplinary collaborations of geomorphologists, hydrologists, ecologists, permafrost scientists and glaciologists with different levels of detail. SEDIBUD has developed a key set of primary research data requirements intended to incorporate results from these varied projects and allow quantitative analysis across the program. Defined SEDIBUD key test sites provide field data on annual climatic conditions, total discharge and particulate and dissolved fluxes and yields as well as information on other relevant denudational Earth surface processes. A number of selected key test sites are providing high-resolution data on climatic conditions, runoff and solute and sedimentary fluxes and yields, which - in addition to the annual data - contribute to the SEDIBUD metadata database. To support these coordinated efforts, the SEDIFLUX manual and a set of framework papers and book chapters have been produced to establish the integrative approach and common methods and data standards. Comparable field-datasets from different SEDIBUD key test sites are analyzed and integrated to address key research questions of the SEDIBUD program as defined in the SEDIBUD working group objective. A key SEDIBUD synthesis book was published in 2016 by the group and a synthesis key paper is currently in preparation. Detailed information on all SEDIBUD activities, outcomes and published products is found at http://www.geomorph.org/sedibud-working-group/.

A stochastic multicloud convective parameterization in the NCEP Climate Forecast System (CFSv2) : implementation and calibration.

NASA Astrophysics Data System (ADS)

Goswami, B. B.; Khouider, B.; Krishna, R. P. M.; Mukhopadhyay, P.; Majda, A.

2017-12-01

A stochastic multicloud (SMCM) cumulus parameterization is implemented in the National Centres for Environmental Predictions (NCEP) Climate Forecast System version 2 (CFSv2) model, named as the CFSsmcm model. We present here results from a systematic attempt to understand the CFSsmcm model's sensitivity to the SMCM parameters. To asses the model-sentivity to the different SMCM parameters, we have analized a set of 14 5-year long climate simulations produced by the CFSsmcm model. The model is found to be resilient to minor changes in the parameter values. The middle tropospheric dryness (MTD) and the stratiform cloud decay timescale are found to be most crucial parameters in the SMCM formulation in the CFSsmcm model.

Understanding Climate Uncertainty with an Ocean Focus

NASA Astrophysics Data System (ADS)

Tokmakian, R. T.

2009-12-01

Uncertainty in climate simulations arises from various aspects of the end-to-end process of modeling the Earth’s climate. First, there is uncertainty from the structure of the climate model components (e.g. ocean/ice/atmosphere). Even the most complex models are deficient, not only in the complexity of the processes they represent, but in which processes are included in a particular model. Next, uncertainties arise from the inherent error in the initial and boundary conditions of a simulation. Initial conditions are the state of the weather or climate at the beginning of the simulation and other such things, and typically come from observations. Finally, there is the uncertainty associated with the values of parameters in the model. These parameters may represent physical constants or effects, such as ocean mixing, or non-physical aspects of modeling and computation. The uncertainty in these input parameters propagates through the non-linear model to give uncertainty in the outputs. The models in 2020 will no doubt be better than today’s models, but they will still be imperfect, and development of uncertainty analysis technology is a critical aspect of understanding model realism and prediction capability. Smith [2002] and Cox and Stephenson [2007] discuss the need for methods to quantify the uncertainties within complicated systems so that limitations or weaknesses of the climate model can be understood. In making climate predictions, we need to have available both the most reliable model or simulation and a methods to quantify the reliability of a simulation. If quantitative uncertainty questions of the internal model dynamics are to be answered with complex simulations such as AOGCMs, then the only known path forward is based on model ensembles that characterize behavior with alternative parameter settings [e.g. Rougier, 2007]. The relevance and feasibility of using "Statistical Analysis of Computer Code Output" (SACCO) methods for examining uncertainty in ocean circulation due to parameter specification will be described and early results using the ocean/ice components of the CCSM climate model in a designed experiment framework will be shown. Cox, P. and D. Stephenson, Climate Change: A Changing Climate for Prediction, 2007, Science 317 (5835), 207, DOI: 10.1126/science.1145956. Rougier, J. C., 2007: Probabilistic Inference for Future Climate Using an Ensemble of Climate Model Evaluations, Climatic Change, 81, 247-264. Smith L., 2002, What might we learn from climate forecasts? Proc. Nat’l Academy of Sciences, Vol. 99, suppl. 1, 2487-2492 doi:10.1073/pnas.012580599.

Peer Victimization and Authoritative School Climate: A Multilevel Approach

ERIC Educational Resources Information Center

Cornell, Dewey; Shukla, Kathan; Konold, Timothy

2015-01-01

School climate is widely recognized as an important influence on peer victimization in schools. The purpose of this study is to examine how authoritative school climate theory provides a framework for conceptualizing 2 key features of school climate--disciplinary structure and student support--that are associated with 3 measures of peer…

Multilevel Multi-Informant Structure of the Authoritative School Climate Survey

ERIC Educational Resources Information Center

Konold, Timothy; Cornell, Dewey; Huang, Francis; Meyer, Patrick; Lacey, Anna; Nekvasil, Erin; Heilbrun, Anna; Shukla, Kathan

2014-01-01

The Authoritative School Climate Survey was designed to provide schools with a brief assessment of 2 key characteristics of school climate--disciplinary structure and student support--that are hypothesized to influence 2 important school climate outcomes--student engagement and prevalence of teasing and bullying in school. The factor structure of…

76 FR 17962 - Strengthening the Scientific Understanding of Climate Change Impacts on Freshwater Resources of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-31

... Understanding of Climate Change Impacts on Freshwater Resources of the United States AGENCY: U.S. Geological... Scientific Understanding of Climate Change Impacts on Freshwater Resources of the United States''. The report reviews key issues related to freshwater resource data and climate change and identifies next steps to...

Expanding the Foundation: Climate Change and Opportunities for Educational Research

ERIC Educational Resources Information Center

Henderson, Joseph; Long, David; Berger, Paul; Russell, Constance; Drewes, Andrea

2017-01-01

Human-caused climate change is a dominant global challenge. Unlike other disciplines and fields, there has as yet been only limited attention to climate change in educational research generally, and in educational foundations in particular. Education is key to assisting humanity in mitigating and adapting to climate change, and educational…

Global Climate Change: What Has Science Education Got to Do with It?

ERIC Educational Resources Information Center

Sharma, Ajay

2012-01-01

Despite a near universal consensus among scientists regarding the perils of climate change for human civilizations, climate change has not emerged as a key issue among science educators. This position paper advocates for the centrality of climate change in science education. Using Polanyi's critique of market in capitalist societies, it positions…

Academic Service Climate as a Source of Competitive Advantage: Leverage for University Administrators

ERIC Educational Resources Information Center

Martin, Angela; Kennedy, Barbara; Stocks, Belinda

2006-01-01

The psychological climate literature examines links between facets of climate, such as service orientation and a range of individual and organisational outcomes including work attitudes and performance. This study investigated the relationship between the service climate of an Australian university and outcomes important to its key stakeholders. A…

Swimming against the tide: resilience of a riverine turtle to recurrent extreme environmental events.

PubMed

Jergenson, Abigail M; Miller, David A W; Neuman-Lee, Lorin A; Warner, Daniel A; Janzen, Fredric J

2014-03-01

Extreme environmental events (EEEs) are likely to exert deleterious effects on populations. From 1996 to 2012 we studied the nesting dynamics of a riverine population of painted turtles (Chrysemys picta) that experienced seven years with significantly definable spring floods. We used capture-mark-recapture methods to estimate the relationships between more than 5 m and more than 6 m flood events and population parameters. Contrary to expectations, flooding was not associated with annual differences in survival, recruitment or annual population growth rates of the adult female segment of the population. These findings suggest that female C. picta exhibit resiliency to key EEE, which are expected to increase in frequency under climate change.

Influence of three common calibration metrics on the diagnosis of climate change impacts on water resources

NASA Astrophysics Data System (ADS)

Seiller, G.; Roy, R.; Anctil, F.

2017-04-01

Uncertainties associated to the evaluation of the impacts of climate change on water resources are broad, from multiple sources, and lead to diagnoses sometimes difficult to interpret. Quantification of these uncertainties is a key element to yield confidence in the analyses and to provide water managers with valuable information. This work specifically evaluates the influence of hydrological modeling calibration metrics on future water resources projections, on thirty-seven watersheds in the Province of Québec, Canada. Twelve lumped hydrologic models, representing a wide range of operational options, are calibrated with three common objective functions derived from the Nash-Sutcliffe efficiency. The hydrologic models are forced with climate simulations corresponding to two RCP, twenty-nine GCM from CMIP5 (Coupled Model Intercomparison Project phase 5) and two post-treatment techniques, leading to future projections in the 2041-2070 period. Results show that the diagnosis of the impacts of climate change on water resources are quite affected by the hydrologic models selection and calibration metrics. Indeed, for the four selected hydrological indicators, dedicated to water management, parameters from the three objective functions can provide different interpretations in terms of absolute and relative changes, as well as projected changes direction and climatic ensemble consensus. The GR4J model and a multimodel approach offer the best modeling options, based on calibration performance and robustness. Overall, these results illustrate the need to provide water managers with detailed information on relative changes analysis, but also absolute change values, especially for hydrological indicators acting as security policy thresholds.

Observing climate change trends in ocean biogeochemistry: when and where.

PubMed

Henson, Stephanie A; Beaulieu, Claudie; Lampitt, Richard

2016-04-01

Understanding the influence of anthropogenic forcing on the marine biosphere is a high priority. Climate change-driven trends need to be accurately assessed and detected in a timely manner. As part of the effort towards detection of long-term trends, a network of ocean observatories and time series stations provide high quality data for a number of key parameters, such as pH, oxygen concentration or primary production (PP). Here, we use an ensemble of global coupled climate models to assess the temporal and spatial scales over which observations of eight biogeochemically relevant variables must be made to robustly detect a long-term trend. We find that, as a global average, continuous time series are required for between 14 (pH) and 32 (PP) years to distinguish a climate change trend from natural variability. Regional differences are extensive, with low latitudes and the Arctic generally needing shorter time series (<~30 years) to detect trends than other areas. In addition, we quantify the 'footprint' of existing and planned time series stations, that is the area over which a station is representative of a broader region. Footprints are generally largest for pH and sea surface temperature, but nevertheless the existing network of observatories only represents 9-15% of the global ocean surface. Our results present a quantitative framework for assessing the adequacy of current and future ocean observing networks for detection and monitoring of climate change-driven responses in the marine ecosystem. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Modeling pN2 through Geological Time: Implications for Planetary Climates and Atmospheric Biosignatures.

PubMed

Stüeken, E E; Kipp, M A; Koehler, M C; Schwieterman, E W; Johnson, B; Buick, R

2016-12-01

Nitrogen is a major nutrient for all life on Earth and could plausibly play a similar role in extraterrestrial biospheres. The major reservoir of nitrogen at Earth's surface is atmospheric N 2 , but recent studies have proposed that the size of this reservoir may have fluctuated significantly over the course of Earth's history with particularly low levels in the Neoarchean-presumably as a result of biological activity. We used a biogeochemical box model to test which conditions are necessary to cause large swings in atmospheric N 2 pressure. Parameters for our model are constrained by observations of modern Earth and reconstructions of biomass burial and oxidative weathering in deep time. A 1-D climate model was used to model potential effects on atmospheric climate. In a second set of tests, we perturbed our box model to investigate which parameters have the greatest impact on the evolution of atmospheric pN 2 and consider possible implications for nitrogen cycling on other planets. Our results suggest that (a) a high rate of biomass burial would have been needed in the Archean to draw down atmospheric pN 2 to less than half modern levels, (b) the resulting effect on temperature could probably have been compensated by increasing solar luminosity and a mild increase in pCO 2 , and (c) atmospheric oxygenation could have initiated a stepwise pN 2 rebound through oxidative weathering. In general, life appears to be necessary for significant atmospheric pN 2 swings on Earth-like planets. Our results further support the idea that an exoplanetary atmosphere rich in both N 2 and O 2 is a signature of an oxygen-producing biosphere. Key Words: Biosignatures-Early Earth-Planetary atmospheres. Astrobiology 16, 949-963.

Can integrative catchment management mitigate future water quality issues caused by climate change and socio-economic development?

NASA Astrophysics Data System (ADS)

Honti, Mark; Schuwirth, Nele; Rieckermann, Jörg; Stamm, Christian

2017-03-01

The design and evaluation of solutions for integrated surface water quality management requires an integrated modelling approach. Integrated models have to be comprehensive enough to cover the aspects relevant for management decisions, allowing for mapping of larger-scale processes such as climate change to the regional and local contexts. Besides this, models have to be sufficiently simple and fast to apply proper methods of uncertainty analysis, covering model structure deficits and error propagation through the chain of sub-models. Here, we present a new integrated catchment model satisfying both conditions. The conceptual iWaQa model was developed to support the integrated management of small streams. It can be used to predict traditional water quality parameters, such as nutrients and a wide set of organic micropollutants (plant and material protection products), by considering all major pollutant pathways in urban and agricultural environments. Due to its simplicity, the model allows for a full, propagative analysis of predictive uncertainty, including certain structural and input errors. The usefulness of the model is demonstrated by predicting future surface water quality in a small catchment with mixed land use in the Swiss Plateau. We consider climate change, population growth or decline, socio-economic development, and the implementation of management strategies to tackle urban and agricultural point and non-point sources of pollution. Our results indicate that input and model structure uncertainties are the most influential factors for certain water quality parameters. In these cases model uncertainty is already high for present conditions. Nevertheless, accounting for today's uncertainty makes management fairly robust to the foreseen range of potential changes in the next decades. The assessment of total predictive uncertainty allows for selecting management strategies that show small sensitivity to poorly known boundary conditions. The identification of important sources of uncertainty helps to guide future monitoring efforts and pinpoints key indicators, whose evolution should be closely followed to adapt management. The possible impact of climate change is clearly demonstrated by water quality substantially changing depending on single climate model chains. However, when all climate trajectories are combined, the human land use and management decisions have a larger influence on water quality against a time horizon of 2050 in the study.

Abrupt Climate Change: the View from the Past, the Present and the Future

NASA Astrophysics Data System (ADS)

White, J. W. C.

2014-12-01

Climate is changing as humans put more and more greenhouse gases into the atmosphere. With CO2 levels today around 400ppm, we are clearly committed to far more climate change, both in the near term, and well beyond our children's future. A key question is how that change will occur. Abrupt climate changes are those that exceed our expectations, preparedness, and ability to adapt. Such changes challenge us economically, physically, and socially. This talk will draw upon results from ice core research over the past twenty years, as well as a new NRC report on abrupt climate change in order to address abrupt change, as seen in the past in ice cores, as seen today in key environmental systems upon which humans depend, and what is may be coming in the future.

Climate change and tropical biodiversity: a new focus.

PubMed

Brodie, Jedediah; Post, Eric; Laurance, William F

2012-03-01

Considerable efforts are focused on the consequences of climate change for tropical rainforests. However, potentially the greatest threats to tropical biodiversity (synergistic interactions between climatic changes and human land use) remain understudied. Key concerns are that aridification could increase the accessibility of previously non-arable or remote lands, elevate fire impacts and exacerbate ecological effects of habitat disturbance. The growing climatic change literature often fails to appreciate that, in coming decades, climate-land use interactions might be at least as important as abiotic changes per se for the fate of tropical biodiversity. In this review, we argue that protected area expansion along key ecological gradients, regulation of human-lit fires, strategic forest-carbon financing and re-evaluations of agricultural and biofuel subsidies could ameliorate some of these synergistic threats. Copyright © 2011 Elsevier Ltd. All rights reserved.

Is There a Difference? The Impact of Campus Climate on Sexual Minority and Gender Minority Students' Levels of Outness

ERIC Educational Resources Information Center

di Bartolo, Adriana N.

2013-01-01

Key scholars have studied campus climate, and often these climate studies are done through the lens of race and racial issues on campus. A few studies have explored the interaction between campus climate and sexual and gender minority students. However, those studies, like the climate studies through a racial lens, found that lesbian, gay,…

Testing statistical self-similarity in the topology of river networks

USGS Publications Warehouse

Troutman, Brent M.; Mantilla, Ricardo; Gupta, Vijay K.

2010-01-01

Recent work has demonstrated that the topological properties of real river networks deviate significantly from predictions of Shreve's random model. At the same time the property of mean self-similarity postulated by Tokunaga's model is well supported by data. Recently, a new class of network model called random self-similar networks (RSN) that combines self-similarity and randomness has been introduced to replicate important topological features observed in real river networks. We investigate if the hypothesis of statistical self-similarity in the RSN model is supported by data on a set of 30 basins located across the continental United States that encompass a wide range of hydroclimatic variability. We demonstrate that the generators of the RSN model obey a geometric distribution, and self-similarity holds in a statistical sense in 26 of these 30 basins. The parameters describing the distribution of interior and exterior generators are tested to be statistically different and the difference is shown to produce the well-known Hack's law. The inter-basin variability of RSN parameters is found to be statistically significant. We also test generator dependence on two climatic indices, mean annual precipitation and radiative index of dryness. Some indication of climatic influence on the generators is detected, but this influence is not statistically significant with the sample size available. Finally, two key applications of the RSN model to hydrology and geomorphology are briefly discussed.

Surfing parameter hyperspaces under climate change scenarios to design future rice ideotypes.

PubMed

Paleari, Livia; Movedi, Ermes; Cappelli, Giovanni; Wilson, Lloyd T; Confalonieri, Roberto

2017-11-01

Growing food crops to meet global demand and the search for more sustainable cropping systems are increasing the need for new cultivars in key production areas. This study presents the identification of rice traits putatively producing the largest yield benefits in five areas that markedly differ in terms of environmental conditions in the Philippines, India, China, Japan and Italy. The ecophysiological model WARM and sensitivity analysis techniques were used to evaluate phenotypic traits involved with light interception, photosynthetic efficiency, tolerance to abiotic stressors, resistance to fungal pathogens and grain quality. The analysis involved only model parameters that have a close relationship with phenotypic traits breeders are working on, to increase the in vivo feasibility of selected ideotypes. Current climate and future projections were considered, in the light of the resources required by breeding programs and of the role of weather variables in the identification of promising traits. Results suggest that breeding for traits involved with disease resistance, and tolerance to cold- and heat-induced spikelet sterility could provide benefits similar to those obtained from the improvement of traits involved with canopy structure and photosynthetic efficiency. In contrast, potential benefits deriving from improved grain quality traits are restricted by weather variability and markedly affected by G × E interactions. For this reason, district-specific ideotypes were identified using a new index accounting for both their productivity and feasibility. © 2017 John Wiley & Sons Ltd.

Phytoplankton and Climate

NASA Technical Reports Server (NTRS)

Moisan, John R.

2009-01-01

Ocean phytoplankton supply about half of the oxygen that humans utilize to sustain life. In this lecture, we will explore how phytoplankton plays a critical role in modulating the Earth's climate. These tiny organisms are the base of the Ocean's food web. They can modulate the rate at which solar heat is absorbed by the ocean, either through direct absorption or through production of highly scattering cellular coverings. They take up and help sequester carbon dioxide, a key greenhouse gas that modulated the Earth's climate. They are the source of cloud nucleation gases that are key to cloud formation/processes. They are also able to modify the nutrient budgets of the ocean through active uptake of inert atmospheric nitrogen. Climate variations have a pronounced impact on phytoplankton dynamics. Long term variations in the climate have been studied through geological interpretations on its influence on phytoplankton populations. The presentation will focus on presenting the numerous linkages that have been observed between climate and phytoplankton and further discuss how present climate change scenarios are likely to impact phytoplankton populations as well as present findings from several studies that have tried to understand how the climate might react to the feedbacks from these numerous climate-phytop|ankton linkages.

PREFACE: The IARU International Scientific Congress on Climate Change: Global Risks, Challenges and Decisions (10-12 March, Copenhagen, Denmark)

NASA Astrophysics Data System (ADS)

2009-01-01

In an attempt to make the main results from the Congress on Climate Change: Global Risk, Challenges and Decisions available to the public as early as possible, the steering committee decided to publish all talks and posters presented at the Congress in this unique collection of abstracts, in time for the conference Further to the abstract collection the Congress will publish two more products in the near future as described in the following; a synthesis report with the main conclusions, and a book aimed at an academic audience 1 Two Products from the Congress Two products are being produced based on the presentations and discussions at the Congress The first product will be a synthesis report of the main conclusions from the Congress The synthesis report will be ready in June 2009 The synthesis has the purpose of explaining the current state of understanding man-made climate change and what we can do about it to the non-scientist, ie politicians, media and interested citizens The synthesis will build on the messages presented to the Danish Prime Minister, Mr Anders Fogh Rasmussen, host of the COP15, at the closing session of the Congress These six messages were drafted by the Writing Team (see below) based on input from the session chairs and a reading of the 1600+ abstracts submitted to the Congress The second product is a book aimed at an academic audience The book will include more detailed scientific results from all of the sessions and will be published by Cambridge University Press in 2010 It will be an extension and elaboration of the synthesis report Who's writing the Synthesis Report and the Book? A Writing Team consisting of 12 internationally respected scientists from all continents is responsible for developing both products When the synthesis report has been drafted by the Writing Team, it will be discussed in the Scientific Steering Committee of the Congress and reviewed by the Earth System Science Partnership (ESSP) and a group of experts identified by the IARU universities In keeping with normal scientific practice, a procedure for producing the synthesis report that has been adopted optimises the chances of arriving at a product that will receive a broad backing from the scientific community as being a message that can be sent to the non-scientific community and that explains current understanding in climate change science The Writing Team will also be responsible for writing the book Members of the Writing Team (in alphabetical order) Professor Joe Alcamo, University of Stellenbosch Dr Terry Barker, Cambridge University Professor Daniel Kammen, University of California - Berkeley Professor Rik Leemans, Environmental Systems Analysis Group, Wageningen University Professor Diana Liverman, Oxford University Professor Mohan Munasinghe, Chairman, Munasinghe Institute for Development (MIND) Dr Balgis Osman-Elasha, Higher Council for Environment and Natural Resources (HCENR), Sudan Professor Katherine Richardson, University of Copenhagen Professor John Schellnhuber, Potsdam Institute for Climate Impact Research and visiting professor at the University of Oxford Professor Will Steffen, Australian National University Professor Lord Nicholas Stern, London School of Economics and Political Science (LSE) Professor Ole Wæver, University of Copenhagen 2 Key Messages from the Congress Key Message 1: Climatic Trends Recent observations confirm that, given high rates of observed emissions, the worst-case IPCC scenario trajectories (or even worse) are being realized For many key parameters, the climate system is already moving beyond the patterns of natural variability within which our society and economy have developed and thrived These parameters include global mean surface temperature, sea-level rise, ocean and ice sheet dynamics, ocean acidification, and extreme climatic events There is a significant risk that many of the trends will accelerate, leading to an increasing risk of abrupt or irreversible climatic shifts Key Message 2: Social disruption The research community is providing much more information to support discussions on 'dangerous climate change' Recent observations show that societies are highly vulnerable to even modest levels of climate change, with poor nations and communities particularly at risk Temperature rises above 2°C will be very difficult for contemporary societies to cope with, and will increase the level of climate disruption through the rest of the century Key Message 3: Long-Term Strategy Rapid, sustained, and effective mitigation based on coordinated global and regional action is required to avoid 'dangerous climate change' regardless of how it is defined Weaker targets for 2020 increase the risk of crossing tipping points and make the task of meeting 2050 targets more difficult Delay in initiating effective mitigation actions increases significantly the long-term social and economic costs of both adaptation and mitigation Key Message 4: Equity Dimensions Climate change is having, and will have, strongly differential effects on people within and between countries and regions, on this generation and future generations, and on human societies and the natural world An effective, well-funded adaptation safety net is required for those people least capable of coping with climate change impacts, and a common but differentiated mitigation strategy is needed to protect the poor and most vulnerable Key Message 5: Inaction is Inexcusable There is no excuse for inaction We already have many tools and approaches - economic, technological, behavioral, management - to deal effectively with the climate change challenge But they must be vigorously and widely implemented to achieve the societal transformation required to decarbonize economies A wide range of benefits will flow from a concerted effort to alter our energy economy now, including sustainable energy job growth, reductions in the health and economic costs of climate change, and the restoration of ecosystems and revitalization of ecosystem services Key Message 6: Meeting the Challenge To achieve the societal transformation required to meet the climate change challenge, we must overcome a number of significant constraints and seize critical opportunities These include reducing inertia in social and economic systems; building on a growing public desire for governments to act on climate change; removing implicit and explicit subsidies; reducing the influence of vested interests that increase emissions and reduce resilience; enabling the shifts from ineffective governance and weak institutions to innovative leadership in government, the private sector and civil society; and engaging society in the transition to norms and practices that foster sustainability The editors of the volume are all the session chairs: Professor Agus Sari Dr Aled Jones Science Manager Anders Viksø-Nielsen Dr Andreas Barkman Professor Anette Reenberg Professor Ann Henderson-Sellers Professor Anthony J McMichael Dr Anthony Patt Dr Bette Otto-Bliesner Dr Cameron Hepburn Dr Carlos Nobre Dr Carol Turley Dr Chris Hope Professor Chris Turney Professor Claus Felby Professor Coleen Vogel Professor Dale Jamieson Professor Daniel M Kammen Senior Scientist Detlef F Sprinz Professor Diana Ürge-Vorsatz Professor Dorthe Dahl-Jensen PhD Fatima Denton Director Generel Frances Seymour Dr Frank Jotzo Professor Harold Mooney Director Henrik Bindslev Mr Jamie Pittock Professor Jacquie Burgess Dr James E Hansen Professor Jiahua Pan Dr Jill Jäger Professor Jim Skea Professor Johan Rockström Dr John Christensen Professor John Mitchell Professor John R Porter Professor Joyeeta Gupta Professor Jørgen E Olesen Professor Karen O'Brien Dr Kazuhiko Takeuchi Dr Katrine Krogh Andersen Professor Keith Paustian Professor Ken Caldeira Professor Kevin Anderson Dr Koko Warner Professor Konrad Steffen Professor Liping Zhou Professor Louise Fresco Professor Maria Carmen Lemos Professor Mark Ashton Dr Mark Stafford-Smith Dr Martin Claussen Dr Martin Visbeck Professor Mary Scholes Professor Masahide Kimoto Professor Matthew England Dr Maxwell Boykoff Dr Michael Raupach Professor Nathan Bindoff Professor Nicolas Gruber Professor Niels Elers Koch Professor Ole John Nielsen Professor Ole Wæver Professor Oran Young Dr Pamela Matson Dr Paul Baer Professor Paul Leadley Dr Pep Canadell Professor Pete Smith Professor Peter Gregory Professor Pier Vellinga Dr Rik Leemans Dr Roberto Bertollini Professor Roberto S Rodriguez Professor Scott Denning Dr Sivan Kartha Dr Thomas Downing Dr Tariq Banuri Professor Thomas Heyd Professor Tim Lenton Professor Timmons Roberts Professor Torkil Jønch Clausen Professor Warwick McKibbin Professor Wim C Turkenburg

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Sokolov, Andrei; Schlosser, Adam; Scott, Jeffery; Gao, Xiang

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia.

Climate change : expert opinion on the economics of policy options to address climate change

DOT National Transportation Integrated Search

2008-05-01

Panelists identified key strengths and limitations of alternative policy approaches that should be of assistance to the Congress in weighing the potential benefits and costs of different policies for addressing climate change. Many panelists said tha...

Homogenization of vegetation structure across residential neighborhoods: effects of climate, urban morphology, and socio-economics

EPA Science Inventory

Climate is a key driver regulating vegetation structure across rural ecosystems. In urban ecosystems, multiple interactions between humans and the environment can have homogenizing influences, confounding the relationship between vegetation structure and climate. In fact, vegetat...

Extrinsic regime shifts drive abrupt changes in regeneration dynamics at upper treeline in the Rocky Mountains, U.S.A.

PubMed

Elliott, Grant P

2012-07-01

Given the widespread and often dramatic influence of climate change on terrestrial ecosystems, it is increasingly common for abrupt threshold changes to occur, yet explicitly testing for climate and ecological regime shifts is lacking in climatically sensitive upper treeline ecotones. In this study, quantitative evidence based on empirical data is provided to support the key role of extrinsic, climate-induced thresholds in governing the spatial and temporal patterns of tree establishment in these high-elevation environments. Dendroecological techniques were used to reconstruct a 420-year history of regeneration dynamics within upper treeline ecotones along a latitudinal gradient (approximately 44-35 degrees N) in the Rocky Mountains. Correlation analysis was used to assess the possible influence of minimum and maximum temperature indices and cool-season (November-April) precipitation on regional age-structure data. Regime-shift analysis was used to detect thresholds in tree establishment during the entire period of record (1580-2000), temperature variables significantly Correlated with establishment during the 20th century, and cool-season precipitation. Tree establishment was significantly correlated with minimum temperature during the spring (March-May) and cool season. Regime-shift analysis identified an abrupt increase in regional tree establishment in 1950 (1950-1954 age class). Coincident with this period was a shift toward reduced cool-season precipitation. The alignment of these climate conditions apparently triggered an abrupt increase in establishment that was unprecedented during the period of record. Two main findings emerge from this research that underscore the critical role of climate in governing regeneration dynamics within upper treeline ecotones. (1) Regional climate variability is capable of exceeding bioclimatic thresholds, thereby initiating synchronous and abrupt changes in the spatial and temporal patterns of tree establishment at broad regional scales. (2) The importance of climate parameters exceeding critical threshold values and triggering a regime shift in tree establishment appears to be contingent on the alignment of favorable temperature and moisture regimes. This research suggests that threshold changes in the climate system can fundamentally alter regeneration dynamics within upper treeline ecotones and, through the use of regime-shift analysis, reveals important climate-vegetation linkages.

Effects of climate change on Forest Service strategic goals

Treesearch

Forest Service U.S. Department of Agriculture

2010-01-01

Climate change affects forests and grasslands in many ways. Changes in temperature and precipitation affect plant productivity as well as some species' habitat. Changes in key climate variables affect the length of the fire season and the seasonality of National Forest hydrological regimes. Also, invasive species tend to adapt to climate change more easily and...

Forest environmental investments and implications for climate change mitigation.

Treesearch

Ralph J. Alig; Lucas S. Bair

2006-01-01

Forest environmental conditions are affected by climate change, but investments in forest environmental quality can be used as part of the climate change mitigation strategy. A key question involving the potential use of forests to store more carbon as part of climate change mitigation is the impact of forest investments on the timing and quantity of forest volumes...

The Development of a New Comprehensive Measure of School Climate and Associations with School Leadership

ERIC Educational Resources Information Center

Maier, Christopher J.

2017-01-01

A positive school climate has been related to increase in student achievement, teacher satisfaction, and teacher retention. One of the most influential aspects of developing a positive school climate hinges on principal leadership style. The Development of a New Comprehensive Measure of School Climate assesses six key areas related to school…

Losing the Lake: Simulations to Promote Gains in Student Knowledge and Interest about Climate Change

ERIC Educational Resources Information Center

Nussbaum, E. Michael; Owens, Marissa C.; Sinatra, Gale M.; Rehmat, Abeera P.; Cordova, Jacqueline R.; Ahmad, Sajjad; Harris, Fred C., Jr.; Dascalu, Sergiu M.

2015-01-01

Climate change literacy plays a key role in promoting sound political decisions and promoting sustainable consumption patterns. Based on evidence suggesting that student understanding and interest in climate change is best accomplished through studying local effects, we developed a simulation/game exploring the impact of climate change on the…

Hillslope characterization: Identifying key controls on local-scale plant communities' distribution using remote sensing and subsurface data fusion.

NASA Astrophysics Data System (ADS)

Falco, N.; Wainwright, H. M.; Dafflon, B.; Leger, E.; Peterson, J.; Steltzer, H.; Wilmer, C.; Williams, K. H.; Hubbard, S. S.

2017-12-01

Mountainous watershed systems are characterized by extreme heterogeneity in hydrological and pedological properties that influence biotic activities, plant communities and their dynamics. To gain predictive understanding of how ecosystem and watershed system evolve under climate change, it is critical to capture such heterogeneity and to quantify the effect of key environmental variables such as topography, and soil properties. In this study, we exploit advanced geophysical and remote sensing techniques - coupled with machine learning - to better characterize and quantify the interactions between plant communities' distribution and subsurface properties. First, we have developed a remote sensing data fusion framework based on the random forest (RF) classification algorithm to estimate the spatial distribution of plant communities. The framework allows the integration of both plant spectral and structural information, which are derived from multispectral satellite images and airborne LiDAR data. We then use the RF method to evaluate the estimated plant community map, exploiting the subsurface properties (such as bedrock depth, soil moisture and other properties) and geomorphological parameters (such as slope, curvature) as predictors. Datasets include high-resolution geophysical data (electrical resistivity tomography) and LiDAR digital elevation maps. We demonstrate our approach on a mountain hillslope and meadow within the East River watershed in Colorado, which is considered to be a representative headwater catchment in the Upper Colorado Basin. The obtained results show the existence of co-evolution between above and below-ground processes; in particular, dominant shrub communities in wet and flat areas. We show that successful integration of remote sensing data with geophysical measurements allows identifying and quantifying the key environmental controls on plant communities' distribution, and provides insights into their potential changes in the future climate conditions.

An end-users oriented methodology for enhancing the integration of knowledge on soil-water-sediment systems in River Basin Management: an illustration from the AquaTerra project.

PubMed

Merly, Corinne; Chapman, Antony; Mouvet, Christophe

2012-01-01

Research results in environmental and socio-economic sciences are often under-used by stakeholders involved in the management of natural resources. To minimise this gap, the FP6 EU interdisciplinary project AquaTerra (AT) developed an end-users' integration methodology in order to ensure that the data, knowledge and tools related to the soil-water-sediment system that were generated by the project were delivered in a meaningful way for end-users, thus improving their uptake. The methodology and examples of its application are presented in this paper. From the 408 project deliverables, 96 key findings were identified, 53 related to data and knowledge, and 43 describing advanced tools. River Basin Management (RBM) stakeholders workshops identified 8 main RBM issues and 25 specific stakeholders' questions related to RBM which were classified into seven groups of cross-cutting issues, namely scale, climate change, non-climatic change, the need for systemic approaches, communication and participation, international and inter-basin coordination and collaboration, and the implementation of the Water Framework Directive. The integration methodology enabled an assessment of how AT key findings meet stakeholders' demands, and for each main RBM issue and for each specific question, described the added-value of the AT project in terms of knowledge and tools generated, key parameters to consider, and recommendations that can be made to stakeholders and the wider scientific community. Added value and limitations of the integration methodology and its outcomes are discussed and recommendations are provided to further improve integration methodology and bridge the gaps between scientific research data and their potential uptake by end-users.

The Role of Sea Ice in 2 x CO2 Climate Model Sensitivity. Part 2; Hemispheric Dependencies

NASA Technical Reports Server (NTRS)

Rind, D.; Healy, R.; Parkinson, C.; Martinson, D.

1997-01-01

How sensitive are doubled CO2 simulations to GCM control-run sea ice thickness and extent? This issue is examined in a series of 10 control-run simulations with different sea ice and corresponding doubled CO2 simulations. Results show that with increased control-run sea ice coverage in the Southern Hemisphere, temperature sensitivity with climate change is enhanced, while there is little effect on temperature sensitivity of (reasonable) variations in control-run sea ice thickness. In the Northern Hemisphere the situation is reversed: sea ice thickness is the key parameter, while (reasonable) variations in control-run sea ice coverage are of less importance. In both cases, the quantity of sea ice that can be removed in the warmer climate is the determining factor. Overall, the Southern Hemisphere sea ice coverage change had a larger impact on global temperature, because Northern Hemisphere sea ice was sufficiently thick to limit its response to doubled CO2, and sea ice changes generally occurred at higher latitudes, reducing the sea ice-albedo feedback. In both these experiments and earlier ones in which sea ice was not allowed to change, the model displayed a sensitivity of -0.02 C global warming per percent change in Southern Hemisphere sea ice coverage.

Slow science: the value of long ocean biogeochemistry records

PubMed Central

Henson, Stephanie A.

2014-01-01

Sustained observations (SOs) have provided invaluable information on the ocean's biology and biogeochemistry for over 50 years. They continue to play a vital role in elucidating the functioning of the marine ecosystem, particularly in the light of ongoing climate change. Repeated, consistent observations have provided the opportunity to resolve temporal and/or spatial variability in ocean biogeochemistry, which has driven exploration of the factors controlling biological parameters and processes. Here, I highlight some of the key breakthroughs in biological oceanography that have been enabled by SOs, which include areas such as trophic dynamics, understanding variability, improved biogeochemical models and the role of ocean biology in the global carbon cycle. In the near future, SOs are poised to make progress on several fronts, including detecting climate change effects on ocean biogeochemistry, high-resolution observations of physical–biological interactions and greater observational capability in both the mesopelagic zone and harsh environments, such as the Arctic. We are now entering a new era for biological SOs, one in which our motivations have evolved from the need to acquire basic understanding of the ocean's state and variability, to a need to understand ocean biogeochemistry in the context of increasing pressure in the form of climate change, overfishing and eutrophication. PMID:25157192

Robust climate policies under uncertainty: a comparison of robust decision making and info-gap methods.

PubMed

Hall, Jim W; Lempert, Robert J; Keller, Klaus; Hackbarth, Andrew; Mijere, Christophe; McInerney, David J

2012-10-01

This study compares two widely used approaches for robustness analysis of decision problems: the info-gap method originally developed by Ben-Haim and the robust decision making (RDM) approach originally developed by Lempert, Popper, and Bankes. The study uses each approach to evaluate alternative paths for climate-altering greenhouse gas emissions given the potential for nonlinear threshold responses in the climate system, significant uncertainty about such a threshold response and a variety of other key parameters, as well as the ability to learn about any threshold responses over time. Info-gap and RDM share many similarities. Both represent uncertainty as sets of multiple plausible futures, and both seek to identify robust strategies whose performance is insensitive to uncertainties. Yet they also exhibit important differences, as they arrange their analyses in different orders, treat losses and gains in different ways, and take different approaches to imprecise probabilistic information. The study finds that the two approaches reach similar but not identical policy recommendations and that their differing attributes raise important questions about their appropriate roles in decision support applications. The comparison not only improves understanding of these specific methods, it also suggests some broader insights into robustness approaches and a framework for comparing them. © 2012 RAND Corporation.

Effect of sequential fermentations and grape cultivars on volatile compounds and sensory profiles of Danish wines.

PubMed

Liu, Jing; Arneborg, Nils; Toldam-Andersen, Torben B; Petersen, Mikael A; Bredie, Wender Lp

2017-08-01

There has been an increasing interest in the use of selected non-Saccharomyces yeasts in co-culture with Saccharomyces cerevisiae. In this work, three non-Saccharomyces yeast strains (Metschnikowia viticola, Metschnikowia fructicola and Hanseniaspora uvarum) indigenously isolated in Denmark were used in sequential fermentations with S. cerevisiae on three cool-climate grape cultivars, Bolero, Rondo and Regent. During the fermentations, the yeast growth was determined as well as key oenological parameters, volatile compounds and sensory properties of finished rosé wines. The different non-Saccharomyces strains and cool-climate grape cultivars produced wines with a distinctive aromatic profile. A total of 67 volatile compounds were identified, including 43 esters, 14 alcohols, five acids, two ketones, a C13-norisoprenoid, a lactone and a sulfur compound. The use of M. viticola in sequential fermentation with S. cerevisiae resulted in richer berry and fruity flavours in wines. The sensory plot showed a more clear separation among wine samples by grape cultivars compared with yeast strains. Knowledge on the influence of indigenous non-Saccharomyces strains and grape cultivars on the flavour generation contributed to producing diverse wines in cool-climate wine regions. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Key ecological responses to nitrogen are altered by climate change

USGS Publications Warehouse

Greaver, T.L.; Clark, C.M.; Compton, J.E.; Vallano, D.; Talhelm, A. F.; Weaver, C.P.; Band, L.E.; Baron, Jill S.; Davidson, E.A.; Tague, C.L.; Felker-Quinn, E.; Lynch, J.A.; Herrick, J.D.; Liu, L.; Goodale, C.L.; Novak, K. J.; Haeuber, R. A.

2016-01-01

Climate change and anthropogenic nitrogen deposition are both important ecological threats. Evaluating their cumulative effects provides a more holistic view of ecosystem vulnerability to human activities, which would better inform policy decisions aimed to protect the sustainability of ecosystems. Our knowledge of the cumulative effects of these stressors is growing, but we lack an integrated understanding. In this Review, we describe how climate change alters key processes in terrestrial and freshwater ecosystems related to nitrogen cycling and availability, and the response of ecosystems to nitrogen addition in terms of carbon cycling, acidification and biodiversity.

Key ecological responses to nitrogen are altered by climate change

NASA Astrophysics Data System (ADS)

Greaver, T. L.; Clark, C. M.; Compton, J. E.; Vallano, D.; Talhelm, A. F.; Weaver, C. P.; Band, L. E.; Baron, J. S.; Davidson, E. A.; Tague, C. L.; Felker-Quinn, E.; Lynch, J. A.; Herrick, J. D.; Liu, L.; Goodale, C. L.; Novak, K. J.; Haeuber, R. A.

2016-09-01

Climate change and anthropogenic nitrogen deposition are both important ecological threats. Evaluating their cumulative effects provides a more holistic view of ecosystem vulnerability to human activities, which would better inform policy decisions aimed to protect the sustainability of ecosystems. Our knowledge of the cumulative effects of these stressors is growing, but we lack an integrated understanding. In this Review, we describe how climate change alters key processes in terrestrial and freshwater ecosystems related to nitrogen cycling and availability, and the response of ecosystems to nitrogen addition in terms of carbon cycling, acidification and biodiversity.

Classification of climate-change-induced stresses on biological diversity.

PubMed

Geyer, Juliane; Kiefer, Iris; Kreft, Stefan; Chavez, Veronica; Salafsky, Nick; Jeltsch, Florian; Ibisch, Pierre L

2011-08-01

Conservation actions need to account for and be adapted to address changes that will occur under global climate change. The identification of stresses on biological diversity (as defined in the Convention on Biological Diversity) is key in the process of adaptive conservation management. We considered any impact of climate change on biological diversity a stress because such an effect represents a change (negative or positive) in key ecological attributes of an ecosystem or parts of it. We applied a systemic approach and a hierarchical framework in a comprehensive classification of stresses to biological diversity that are caused directly by global climate change. Through analyses of 20 conservation sites in 7 countries and a review of the literature, we identified climate-change-induced stresses. We grouped the identified stresses according to 3 levels of biological diversity: stresses that affect individuals and populations, stresses that affect biological communities, and stresses that affect ecosystem structure and function. For each stress category, we differentiated 3 hierarchical levels of stress: stress class (thematic grouping with the coarsest resolution, 8); general stresses (thematic groups of specific stresses, 21); and specific stresses (most detailed definition of stresses, 90). We also compiled an overview of effects of climate change on ecosystem services using the categories of the Millennium Ecosystem Assessment and 2 additional categories. Our classification may be used to identify key climate-change-related stresses to biological diversity and may assist in the development of appropriate conservation strategies. The classification is in list format, but it accounts for relations among climate-change-induced stresses. © 2011 Society for Conservation Biology.

Changing Permafrost in the Arctic and its Global Effects in the 21st Century (PAGE21): A very large international and integrated project to measure the impact of permafrost degradation on the climate system

NASA Astrophysics Data System (ADS)

Lantuit, Hugues; Boike, Julia; Dahms, Melanie; Hubberten, Hans-Wolfgang

2013-04-01

The northern permafrost region contains approximately 50% of the estimated global below-ground organic carbon pool and more than twice as much as is contained in the current atmos-pheric carbon pool. The sheer size of this carbon pool, together with the large amplitude of predicted arctic climate change im-plies that there is a high potential for global-scale feedbacks from arctic climate change if these carbon reservoirs are desta-bilized. Nonetheless, significant gaps exist in our current state of knowledge that prevent us from producing accurate assess-ments of the vulnerability of the arctic permafrost to climate change, or of the implications of future climate change for global greenhouse gas (GHG) emissions. Specifically: • Our understanding of the physical and biogeochemical processes at play in permafrost areas is still insuffi-cient in some key aspects • Size estimates for the high latitude continental carbon and nitrogen stocks vary widely between regions and research groups. • The representation of permafrost-related processes in global climate models still tends to be rudimentary, and is one reason for the frequently poor perform-ances of climate models at high latitudes. The key objectives of PAGE21 are: • to improve our understanding of the processes affect-ing the size of the arctic permafrost carbon and nitro-gen pools through detailed field studies and monitor-ing, in order to quantify their size and their vulnerability to climate change, • to produce, assemble and assess high-quality datasets in order to develop and evaluate representations of permafrost and related processes in global models, • to improve these models accordingly, • to use these models to reduce the uncertainties in feed-backs from arctic permafrost to global change, thereby providing the means to assess the feasibility of stabili-zation scenarios, and • to ensure widespread dissemination of our results in order to provide direct input into the ongoing debate on climate-change mitigation. The concept of PAGE21 is to directly address these questions through a close interaction between monitoring activities, proc-ess studies and modeling on the pertinent temporal and spatial scales. Field sites have been selected to cover a wide range of environmental conditions for the validation of large scale mod-els, the development of permafrost monitoring capabilities, the study of permafrost processes, and for overlap with existing monitoring programs. PAGE21 will contribute to upgrading the project sites with the objective of providing a measurement baseline, both for process studies and for modeling programs. PAGE21 is determined to break down the traditional barriers in permafrost sciences between observational and model-supported site studies and large-scale climate modeling. Our concept for the interaction between site-scale studies and large-scale modeling is to establish and maintain a direct link be-tween these two areas for developing and evaluating, on all spatial scales, the land-surface modules of leading European global climate models taking part in the Coupled Model Inter-comparison Project Phase 5 (CMIP5), designed to inform the IPCC process. The timing of this project is such that the main scientific results from PAGE21, and in particular the model-based assessments will build entirely on new outputs and results from the CMIP5 Climate Model Intercomparison Project designed to inform the IPCC Fifth Assessment Report. However, PAGE21 is designed to leave a legacy that will en-dure beyond the lifetime of the projections that it produces. This legacy will comprise • an improved understanding of the key processes and parameters that determine the vulnerability of arctic permafrost to climate change, • the production of a suite of major European coupled climate models including detailed and validated repre-sentations of permafrost-related processes, that will reduce uncertainties in future climate projections pro-duced well beyond the lifetime of PAGE21, and • the training of a new generation of permafrost scien-tists who will bridge the long-standing gap between permafrost field science and global climate modeling, for the long-term benefit of science and society.

Refocusing and Evolving Subseasonal-to-Seasonal Services in NOAA's National Weather Service

NASA Astrophysics Data System (ADS)

Timofeyeva-Livezey, M. M.; Horsfall, F. M. C.; Silva, V.; Mangan, M. R.; Meyers, J. C.; Zdrojewski, J.

2017-12-01

NOAA's National Weather Service (NWS) recently completed a reorganization to better support its goal to build a Weather-Ready Nation. As part of the reorganization, NWS streamlined its 11 national service programs, including climate services, to provide a more structured approach to supporting service delivery needs. As the American public increasingly requests information at sub-seasonal and seasonal time scales for decision making, the NWS Climate Services Program is striving to meet those needs by accelerating transition of research to operations, improving delivery of products and services, and enhancing partnerships to facilitate provision of seamless weather, water, and climate products and services at regional and local scales. Additionally, NWS forecasters are requesting more tools to be able to put severe weather and water events into a climate context to provide more effective impact-based decision support services (IDSS). This paper will describe the activities to more effectively integrate climate services into the NWS suite of environmental information, the roles of the NWS offices supporting or delivering sub-seasonal and seasonal information to the US public, and engaging NWS core and deep-core partners in provision of information on climatological risks and preparedness as a part of IDSS. We will discuss the process by which we collect user requests and/or needs and the NWS process that allows us to move these requests and needs through a formal requirements validation process and thus place the requirement on a path to identify a potential solution for implementation. The validation of a NWS climate-related requirement is also key to identify research, development, and transition mission delivery needs that are supported through the Office of Oceanic and Atmospheric Research (OAR) Climate Program Office (CPO). In addition, we will present the outcomes of key actions of the first ever NWS National Climate Services Meeting (NCSM) that was held in May 2016 with the participation of more than 250 NWS climate services staff and key partners from across the country. The key actions include understanding core and deep-core partners, advancing training for NWS staff focused on IDSS, and better organization of service delivery at regional and local levels.

Using Four Downscaling Techniques to Characterize Uncertainty in Updating Intensity-Duration-Frequency Curves Under Climate Change

NASA Astrophysics Data System (ADS)

Cook, L. M.; Samaras, C.; McGinnis, S. A.

2017-12-01

Intensity-duration-frequency (IDF) curves are a common input to urban drainage design, and are used to represent extreme rainfall in a region. As rainfall patterns shift into a non-stationary regime as a result of climate change, these curves will need to be updated with future projections of extreme precipitation. Many regions have begun to update these curves to reflect the trends from downscaled climate models; however, few studies have compared the methods for doing so, as well as the uncertainty that results from the selection of the native grid scale and temporal resolution of the climate model. This study examines the variability in updated IDF curves for Pittsburgh using four different methods for adjusting gridded regional climate model (RCM) outputs into station scale precipitation extremes: (1) a simple change factor applied to observed return levels, (2) a naïve adjustment of stationary and non-stationary Generalized Extreme Value (GEV) distribution parameters, (3) a transfer function of the GEV parameters from the annual maximum series, and (4) kernel density distribution mapping bias correction of the RCM time series. Return level estimates (rainfall intensities) and confidence intervals from these methods for the 1-hour to 48-hour duration are tested for sensitivity to the underlying spatial and temporal resolution of the climate ensemble from the NA-CORDEX project, as well as, the future time period for updating. The first goal is to determine if uncertainty is highest for: (i) the downscaling method, (ii) the climate model resolution, (iii) the climate model simulation, (iv) the GEV parameters, or (v) the future time period examined. Initial results of the 6-hour, 10-year return level adjusted with the simple change factor method using four climate model simulations of two different spatial resolutions show that uncertainty is highest in the estimation of the GEV parameters. The second goal is to determine if complex downscaling methods and high-resolution climate models are necessary for updating, or if simpler methods and lower resolution climate models will suffice. The final results can be used to inform the most appropriate method and climate model resolutions to use for updating IDF curves for urban drainage design.

Answering the Oregon challenge : climate change

DOT National Transportation Integrated Search

2009-01-13

This paper outlines Gov. Kulongoski's agenda concerning the issue of climate change. It addresses several key topics: greenhouse gas reduction, energy efficiency, renewable energy, and sustainable transportation.

Modeling erosion under future climates with the WEPP model

Treesearch

Timothy Bayley; William Elliot; Mark A. Nearing; D. Phillp Guertin; Thomas Johnson; David Goodrich; Dennis Flanagan

2010-01-01

The Water Erosion Prediction Project Climate Assessment Tool (WEPPCAT) was developed to be an easy-to-use, web-based erosion model that allows users to adjust climate inputs for user-specified climate scenarios. WEPPCAT allows the user to modify monthly mean climate parameters, including maximum and minimum temperatures, number of wet days, precipitation, and...

Putting the Assessment into Practice: Applications of Climate and Health Data and Information

NASA Astrophysics Data System (ADS)

Balbus, J. M.; Morris, J.; Luber, G.

2016-12-01

The USGCRP Climate and Health Assessment represents the most up to date synthesis of the scientific literature on the health impacts of climate change in the United States. One of its key messages is that climate change is already affecting the health of people in the United States and around the world, and these impacts are likely to become more extensive over time. Another key message is that all Americans have some degree of vulnerability to the health impacts of climate change at some point in their lives. Conclusions as significant as those call for measures to translate current knowledge into specific actions to protect populations and enhance resilience to the health impacts of climate change. This presentation will summarize efforts underway across the federal government to apply research results and climate and health data to enhancing the resilience of populations. These efforts include the development of early warning systems and other applications of predictive models of weather and climate-related health hazards; partnerships with health professional societies to help translate the assessment's findings into specific recommendations for health professionals; and the development of educational materials to help enhance the resilience of students and their families by enhancing their understanding of the connections between climate, climate change and health.

Adaptation to Climatic Hazards in the Savannah Ecosystem: Improving Adaptation Policy and Action

NASA Astrophysics Data System (ADS)

Yiran, Gerald A. B.; Stringer, Lindsay C.

2017-10-01

People in Ghana's savannah ecosystem have historically experienced a range of climatic hazards that have affected their livelihoods. In view of current climate variability and change, and projected increases in extreme events, adaptation to climate risks is vital. Policies have been put in place to enhance adaptation across sub-Saharan Africa in accordance with international agreements. At the same time, local people, through experience, have learned to adapt. This paper examines current policy actions and their implementation alongside an assessment of barriers to local adaptation. In doing so it links adaptation policy and practice. Policy documents were analysed that covered key livelihood sectors, which were identified as climate sensitive. These included agriculture, water, housing and health policies, as well as the National Climate Change Policy. In-depth interviews and focus group discussions were also held with key stakeholders in the Upper East Region of Ghana. Analyses were carried using thematic content analysis. Although policies and actions complement each other, their integration is weak. Financial, institutional, social, and technological barriers hinder successful local implementation of some policy actions, while lack of local involvement in policy formulation also hinders adaptation practice. Integration of local perspectives into policy needs to be strengthened in order to enhance adaptation. Coupled with this is a need to consider adaptation to climate change in development policies and to pursue efforts to reduce or remove the key barriers to implementation at the local level.

Simulated discharge trends indicate robustness of hydrological models in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Nikolova, Silviya; Seibert, Jan

2016-04-01

Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant parameter values over the whole reference period. Further, preliminary results suggest that some trends in parameter values do not reflect changes in hydrological processes, as reported by others previously, but instead might stem from a modeling artifact related to the parameterization of evapotranspiration, which is overly sensitive to temperature increase. We adopt a trading-space-for-time approach to better understand whether robust relationships between parameter values and forcing can be established, and to critically explore the rationale behind time-dependent parameter values in conceptual hydrological models.

Climate Change Indicators for the United States

EPA Science Inventory

EPA’s publishes the Climate Change Indicators for the United States report to communicate information about the science and impacts of climate change, track trends in environmental quality, and inform de¬cision-making. This report presents a set of key indicators to help readers ...

Adjoint-Based Climate Model Tuning: Application to the Planet Simulator

NASA Astrophysics Data System (ADS)

Lyu, Guokun; Köhl, Armin; Matei, Ion; Stammer, Detlef

2018-01-01

The adjoint method is used to calibrate the medium complexity climate model "Planet Simulator" through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA-Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in nonlinear coupled climate models.

Inferring responses to climate dynamics from historical demography in neotropical forest lizards

PubMed Central

Xue, Alexander T.; Brown, Jason L.; Alvarado-Serrano, Diego F.; Rodrigues, Miguel T.; Hickerson, Michael J.; Carnaval, Ana C.

2016-01-01

We apply a comparative framework to test for concerted demographic changes in response to climate shifts in the neotropical lowland forests, learning from the past to inform projections of the future. Using reduced genomic (SNP) data from three lizard species codistributed in Amazonia and the Atlantic Forest (Anolis punctatus, Anolis ortonii, and Polychrus marmoratus), we first reconstruct former population history and test for assemblage-level responses to cycles of moisture transport recently implicated in changes of forest distribution during the Late Quaternary. We find support for population shifts within the time frame of inferred precipitation fluctuations (the last 250,000 y) but detect idiosyncratic responses across species and uniformity of within-species responses across forest regions. These results are incongruent with expectations of concerted population expansion in response to increased rainfall and fail to detect out-of-phase demographic syndromes (expansions vs. contractions) across forest regions. Using reduced genomic data to infer species-specific demographical parameters, we then model the plausible spatial distribution of genetic diversity in the Atlantic Forest into future climates (2080) under a medium carbon emission trajectory. The models forecast very distinct trajectories for the lizard species, reflecting unique estimated population densities and dispersal abilities. Ecological and demographic constraints seemingly lead to distinct and asynchronous responses to climatic regimes in the tropics, even among similarly distributed taxa. Incorporating such constraints is key to improve modeling of the distribution of biodiversity in the past and future. PMID:27432951

Inferring responses to climate dynamics from historical demography in neotropical forest lizards.

PubMed

Prates, Ivan; Xue, Alexander T; Brown, Jason L; Alvarado-Serrano, Diego F; Rodrigues, Miguel T; Hickerson, Michael J; Carnaval, Ana C

2016-07-19

We apply a comparative framework to test for concerted demographic changes in response to climate shifts in the neotropical lowland forests, learning from the past to inform projections of the future. Using reduced genomic (SNP) data from three lizard species codistributed in Amazonia and the Atlantic Forest (Anolis punctatus, Anolis ortonii, and Polychrus marmoratus), we first reconstruct former population history and test for assemblage-level responses to cycles of moisture transport recently implicated in changes of forest distribution during the Late Quaternary. We find support for population shifts within the time frame of inferred precipitation fluctuations (the last 250,000 y) but detect idiosyncratic responses across species and uniformity of within-species responses across forest regions. These results are incongruent with expectations of concerted population expansion in response to increased rainfall and fail to detect out-of-phase demographic syndromes (expansions vs. contractions) across forest regions. Using reduced genomic data to infer species-specific demographical parameters, we then model the plausible spatial distribution of genetic diversity in the Atlantic Forest into future climates (2080) under a medium carbon emission trajectory. The models forecast very distinct trajectories for the lizard species, reflecting unique estimated population densities and dispersal abilities. Ecological and demographic constraints seemingly lead to distinct and asynchronous responses to climatic regimes in the tropics, even among similarly distributed taxa. Incorporating such constraints is key to improve modeling of the distribution of biodiversity in the past and future.

Aerosol physicochemical properties in relation to meteorology: Case studies in urban, marine, and arid settings

NASA Astrophysics Data System (ADS)

Wonaschuetz, Anna

Atmospheric aerosols are a highly relevant component of the climate system affecting atmospheric radiative transfer and the hydrological cycle. As opposed to other key atmospheric constituents with climatic relevance, atmospheric aerosol particles are highly heterogeneous in time and space with respect to their size, concentration, chemical composition and physical properties. Many aspects of their life cycle are not understood, making them difficult to represent in climate models and hard to control as a pollutant. Aerosol-cloud interactions in particular are infamous as a major source of uncertainty in future climate predictions. Field measurements are an important source of information for the modeling community and can lead to a better understanding of chemical and microphysical processes. In this study, field data from urban, marine, and arid settings are analyzed and the impact of meteorological conditions on the evolution of aerosol particles while in the atmosphere is investigated. Particular attention is given to organic aerosols, which are a poorly understood component of atmospheric aerosols. Local wind characteristics, solar radiation, relative humidity and the presence or absence of clouds and fog are found to be crucial factors in the transport and chemical evolution of aerosol particles. Organic aerosols in particular are found to be heavily impacted by processes in the liquid phase (cloud droplets and aerosol water). The reported measurements serve to improve the process-level understanding of aerosol evolution in different environments and to inform the modeling community by providing realistic values for input parameters and validation of model calculations.

Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

NASA Astrophysics Data System (ADS)

Besha, A. A.; Steele, C. M.; Fernald, A.

2014-12-01

Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

Heat, Human Performance, and Occupational Health: A Key Issue for the Assessment of Global Climate Change Impacts.

PubMed

Kjellstrom, Tord; Briggs, David; Freyberg, Chris; Lemke, Bruno; Otto, Matthias; Hyatt, Olivia

2016-01-01

Ambient heat exposure is a well-known health hazard, which reduces human performance and work capacity at heat levels already common in tropical and subtropical areas. Various health problems have been reported. Increasing heat exposure during the hottest seasons of each year is a key feature of global climate change. Heat exhaustion and reduced human performance are often overlooked in climate change health impact analysis. Later this century, many among the four billion people who live in hot areas worldwide will experience significantly reduced work capacity owing to climate change. In some areas, 30-40% of annual daylight hours will become too hot for work to be carried out. The social and economic impacts will be considerable, with global gross domestic product (GDP) losses greater than 20% by 2100. The analysis to date is piecemeal. More analysis of climate change-related occupational health impact assessments is greatly needed.

NCAR Johns Hopkins/CDC Climate and Health Summer Institute

NASA Technical Reports Server (NTRS)

Mearns, Linda O.

2005-01-01

The interactions between climate and health are rife with complexity and present many conceptual and methodological challenges. Possible effects of climate change on health are considered some of the most sensitive impacts of climate change and are a high priority for policy-makers and the public. As a first step toward improving tlit: quality of research, we developed a Climate and Health Workshop (Institute), geared toward teaching students various aspects of how to conduct integrated climate and health research. At the workshop scientists presented selected case studies of climate and health (e.g., heat mortality, vector-borne diseases), thus demonstrating a subset of key analytical tools and databases most useful to researchers in this field. Key research gaps in this research area were discussed. In this six-day Institute (21-28 July 2004, Boulder, Colorado), health scientists and students benefited from lectures and hands-on tools taught by top NCAR scientists. The attendees learned about health databases and epidemiologic methods from leading health scientists from CDC, Johns Hopkins, and other institutions from around the globe.

ARC3.2 Summary for City Leaders Climate Change and Cities: Second Assessment Report of the Urban Climate Change Research Network

NASA Technical Reports Server (NTRS)

Rosenzweig, C.; Solecki, W.; Romero-Lankao, P.; Mehrotra, S.; Dhakal, S.; Bowman, T.; Ibrahim, S. Ali

2015-01-01

ARC3.2 presents a broad synthesis of the latest scientific research on climate change and cities. Mitigation and adaptation climate actions of 100 cities are documented throughout the 16 chapters, as well as online through the ARC3.2 Case Study Docking Station. Pathways to Urban Transformation, Major Findings, and Key Messages are highlighted here in the ARC3.2 Summary for City Leaders. These sections lay out what cities need to do achieve their potential as leaders of climate change solutions. UCCRN Regional Hubs in Europe, Latin America, Africa, Australia and Asia will share ARC3.2 findings with local city leaders and researchers. The ARC3.2 Summary for City Leaders synthesizes Major Findings and Key Messages on urban climate science, disasters and risks, urban planning and design, mitigation and adaptation, equity and environmental justice, economics and finance, the private sector, urban ecosystems, urban coastal zones, public health, housing and informal settlements, energy, water, transportation, solid waste, and governance. These were based on climate trends and future projections for 100 cities around the world.

Putting the Weather Back Into Climate

NASA Astrophysics Data System (ADS)

Smith, Leonard A.; Stainforth, David A.

2014-05-01

The literature contains a variety of definitions of climate, and the emphasis in these definitions has changed over time. Defining climate as a mean value is, of course, both limiting and misleading; definitions of climate based on averages have been deprecated as far back as 1931 [1]. In the context of current efforts to produce climate predictions for use in climate adaptation, it is timely to consider how well various definitions of climate serve the research for applications community. From a nonlinear dynamical systems perspective it is common to associate climate with a system's natural measure (or "attractor" if such an object exists). Such a definition is not easily applied to physical systems where we have limited observations over a restricted period of time; the duration of 30 years is often mentioned today and the origin of this period is discussed. Given a dynamic system in which parameters are evolving in time, the view of climate as a natural measure becomes problematic as, by definition, there may be no attractor per se. Attractors defined for particular parameter values cannot be expected to have any association with the probability of states under transient changes in the values of that parameter. Alternatively, distributions may be determined which reflect the transient situation, based on (rather broad) additional assumptions regarding the state of the system at some point in the past (say, an ice age planet vs an interglacial planet). Such distributions reflect many of the properties one would hope to be represented in a generalised definition of the system's climate. Here we trace how definitions of climate have changed over time and highlight a number of properties of definitions of climate which would facilitate common use across researchers, from observers to theoreticians, from climate modellers to mathematicians. We show while periodic changes in parameter values (such as those found in an annual cycle or a diurnal cycle) are easily incorporated within the traditional nonlinear dynamical systems view, non-periodic or secular changes (such as those due to increasing atmospheric greenhouse gas concentrations) yield an open challenge. We argue the need both for clarifying and for clearly meeting the open challenges of defining climate in relation to the state of an evolving system, and suggest a path forward. [1] Miller, A.A., 1931: Climatology. First Ed. Methuen.

Climate Modeling and Causal Identification for Sea Ice Predictability

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

Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark

This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments inmore » which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.« less

Modelling the influence of climate change on the chemical concentrations in the Baltic Sea region with the POPCYCLING-Baltic model.

PubMed

Kong, Deguo; MacLeod, Matthew; Cousins, Ian T

2014-09-01

The effect of projected future changes in temperature, wind speed, precipitation and particulate organic carbon on concentrations of persistent organic chemicals in the Baltic Sea regional environment is evaluated using the POPCYCLING-Baltic multimedia chemical fate model. Steady-state concentrations of hypothetical perfectly persistent chemicals with property combinations that encompass the entire plausible range for non-ionizing organic substances are modelled under two alternative climate change scenarios (IPCC A2 and B2) and compared to a baseline climate scenario. The contributions of individual climate parameters are deduced in model experiments in which only one of the four parameters is changed from the baseline scenario. Of the four selected climate parameters, temperature is the most influential, and wind speed is least. Chemical concentrations in the Baltic region are projected to change by factors of up to 3.0 compared to the baseline climate scenario. For chemicals with property combinations similar to legacy persistent organic pollutants listed by the Stockholm Convention, modelled concentration ratios between two climate change scenarios and the baseline scenario range from factors of 0.5 to 2.0. This study is a first step toward quantitatively assessing climate change-induced changes in the environmental concentrations of persistent organic chemicals in the Baltic Sea region. Copyright © 2014 Elsevier Ltd. All rights reserved.

Tracking Middle Grades Climate Data to Inform School Change. REL West Research Digest

ERIC Educational Resources Information Center

Regional Educational Laboratory West, 2015

2015-01-01

A growing body of research shows that positive school climate is a key lever for students' academic and social development and success. This research digest shows how an alliance of California schools and districts, school climate experts, and state education agency personnel have teamed up to use school climate data to drive a continuous cycle of…

Ecosystem vulnerability assessment and synthesis: a report from the Climate Change Response Framework Project in northern Wisconsin

Treesearch

Chris Swanston; Maria Janowiak; Louis Iverson; Linda Parker; David Mladenoff; Leslie Brandt; Patricia Butler; Matt St. Pierre; Anantha Prasad; Stephen Matthews; Matthew Peters; Dale Higgins; Avery Dorland

2011-01-01

The forests of northern Wisconsin will likely experience dramatic changes over the next 100 years as a result of climate change. This assessment evaluates key forest ecosystem vulnerabilities to climate change across northern Wisconsin under a range of future climate scenarios. Warmer temperatures and shifting precipitation patterns are expected to influence ecosystem...

VEMAP phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

Treesearch

Timothy G.F. Kittel; Nan. A. Rosenbloom; J.A. Royle; C. Daly; W.P. Gibson; H.H. Fisher; P. Thornton; D.N. Yates; S. Aulenbach; C. Kaufman; R. McKeown; Dominque Bachelet; David S. Schimel

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the...

Exploring Elementary Students' Understanding of Energy and Climate Change

ERIC Educational Resources Information Center

Boylan, Colin

2008-01-01

As environmental changes become a significant societal issue, elementary science curricula need to develop students' understanding about the key concepts of energy and climate change. For teachers, developing quality learning experiences involves establishing what their students' prior understanding about energy and climate change are. A survey…

Mitigation and adaptation within a climate change policy portfolio: A research program

EPA Science Inventory

It is now recognized that optimal global climate policy is a portfolio of the two key responses for reducing the risks of climate change: mitigation and adaptation. Significant differences between the two responses have inhibited understanding of how to appropriately view these...

Arctic systems in the Quaternary: Ecological collision, faunal mosaics and the consequences of wobbling climate

USDA-ARS?s Scientific Manuscript database

Climate oscillations and episodic or recurrent processes interact with evolution, ecology and biogeography determining the structure and complex mosaic that is the biosphere. Parasites and parasite-host assemblages, within an expansive environmental matrix determined by climate, are key components...

ASR Application in Climate Change Adaptation: The Need, Issues and Research Focus

EPA Science Inventory

This presentation will focus on four key points: (a) Aquifer storage and recovery: a long-held practice offering a potential tool for climate change adaptation, (b) The drivers: 1) hydrological perturbations related to climate change, 2) water imbalance in both Qand Vbetween wat...

Hydrologic drivers of tree biodiversity: The impact of climate change (Invited)

NASA Astrophysics Data System (ADS)

Rodriguez-Iturbe, I.; Konar, M.; Muneepeerakul, R.; Azaele, S.; Bertuzzo, E.; Rinaldo, A.

2009-12-01

Biodiversity of forests is of major importance for society. The possible impact of climate change on the characteristics of tree diversity is a topic of crucial importance with relevant implications for conservation campaigns and resource management. Here we present the main results of the expected biodiversity changes in the Mississippi-Missouri River Basin (MMRS) and two of its subregions under different scenarios of possible climate change. A mechanistic neutral metapopulation model is developed to study the main drivers of large scale biodiversity signatures in the MMRS system. The region is divided into 824 Direct Tributary Areas (DTAs), each one characterized by its own habitat capacity. Data for the spatial occurrence of the 231 species present in the system is taken from the US Forest Service Inventory and Analysis Database. The model has permeable boundaries to account for immigration from the regions surrounding the MMRS. The model accounts for key aspects of ecological dynamics (e.g., birth, death, speciation, and migration) and is fundamentally driven by the mean annual precipitation characteristic of each of the DTAs in the system. It is found that such a simple model, with only four parameters, yields an excellent representation of the observed local species richness (LSR), between-community (β) diversity, and species rank-occupancy function. The mean annual rainfall of each DTA is then changed according to the climate scenarios and new habitat capacities are thus obtained throughout the MMRS and its subregions. The resulting large-scale biodiversity signatures are computed and compared with those of the present scenario, showing that there are very important changes arising from the climate change conditions. For the dry scenarios, it is shown that there is a considerable decrease of species richness, both at local and regional scales, and a contraction of species' geographic ranges. These findings link the hydrologic and ecological dynamics of the MMRS under climate change conditions and are important for a comprehensive evaluation of the climate change impacts over the United States.

Vegetation Fires in the Coupled Human-Earth System Under Future Environmental and Policy Perspectives

NASA Astrophysics Data System (ADS)

le page, Y.; Morton, D. C.; Hurtt, G. C.

2013-12-01

Fires play a major role in terrestrial ecosystems dynamics and the carbon cycle. Potential changes in fire regimes due to climate change, land use change, or human management could have substantial ecological, climatic and socio-economic impacts, and have recently been emphasized as a source of uncertainty for policy-makers and climate mitigation cost estimates. Anticipating these interactions thus entails interdisciplinary models. Here we describe the development of a new fire modeling framework, which features the essential integration of climatic, vegetation and anthropogenic drivers. The model is an attempt to realistically account for ignition, spread and termination processes, on a 12-hour time step and at 1 degree spatial resolution globally. Because the quantitative influence of fire drivers on these processes are often poorly constrained, the framework includes an optimization procedure whereby key parameters (e.g. influence of moisture on fire spread, probability of cloud-to-ground lightning flashes to actually ignite a fire, human ignition frequency as a function of land use density) are determined to maximize the agreement between modeled and observed burned area over the past decade. The model performs surprisingly well across all biomes, and shows good agreement on non-optimized features, such as seasonality and fire size, which suggests some potential for robust projections. We couple the model to an integrated assessment model and explore the consequences of mitigation policies, land use decisions and climate change on future fire regimes with a focus on the Amazon basin. The coupled model future projections show that business-as-usual land use expansion would increase the frequency of escaped fires in the remaining forest, especially when combined with models projecting a drier climate. Inversely, climate mitigation policies as projected in the IPCC RCP4.5 scenario achieve synergistic benefits, with increased forest extent, less fire ignitions, and higher moisture levels.

Linking Land Surface Phenology and Growth Limiting Factor Shifts over the Past 30 Years

NASA Astrophysics Data System (ADS)

Garonna, I.; Schenkel, D.; de Jong, R.; Schaepman, M. E.

2015-12-01

The study of global vegetation dynamics contributes to a better understanding of global change drivers and how these affect ecosystems and ecological diversity. Land-surface phenology (LSP) is a key response and feedback of vegetation to the climate system, and hence a parameter that needs to be accurately represented in terrestrial biosphere models [1]. However, the effects of climatic changes on LSP depend on the relative importance of climatic constraints in specific regions - which are not well understood at global scale. In this study, we analyzed a Phenology Reanalysis dataset [2] to evaluate shifts in three climatic drivers of phenology at global scale and over the last 30 years (1982-2012): incoming radiation, evaporative demand and minimum temperature. As a first step, we compared LAI as modeled from these three factors (LAIre) to remotely sensed observations of LSP (LAI3g, [3]) over the same time period. As a second step, we examined temporal trends in the climatic constraints at Start- and End- of the Growing Season. There was good agreement between phenology metrics as derived form LAI3g and LAIre over the last 30 years - thus providing confidence in the climatic constraints underlying the modeled data. Our analysis reveals inter-annual variation in the relative importance of the three climatic factors in limiting vegetation growth at Start- and End- of the Growing Season over the last 30 years. High northern latitudes, as well as northern Europe and central Asia, appear to have undergone significant changes in dominance between the three controls. We also find that evaporative demand has become increasingly limiting for growth in many parts of the world, in particular in South America and eastern Asia. [1] Richardson, A.D. et al. Global Change Biology 18, 566-584 (2012). [2] Stöckli, R. et al. J. Geophys. Res 116, G03020 (2011). [3] Zhu, Z. et al. Remote Sensing 5, 927-948 (2013).

Designing ecological climate change impact assessments to reflect key climatic drivers

USGS Publications Warehouse

Sofaer, Helen R.; Barsugli, Joseph J.; Jarnevich, Catherine S.; Abatzoglou, John T.; Talbert, Marian; Miller, Brian W.; Morisette, Jeffrey T.

2017-01-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.

Designing ecological climate change impact assessments to reflect key climatic drivers.

PubMed

Sofaer, Helen R; Barsugli, Joseph J; Jarnevich, Catherine S; Abatzoglou, John T; Talbert, Marian K; Miller, Brian W; Morisette, Jeffrey T

2017-07-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive - such as means or extremes - can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the 'model space' approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. © 2017 John Wiley & Sons Ltd.

Can We Envision a Bettor's Guide to Climate Prediction Markets?

NASA Astrophysics Data System (ADS)

Trexler, M.

2017-12-01

It's one thing to set up a climate prediction market, it's another to find enough informed traders to make the market work. Climate bets could range widely, from purely scientific or atmospheric metrics, to bets that involve the interplay of science, policy, economic, and behavioral outcomes. For a topic as complex and politicized as climate change, a Bettor's Guide to Climate Predictions could substantially expand and diversify the pool of individuals trading in the market, increasing both its liquidity and decision-support value. The Climate Web is an on-line and publically accessible Beta version of such a Bettor's Guide, implementing the knowledge management adage: "if only we knew what we know." The Climate Web not only curates the key literature, news coverage, and websites relating to more than 100 climate topics, from extreme event exceedance curves to climate economics to climate risk scenarios, it extracts and links together thousands of ideas and graphics across all of those topics. The Climate Web integrates the many disciplinary silos that characterize today's often dysfunctional climate policy conversations, allowing rapid cross-silo exploration and understanding. As a Bettor's Guide it would allow prediction market traders to better research and understand their potential bets, and to quickly survey key thinking and uncertainties relating to those bets. The availability of such a Bettor's Guide to Climate Predictions should make traders willing to place more bets than they otherwise would, and should facilitate higher quality betting. The presentation will introduce the knowledge management dimensions and challenges of climate prediction markets, and introduce the Climate Web as one solution to those challenges.

Impacts of climate change on surface water quality in relation to drinking water production.

PubMed

Delpla, I; Jung, A-V; Baures, E; Clement, M; Thomas, O

2009-11-01

Besides climate change impacts on water availability and hydrological risks, the consequences on water quality is just beginning to be studied. This review aims at proposing a synthesis of the most recent existing interdisciplinary literature on the topic. After a short presentation about the role of the main factors (warming and consequences of extreme events) explaining climate change effects on water quality, the focus will be on two main points. First, the impacts on water quality of resources (rivers and lakes) modifying parameters values (physico-chemical parameters, micropollutants and biological parameters) are considered. Then, the expected impacts on drinking water production and quality of supplied water are discussed. The main conclusion which can be drawn is that a degradation trend of drinking water quality in the context of climate change leads to an increase of at risk situations related to potential health impact.

From field to region yield predictions in response to pedo-climatic variations in Eastern Canada

NASA Astrophysics Data System (ADS)

JÉGO, G.; Pattey, E.; Liu, J.

2013-12-01

The increase in global population coupled with new pressures to produce energy and bioproducts from agricultural land requires an increase in crop productivity. However, the influence of climate and soil variations on crop production and environmental performance is not fully understood and accounted for to define more sustainable and economical management strategies. Regional crop modeling can be a great tool for understanding the impact of climate variations on crop production, for planning grain handling and for assessing the impact of agriculture on the environment, but it is often limited by the availability of input data. The STICS ("Simulateur mulTIdisciplinaire pour les Cultures Standard") crop model, developed by INRA (France) is a functional crop model which has a built-in module to optimize several input parameters by minimizing the difference between calculated and measured output variables, such as Leaf Area Index (LAI). STICS crop model was adapted to the short growing season of the Mixedwood Plains Ecozone using field experiments results, to predict biomass and yield of soybean, spring wheat and corn. To minimize the numbers of inference required for regional applications, 'generic' cultivars rather than specific ones have been calibrated in STICS. After the calibration of several model parameters, the root mean square error (RMSE) of yield and biomass predictions ranged from 10% to 30% for the three crops. A bit more scattering was obtained for LAI (20%

Sensitivity of river fishes to climate change: The role of hydrological stressors on habitat range shifts.

PubMed

Segurado, Pedro; Branco, Paulo; Jauch, Eduardo; Neves, Ramiro; Ferreira, M Teresa

2016-08-15

Climate change will predictably change hydrological patterns and processes at the catchment scale, with impacts on habitat conditions for fish. The main goal of this study is to assess how shifts in fish habitat favourability under climate change scenarios are affected by hydrological stressors. The interplay between climate and hydrological stressors has important implications in river management under climate change because management actions to control hydrological parameters are more feasible than controlling climate. This study was carried out in the Tamega catchment of the Douro basin. A set of hydrological stressor variables were generated through a process-based modelling based on current climate data (2008-2014) and also considering a high-end future climate change scenario. The resulting parameters, along with climatic and site-descriptor variables were used as explanatory variables in empirical habitat models for nine fish species using boosted regression trees. Models were calibrated for the whole Douro basin using 254 fish sampling sites and predictions under future climate change scenarios were made for the Tamega catchment. Results show that models using climatic variables but not hydrological stressors produce more stringent predictions of future favourability, predicting more distribution contractions or stronger range shifts. The use of hydrological stressors strongly influences projections of habitat favourability shifts; the integration of these stressors in the models thinned shifts in range due to climate change. Hydrological stressors were retained in the models for most species and had a high importance, demonstrating that it is important to integrate hydrology in studies of impacts of climate change on freshwater fishes. This is a relevant result because it means that management actions to control hydrological parameters in rivers will have an impact on the effects of climate change and may potentially be helpful to mitigate its negative effects on fish populations and assemblages. Copyright © 2016 Elsevier B.V. All rights reserved.

Community-Based Adaptation To A Changing Climate

EPA Pesticide Factsheets

This resource discusses how climate change is affecting community services, presents sample adaptation strategies, gives examples of successful community adaptation actions, and provides links to other key federal resources.

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.

Community based ecological restoration of peatland in Central Mongolia for climate change mitigation and adaptation

NASA Astrophysics Data System (ADS)

Minayeva, Tatiana; Chultem, Dugarjav; Grootjans, Ab; Yamkhin, Jambaljav; Sirin, Andrey; Suvorov, Gennady; Batdorj, Oyunbileg; Tsamba, Batdorj

2017-04-01

Peatlands cover almost 2 % of Mongolia. They play crucial role in regulation of key natural processes in ecosystems and provide unique resources to maintain traditional way of life and livelihoods of herders. During the last decades, Mongolian peatlands severely degraded both due to the climate related events and due to overgrazing. The peat degradation causes significant losses of carbon store, GHG emissions and is followed by changes in water balance and water composition. The issue arises if such a type of ecosystems as peatlands could be a subject for ecosystem restoration in this arid and subhumid climate. Could it be considered as measure for climate change mitigation and adaptation? With funding opportunities from the Asian Development Bank a pilot project for peatland restoration had been launched in 2016 in Khashaat soum, Arkhangai aimag in Central Mongolia. The pilot aimed to merge local interests of herders with global targets of climate change mitigation. The following questions are addressed: what are the losses of natural functions and ecosystem services of peatland; what are expectations and demands of local communities and incentives for their involvement; how should and could look the target ecosystem; what are the technical solutions in order to achieve the target ecosystem characteristics; and what are the parameters for monitoring to assess the success of the project? The comprehensive baseline study addressed both natural and social aspects. The conclusions are: most of peat in the study area had been mineralised and has turned to organic rich soil with carbon content between 20 to 40 %, the key sources of water - small springs - are partly destroyed by cattle; the permafrost disappeared in this area and could not be the subject for restoration; local herders understand the value of peatland as water source and had carried out some voluntary activities for water storage and regulation such as dam construction; nevertheless there is no understanding of functional particularities of peatland ecosystem and restoration efforts are not effective. Following the baseline study the concept for ecosystem restoration project had been developed. The approach was to merge community based solution with scientific approaches. Restoration in subhumid conditions should avoid creation of open water surfaces, like channels or reservoirs, and deal with integrative ecosystem management. The restoration concept involved fencing of springs, preventing erosion and enhancing water accumulation in soil by cascades of small dams and other small scale ecological solutions. At the same time to meet the needs of local herders, it was decided to repair the dam, constructed by herders, even if it has little value for peatland restoration. The engineering design is now ready and will be implemented next months. The last part of the pilot is monitoring. The parameters determined in the baseline study are included in monitoring program to help to evaluate: carbon sequestration rate, GHG emission reduction, water retention, soil humidity, pasture productivity, social integrity and impact on livelihoods.

On the added value of WUDAPT for Urban Climate Modelling

NASA Astrophysics Data System (ADS)

Brousse, Oscar; Martilli, Alberto; Mills, Gerald; Bechtel, Benjamin; Hammerberg, Kris; Demuzere, Matthias; Wouters, Hendrik; Van Lipzig, Nicole; Ren, Chao; Feddema, Johannes J.; Masson, Valéry; Ching, Jason

2017-04-01

Over half of the planet's population now live in cities and is expected to grow up to 65% by 2050 (United Nations, 2014), most of whom will actually occupy new emerging cities of the global South. Cities' impact on climate is known to be a key driver of environmental change (IPCC, 2014) and has been studied for decades now (Howard, 1875). Still very little is known about our cities' structure around the world, preventing urban climate simulations to be done and hence guidance to be provided for mitigation. Assessing the need to bridge the urban knowledge gap for urban climate modelling perspectives, the World Urban Database and Access Portal Tool - WUDAPT - project (Ching et al., 2015; Mills et al., 2015) developed an innovative technique to map cities globally rapidly and freely. The framework established by Bechtel and Daneke (2012) derives Local Climate Zones (Stewart and Oke, 2012) city maps out of LANDSAT 8 OLI-TIRS imagery (Bechtel et al., 2015) through a supervised classification by a Random Forest Classification algorithm (Breiman, 2001). The first attempt to implement Local Climate Zones (LCZ) out of the WUDAPT product within a major climate model was carried out by Brousse et al. (2016) over Madrid, Spain. This study proved the applicability of LCZs as an enhanced urban parameterization within the WRF model (Chen et al. 2011) employing the urban canopy model BEP-BEM (Martilli, 2002; Salamanca et al., 2010), using the averaged values of the morphological and physical parameters' ranges proposed by Stewart and Oke (2012). Other studies have now used the Local Climate Zones for urban climate modelling purposes (Alexander et al., 2016; Wouters et al. 2016; Hammerberg et al., 2017; Brousse et al., 2017) and demonstrated the added value of the WUDAPT dataset. As urban data accessibility is one of the major challenge for simulations in emerging countries, this presentation will show results of simulations using LCZs and the capacity of the WUDAPT framework to be of high relevancy in multiple regions of the world, such as Africa or Asia.

The seasonal behaviour of carbon fluxes in the Amazon: fusion of FLUXNET data and the ORCHIDEE model

NASA Astrophysics Data System (ADS)

Verbeeck, H.; Peylin, P.; Bacour, C.; Ciais, P.

2009-04-01

Eddy covariance measurements at the Santarém (km 67) site revealed an unexpected seasonal pattern in carbon fluxes which could not be simulated by existing state-of-the-art global ecosystem models (Saleska et al., Sciece 2003). An unexpected high carbon uptake was measured during dry season. In contrast, carbon release was observed in the wet season. There are several possible (combined) underlying mechanisms of this phenomenon: (1) an increased soil respiration due to soil moisture in the wet season, (2) increased photosynthesis during the dry season due to deep rooting, hydraulic lift, increased radiation and/or a leaf flush. The objective of this study is to optimise the ORCHIDEE model using eddy covariance data in order to be able to mimic the seasonal response of carbon fluxes to dry/wet conditions in tropical forest ecosystems. By doing this, we try to identify the underlying mechanisms of this seasonal response. The ORCHIDEE model is a state of the art mechanistic global vegetation model that can be run at local or global scale. It calculates the carbon and water cycle in the different soil and vegetation pools and resolves the diurnal cycle of fluxes. ORCHIDEE is built on the concept of plant functional types (PFT) to describe vegetation. To bring the different carbon pool sizes to realistic values, spin-up runs are used. ORCHIDEE uses climate variables as drivers together with a number of ecosystem parameters that have been assessed from laboratory and in situ experiments. These parameters are still associated with a large uncertainty and may vary between and within PFTs in a way that is currently not informed or captured by the model. Recently, the development of assimilation techniques allows the objective use of eddy covariance data to improve our knowledge of these parameters in a statistically coherent approach. We use a Bayesian optimisation approach. This approach is based on the minimization of a cost function containing the mismatch between simulated model output and observations as well as the mismatch between a priori and optimized parameters. The parameters can be optimized on different time scales (annually, monthly, daily). For this study the model is optimised at local scale for 5 eddy flux sites: 4 sites in Brazil and one in French Guyana. The seasonal behaviour of C fluxes in response to wet and dry conditions differs among these sites. Key processes that are optimised include: the effect of the soil water on heterotrophic soil respiration, the effect of soil water availability on stomatal conductance and photosynthesis, and phenology. By optimising several key parameters we could improve the simulation of the seasonal pattern of NEE significantly. Nevertheless, posterior parameters should be interpreted with care, because resulting parameter values might compensate for uncertainties on the model structure or other parameters. Moreover, several critical issues appeared during this study e.g. how to assimilate latent and sensible heat data, when the energy balance is not closed in the data? Optimisation of the Q10 parameter showed that on some sites respiration was not sensitive at all to temperature, which show only small variations in this region. Considering this, one could question the reliability of the partitioned fluxes (GPP/Reco) at these sites. This study also tests if there is coherence between optimised parameter values of different sites within the tropical forest PFT and if the forward model response to climate variations is similar between sites.

Climate change impacts on mycotoxin risks in US maize

USDA-ARS?s Scientific Manuscript database

To ensure future food security, it is crucial to understand how potential climate change scenarios will affect agriculture. One key area of interest is how climatic factors, both in the near- and the long-term future, could affect fungal infection of crops and mycotoxin production by these fungi. ...

Impacts of Climate Change and Variability on Water Resources in the Southeast USA

Treesearch

Ge Sun; Peter V. Caldwell; Steven G. McNulty; Aris P. Georgakakos; Sankar Arumugam; James Cruise; Richard T. McNider; Adam Terando; Paul A. Conrads; John Feldt; Vasu Misra; Luigi Romolo; Todd C. Rasmussen; Daniel A. Marion

2013-01-01

Key FindingsClimate change is affecting the southeastern USA, particularly increases in rainfall variability and air temperature, which have resulted in more frequent hydrologic extremes, such as high‐intensity storms (tropical storms and hurricanes), flooding, and drought events.Future climate warming likely will...

School Climate and Student Absenteeism and Internalizing and Externalizing Behavioral Problems

ERIC Educational Resources Information Center

Hendron, Marisa; Kearney, Christopher A.

2016-01-01

This study examined whether school climate variables were directly and inversely related to absenteeism severity and key symptoms of psychopathology among youths specifically referred for problematic attendance (N = 398). Adolescents in our sample completed the School Climate Survey Revised Edition, which measured sharing of resources, order and…

Climate change effects on central New Mexico's land use, transportation system, and key natural resources : task 1.2 memo

DOT National Transportation Integrated Search

2014-05-01

The purpose of this report is to illustrate how planning decisions made today will affect central New Mexicos resilience to climate change impacts in 2040. This report first describes climate change impacts in central New Mexico. This report then ...

76 FR 16443 - Proposed Information Collection: Strengthening the Scientific Understanding of Climate Change...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-23

... responsibilities is seeking public review and comment on a draft report to Congress titled ``Strengthening the... report reviews key issues related to freshwater resource data and climate change and identifies next... Sustainability (CENRS) and the Interagency Climate Change Adaptation Task Force and its Water Resources Workgroup...

Microclimate and ecological threshold responses in a warming and wetting experiment following whole-tree harvest

USDA-ARS?s Scientific Manuscript database

Ecosystem climate manipulation experiments (ECMEs) are a key tool for predicting the effects of climate on ecosystems. However, the strength of inferences drawn from these experiments depends on whether the manipulated conditions mimic future climate changes. While ECMEs have examined mean tempera...

Climate and Land-Cover Change Impacts on Stream Flow in the Southwest U.S.

EPA Science Inventory

Vegetation change in arid and semi-arid climatic regions of the American West are a primary concern in sustaining key ecosystem services such as clean, reliable water sources for multiple uses. Land cover and climate change impacts on stream flow were investigated in a southeast ...

Uncertainty analysis of scintillometers methods in measuring sensible heat fluxes of forest ecosystem

NASA Astrophysics Data System (ADS)

Zheng, N.

2017-12-01

Sensible heat flux (H) is one of the driving factors of surface turbulent motion and energy exchange. Therefore, it is particularly important to measure sensible heat flux accurately at the regional scale. However, due to the heterogeneity of the underlying surface, hydrothermal regime, and different weather conditions, it is difficult to estimate the represented flux at the kilometer scale. The scintillometer have been developed into an effective and universal equipment for deriving heat flux at the regional-scale which based on the turbulence effect of light in the atmosphere since the 1980s. The parameter directly obtained by the scintillometer is the structure parameter of the refractive index of air based on the changes of light intensity fluctuation. Combine with parameters such as temperature structure parameter, zero-plane displacement, surface roughness, wind velocity, air temperature and the other meteorological data heat fluxes can be derived. These additional parameters increase the uncertainties of flux because the difference between the actual feature of turbulent motion and the applicable conditions of turbulence theory. Most previous studies often focused on the constant flux layers that are above the rough sub-layers and homogeneous flat surfaces underlying surfaces with suitable weather conditions. Therefore, the criteria and modified forms of key parameters are invariable. In this study, we conduct investment over the hilly area of northern China with different plants, such as cork oak, cedar-black and locust. On the basis of key research on the threshold and modified forms of saturation with different turbulence intensity, modified forms of Bowen ratio with different drying-and-wetting conditions, universal function for the temperature structure parameter under different atmospheric stability, the dominant sources of uncertainty will be determined. The above study is significant to reveal influence mechanism of uncertainty and explore influence degree of uncertainty with quantitative analysis. The study can provide theoretical basis and technical support for accurately measuring sensible heat fluxes of forest ecosystem with scintillometer method, and can also provide work foundation for further study on role of forest ecosystem in energy balance and climate change.

Relevance of Regional Hydro-Climatic Projection Data for Hydrodynamics and Water Quality Modelling of the Baltic Sea

NASA Astrophysics Data System (ADS)

Goldenberg, R.; Vigouroux, G.; Chen, Y.; Bring, A.; Kalantari, Z.; Prieto, C.; Destouni, G.

2017-12-01

The Baltic Sea, located in Northern Europe, is one of the world's largest body of brackish water, enclosed and surrounded by nine different countries. The magnitude of climate change may be particularly large in northern regions, and identifying its impacts on vulnerable inland waters and their runoff and nutrient loading to the Baltic Sea is an important and complex task. Exploration of such hydro-climatic impacts is needed to understand potential future changes in physical, ecological and water quality conditions in the regional coastal and marine waters. In this study, we investigate hydro-climatic changes and impacts on the Baltic Sea by synthesizing multi-model climate projection data from the CORDEX regional downscaling initiative (EURO- and Arctic- CORDEX domains, http://www.cordex.org/). We identify key hydro-climatic variable outputs of these models and assess model performance with regard to their projected temporal and spatial change behavior and impacts on different scales and coastal-marine parts, up to the whole Baltic Sea. Model spreading, robustness and impact implications for the Baltic Sea system are investigated for and through further use in simulations of coastal-marine hydrodynamics and water quality based on these key output variables and their change projections. Climate model robustness in this context is assessed by inter-model spreading analysis and observation data comparisons, while projected change implications are assessed by forcing of linked hydrodynamic and water quality modeling of the Baltic Sea based on relevant hydro-climatic outputs for inland water runoff and waterborne nutrient loading to the Baltic sea, as well as for conditions in the sea itself. This focused synthesis and analysis of hydro-climatically relevant output data of regional climate models facilitates assessment of reliability and uncertainty in projections of driver-impact changes of key importance for Baltic Sea physical, water quality and ecological conditions and their future evolution.

CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

NASA Technical Reports Server (NTRS)

Sandford, Stephen P.

2010-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of 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 provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough 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. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space scale averages that are key to understanding decadal changes.

Global Nitrous Oxide Emissions from Agricultural Soils: Magnitude and Uncertainties Associated with Input Data and Model Parameters

NASA Astrophysics Data System (ADS)

Xu, R.; Tian, H.; Pan, S.; Yang, J.; Lu, C.; Zhang, B.

2016-12-01

Human activities have caused significant perturbations of the nitrogen (N) cycle, resulting in about 21% increase of atmospheric N2O concentration since the pre-industrial era. This large increase is mainly caused by intensive agricultural activities including the application of nitrogen fertilizer and the expansion of leguminous crops. Substantial efforts have been made to quantify the global and regional N2O emission from agricultural soils in the last several decades using a wide variety of approaches, such as ground-based observation, atmospheric inversion, and process-based model. However, large uncertainties exist in those estimates as well as methods themselves. In this study, we used a coupled biogeochemical model (DLEM) to estimate magnitude, spatial, and temporal patterns of N2O emissions from global croplands in the past five decades (1961-2012). To estimate uncertainties associated with input data and model parameters, we have implemented a number of simulation experiments with DLEM, accounting for key parameter values that affect calculation of N2O fluxes (i.e., maximum nitrification and denitrification rates, N fixation rate, and the adsorption coefficient for soil ammonium and nitrate), different sets of input data including climate, land management practices (i.e., nitrogen fertilizer types, application rates and timings, with/without irrigation), N deposition, and land use and land cover change. This work provides a robust estimate of global N2O emissions from agricultural soils as well as identifies key gaps and limitations in the existing model and data that need to be investigated in the future.

Modeling Hydrological Processes in New Mexico-Texas-Mexico Border Region

NASA Astrophysics Data System (ADS)

Samimi, M.; Jahan, N. T.; Mirchi, A.

2017-12-01

Efficient allocation of limited water resources to competing use sectors is becoming increasingly critical for water-scarce regions. Understanding natural and anthropogenic processes affecting hydrological processes is key for efficient water management. We used Soil and Water Assessment Tool (SWAT) to model governing hydrologic processes in New Mexico-Texas-Mexico border region. Our study area includes the Elephant Butte Irrigation District (EBID), which manages water resources to support irrigated agriculture. The region is facing water resources challenges associated with chronic water scarcity, over-allocation, diminishing water supply, and growing water demand. Agricultural activities rely on conjunctive use of Rio Grande River water supply and groundwater withdrawal. The model is calibrated and validated under baseline conditions in the arid and semi-arid climate in order to evaluate potential impacts of climate change on the agricultural sector and regional water availability. We highlight the importance of calibrating the crop growth parameters, evapotranspiration, and groundwater recharge to provide a realistic representation of the hydrological processes and water availability in the region. Furthermore, limitations of the model and its utility to inform stakeholders will be discussed.

Recent ice ages on Mars

NASA Astrophysics Data System (ADS)

Head, James W.; Mustard, John F.; Kreslavsky, Mikhail A.; Milliken, Ralph E.; Marchant, David R.

2003-12-01

A key pacemaker of ice ages on the Earth is climatic forcing due to variations in planetary orbital parameters. Recent Mars exploration has revealed dusty, water-ice-rich mantling deposits that are layered, metres thick and latitude dependent, occurring in both hemispheres from mid-latitudes to the poles. Here we show evidence that these deposits formed during a geologically recent ice age that occurred from about 2.1 to 0.4 Myr ago. The deposits were emplaced symmetrically down to latitudes of ~30°-equivalent to Saudi Arabia and the southern United States on the Earth-in response to the changing stability of water ice and dust during variations in obliquity (the angle between Mars' pole of rotation and the ecliptic plane) reaching 30-35°. Mars is at present in an `interglacial' period, and the ice-rich deposits are undergoing reworking, degradation and retreat in response to the current instability of near-surface ice. Unlike the Earth, martian ice ages are characterized by warmer polar climates and enhanced equatorward transport of atmospheric water and dust to produce widespread smooth deposits down to mid-latitudes.

Soil moisture dynamics modeling considering multi-layer root zone.

PubMed

Kumar, R; Shankar, V; Jat, M K

2013-01-01

The moisture uptake by plant from soil is a key process for plant growth and movement of water in the soil-plant system. A non-linear root water uptake (RWU) model was developed for a multi-layer crop root zone. The model comprised two parts: (1) model formulation and (2) moisture flow prediction. The developed model was tested for its efficiency in predicting moisture depletion in a non-uniform root zone. A field experiment on wheat (Triticum aestivum) was conducted in the sub-temperate sub-humid agro-climate of Solan, Himachal Pradesh, India. Model-predicted soil moisture parameters, i.e., moisture status at various depths, moisture depletion and soil moisture profile in the root zone, are in good agreement with experiment results. The results of simulation emphasize the utility of the RWU model across different agro-climatic regions. The model can be used for sound irrigation management especially in water-scarce humid, temperate, arid and semi-arid regions and can also be integrated with a water transport equation to predict the solute uptake by plant biomass.

Recent ice ages on Mars.

PubMed

Head, James W; Mustard, John F; Kreslavsky, Mikhail A; Milliken, Ralph E; Marchant, David R

2003-12-18

A key pacemaker of ice ages on the Earth is climatic forcing due to variations in planetary orbital parameters. Recent Mars exploration has revealed dusty, water-ice-rich mantling deposits that are layered, metres thick and latitude dependent, occurring in both hemispheres from mid-latitudes to the poles. Here we show evidence that these deposits formed during a geologically recent ice age that occurred from about 2.1 to 0.4 Myr ago. The deposits were emplaced symmetrically down to latitudes of approximately 30 degrees--equivalent to Saudi Arabia and the southern United States on the Earth--in response to the changing stability of water ice and dust during variations in obliquity (the angle between Mars' pole of rotation and the ecliptic plane) reaching 30-35 degrees. Mars is at present in an 'interglacial' period, and the ice-rich deposits are undergoing reworking, degradation and retreat in response to the current instability of near-surface ice. Unlike the Earth, martian ice ages are characterized by warmer polar climates and enhanced equatorward transport of atmospheric water and dust to produce widespread smooth deposits down to mid-latitudes.

Exploring emotional climate in preservice science teacher education

NASA Astrophysics Data System (ADS)

Bellocchi, Alberto; Ritchie, Stephen M.; Tobin, Kenneth; Sandhu, Maryam; Sandhu, Satwant

2013-09-01

Classroom emotional climates (ECs) are interrelated with students' engagement with university courses. Despite growing interest in emotions and EC research, little is known about the ways in which social interactions and different subject matter mediate ECs in preservice science teacher education classes. In this study we investigated the EC and associated classroom interactions in a preservice science teacher education class. We were interested in the ways in which salient classroom interactions were related to the EC during lessons centered on debates about science-based issues (e.g., nuclear energy alternatives). Participants used audience response technology to indicate their perceptions of the EC. Analysis of conversation for salient video clips and analysis of non-verbal conduct (acoustic parameters, body movements, and facial expressions) supplemented EC data. One key contribution that this study makes to preservice science teacher education is to identify the micro-processes of successful and unsuccessful class interactions that were associated with positive and neutral EC. The structure of these interactions can inform the practice of other science educators who wish to produce positive ECs in their classes. The study also extends and explicates the construct of intensity of EC.

Hydrodynamic caracterisation of an heterogeneous aquifer system under semi-arid climate

NASA Astrophysics Data System (ADS)

Drias, T.; Toubal, A. Ch

2009-04-01

The studied zone is a part of the Mellegne's (North-East of Algeria) under pound, this zone is characterised by its semi-arid climate. The water bearing system is formed by the plio-quaternairy alluviums resting on a marley substratuim of age Eocene. The geostatiscitcs approach of the hydrodynamics parameters (Hydrolic load, transmisivity) allowed the study of their spatial distrubution (casting) by the method of Krigeage by blocks and the identification of zones with water-bearing potentialities. In this respect, the zone of Ain Chabro which, is situated in the South of the plain shows the best values of the transmisivity...... The use of a bidimensinnel model in the differences ended in the permanent regime allowed us to establish the global balence sheet (overall assessment) of the tablecloth and to refine the transmisivity field. These would vary more exactley between 10-4 to 10-2 m²/s. The method associating the probability appraoch of Krigeage to that determining the model has facilited the wedging of the model and clarified the inflitration value. Keys words: hydrodynamics, geostatiscitcs, Modeling, Chabro, Tébessa.

Microbial models with data-driven parameters predict stronger soil carbon responses to climate change.

PubMed

Hararuk, Oleksandra; Smith, Matthew J; Luo, Yiqi

2015-06-01

Long-term carbon (C) cycle feedbacks to climate depend on the future dynamics of soil organic carbon (SOC). Current models show low predictive accuracy at simulating contemporary SOC pools, which can be improved through parameter estimation. However, major uncertainty remains in global soil responses to climate change, particularly uncertainty in how the activity of soil microbial communities will respond. To date, the role of microbes in SOC dynamics has been implicitly described by decay rate constants in most conventional global carbon cycle models. Explicitly including microbial biomass dynamics into C cycle model formulations has shown potential to improve model predictive performance when assessed against global SOC databases. This study aimed to data-constrained parameters of two soil microbial models, evaluate the improvements in performance of those calibrated models in predicting contemporary carbon stocks, and compare the SOC responses to climate change and their uncertainties between microbial and conventional models. Microbial models with calibrated parameters explained 51% of variability in the observed total SOC, whereas a calibrated conventional model explained 41%. The microbial models, when forced with climate and soil carbon input predictions from the 5th Coupled Model Intercomparison Project (CMIP5), produced stronger soil C responses to 95 years of climate change than any of the 11 CMIP5 models. The calibrated microbial models predicted between 8% (2-pool model) and 11% (4-pool model) soil C losses compared with CMIP5 model projections which ranged from a 7% loss to a 22.6% gain. Lastly, we observed unrealistic oscillatory SOC dynamics in the 2-pool microbial model. The 4-pool model also produced oscillations, but they were less prominent and could be avoided, depending on the parameter values. © 2014 John Wiley & Sons Ltd.

Spectral Kernel Approach to Study Radiative Response of Climate Variables and Interannual Variability of Reflected Solar Spectrum

NASA Technical Reports Server (NTRS)

Jin, Zhonghai; Wielicki, Bruce A.; Loukachine, Constantin; Charlock, Thomas P.; Young, David; Noeel, Stefan

2011-01-01

The radiative kernel approach provides a simple way to separate the radiative response to different climate parameters and to decompose the feedback into radiative and climate response components. Using CERES/MODIS/Geostationary data, we calculated and analyzed the solar spectral reflectance kernels for various climate parameters on zonal, regional, and global spatial scales. The kernel linearity is tested. Errors in the kernel due to nonlinearity can vary strongly depending on climate parameter, wavelength, surface, and solar elevation; they are large in some absorption bands for some parameters but are negligible in most conditions. The spectral kernels are used to calculate the radiative responses to different climate parameter changes in different latitudes. The results show that the radiative response in high latitudes is sensitive to the coverage of snow and sea ice. The radiative response in low latitudes is contributed mainly by cloud property changes, especially cloud fraction and optical depth. The large cloud height effect is confined to absorption bands, while the cloud particle size effect is found mainly in the near infrared. The kernel approach, which is based on calculations using CERES retrievals, is then tested by direct comparison with spectral measurements from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) (a different instrument on a different spacecraft). The monthly mean interannual variability of spectral reflectance based on the kernel technique is consistent with satellite observations over the ocean, but not over land, where both model and data have large uncertainty. RMS errors in kernel ]derived monthly global mean reflectance over the ocean compared to observations are about 0.001, and the sampling error is likely a major component.

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.

Climate-driven vital rates do not always mean climate-driven population.

PubMed

Tavecchia, Giacomo; Tenan, Simone; Pradel, Roger; Igual, José-Manuel; Genovart, Meritxell; Oro, Daniel

2016-12-01

Current climatic changes have increased the need to forecast population responses to climate variability. A common approach to address this question is through models that project current population state using the functional relationship between demographic rates and climatic variables. We argue that this approach can lead to erroneous conclusions when interpopulation dispersal is not considered. We found that immigration can release the population from climate-driven trajectories even when local vital rates are climate dependent. We illustrated this using individual-based data on a trans-equatorial migratory seabird, the Scopoli's shearwater Calonectris diomedea, in which the variation of vital rates has been associated with large-scale climatic indices. We compared the population annual growth rate λ i , estimated using local climate-driven parameters with ρ i , a population growth rate directly estimated from individual information and that accounts for immigration. While λ i varied as a function of climatic variables, reflecting the climate-dependent parameters, ρ i did not, indicating that dispersal decouples the relationship between population growth and climate variables from that between climatic variables and vital rates. Our results suggest caution when assessing demographic effects of climatic variability especially in open populations for very mobile organisms such as fish, marine mammals, bats, or birds. When a population model cannot be validated or it is not detailed enough, ignoring immigration might lead to misleading climate-driven projections. © 2016 John Wiley & Sons Ltd.

a R-Shiny Based Phenology Analysis System and Case Study Using Digital Camera Dataset

NASA Astrophysics Data System (ADS)

Zhou, Y. K.

2018-05-01

Accurate extracting of the vegetation phenology information play an important role in exploring the effects of climate changes on vegetation. Repeated photos from digital camera is a useful and huge data source in phonological analysis. Data processing and mining on phenological data is still a big challenge. There is no single tool or a universal solution for big data processing and visualization in the field of phenology extraction. In this paper, we proposed a R-shiny based web application for vegetation phenological parameters extraction and analysis. Its main functions include phenological site distribution visualization, ROI (Region of Interest) selection, vegetation index calculation and visualization, data filtering, growth trajectory fitting, phenology parameters extraction, etc. the long-term observation photography data from Freemanwood site in 2013 is processed by this system as an example. The results show that: (1) this system is capable of analyzing large data using a distributed framework; (2) The combination of multiple parameter extraction and growth curve fitting methods could effectively extract the key phenology parameters. Moreover, there are discrepancies between different combination methods in unique study areas. Vegetation with single-growth peak is suitable for using the double logistic module to fit the growth trajectory, while vegetation with multi-growth peaks should better use spline method.

Composition and structure of Pinus koraiensis mixed forest respond to spatial climatic changes.

PubMed

Zhang, Jingli; Zhou, Yong; Zhou, Guangsheng; Xiao, Chunwang

2014-01-01

Although some studies have indicated that climate changes can affect Pinus koraiensis mixed forest, the responses of composition and structure of Pinus koraiensis mixed forests to climatic changes are unknown and the key climatic factors controlling the composition and structure of Pinus koraiensis mixed forest are uncertain. Field survey was conducted in the natural Pinus koraiensis mixed forests along a latitudinal gradient and an elevational gradient in Northeast China. In order to build the mathematical models for simulating the relationships of compositional and structural attributes of the Pinus koraiensis mixed forest with climatic and non-climatic factors, stepwise linear regression analyses were performed, incorporating 14 dependent variables and the linear and quadratic components of 9 factors. All the selected new models were computed under the +2°C and +10% precipitation and +4°C and +10% precipitation scenarios. The Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month were observed to be key climatic factors controlling the stand densities and total basal areas of Pinus koraiensis mixed forest. Increased summer temperatures and precipitations strongly enhanced the stand densities and total basal areas of broadleaf trees but had little effect on Pinus koraiensis under the +2°C and +10% precipitation scenario and +4°C and +10% precipitation scenario. These results show that the Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month are key climatic factors which shape the composition and structure of Pinus koraiensis mixed forest. Although the Pinus koraiensis would persist, the current forests dominated by Pinus koraiensis in the region would all shift and become broadleaf-dominated forests due to the dramatic increase of broadleaf trees under the future global warming and increased precipitation.

Construction of Gridded Daily Weather Data and its Use in Central-European Agroclimatic Study

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Trnka, M.; Skalak, P.

2013-12-01

The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series, interpolated, and then modified according to the GCM- or RCM-based climate change scenarios. The present contribution, in which the parametric daily weather generator M&Rfi is linked to the high-resolution RCM output (ALADIN-Climate/CZ model) and GCM-based climate change scenarios, consists of two parts: The first part focuses on a methodology. Firstly, the gridded WG representing the baseline climate is created by merging information from observations and high resolution RCM outputs. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with RCM-simulated weather series vs. spatially scarcer observations. To represent the future climate, the WG parameters are modified according to the 'WG-friendly' climate change scenarios. These scenarios are defined in terms of changes in WG parameters and include - apart from changes in the means - changes in WG parameters, which represent the additional characteristics of the weather series (e.g. probability of wet day occurrence and lag-1 autocorrelation of daily mean temperature). The WG-friendly scenarios for the present experiment are based on comparison of future vs baseline surface weather series simulated by GCMs from a CMIP3 database. The second part will present results of climate change impact study based on an above methodology applied to Central Europe. The changes in selected climatic (focusing on the extreme precipitation and temperature characteristics) and agroclimatic (including number of days during vegetation season with heat and drought stresses) characteristics will be analysed. In discussing the results, the emphasis will be put on 'added value' of various aspects of above methodology (e.g. inclusion of changes in 'advanced' WG parameters into the climate change scenarios). Acknowledgements: The present experiment is made within the frame of projects WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR), ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), and VALUE (COST ES 1102 action).

Aroma types of flue-cured tobacco in China: spatial distribution and association with climatic factors

NASA Astrophysics Data System (ADS)

Yang, Chao; Wu, Wei; Wu, Shu-Cheng; Liu, Hong-Bin; Peng, Qing

2014-02-01

Aroma types of flue-cured tobacco (FCT) are classified into light, medium, and heavy in China. However, the spatial distribution of FCT aroma types and the relationships among aroma types, chemical parameters, and climatic variables were still unknown at national scale. In the current study, multi-year averaged chemical parameters (total sugars, reducing sugars, nicotine, total nitrogen, chloride, and K2O) of FCT samples with grade of C3F and climatic variables (mean, minimum and maximum temperatures, rainfall, relative humidity, and sunshine hours) during the growth periods were collected from main planting areas across China. Significant relationships were found between chemical parameters and climatic variables ( p < 0.05). A spatial distribution map of FCT aroma types were produced using support vector machine algorithms and chemical parameters. Significant differences in chemical parameters and climatic variables were observed among the three aroma types based on one-way analysis of variance ( p < 0.05). Areas with light aroma type had significantly lower values of mean, maximum, and minimum temperatures than regions with medium and heavy aroma types ( p < 0.05). Areas with heavy aroma type had significantly lower values of rainfall and relative humidity and higher values of sunshine hours than regions with light and medium aroma types ( p < 0.05). The output produced by classification and regression trees showed that sunshine hours, rainfall, and maximum temperature were the most important factors affecting FCT aroma types at national scale.

Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model.

PubMed

Jiang, Yueyang; Zhuang, Qianlai; Schaphoff, Sibyll; Sitch, Stephen; Sokolov, Andrei; Kicklighter, David; Melillo, Jerry

2012-03-01

This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45(o)N and polewards) for the period 1900-2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue.

What’s Needed from Climate Modeling to Advance Actionable Science for Water Utilities?

NASA Astrophysics Data System (ADS)

Barsugli, J. J.; Anderson, C. J.; Smith, J. B.; Vogel, J. M.

2009-12-01

“…perfect information on climate change is neither available today nor likely to be available in the future, but … over time, as the threats climate change poses to our systems grow more real, predicting those effects with greater certainty is non-discretionary. We’re not yet at a level at which climate change projections can drive climate change adaptation.” (Testimony of WUCA Staff Chair David Behar to the House Committee on Science and Technology, May 5, 2009) To respond to this challenge, the Water Utility Climate Alliance (WUCA) has sponsored a white paper titled “Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change. ” This report concerns how investments in the science of climate change, and in particular climate modeling and downscaling, can best be directed to help make climate projections more actionable. The meaning of “model improvement” can be very different depending on whether one is talking to a climate model developer or to a water manager trying to incorporate climate projections in to planning. We first surveyed the WUCA members on present and potential uses of climate model projections and on climate inputs to their various system models. Based on those surveys and on subsequent discussions, we identified four dimensions along which improvement in modeling would make the science more “actionable”: improved model agreement on change in key parameters; narrowing the range of model projections; providing projections at spatial and temporal scales that match water utilities system models; providing projections that water utility planning horizons. With these goals in mind we developed four options for improving global-scale climate modeling and three options for improving downscaling that will be discussed. However, there does not seem to be a single investment - the proverbial “magic bullet” -- which will substantially reduce the range of model projections at the scales at which utility planning is conducted. In the near term we feel strongly that water utilities and climate scientists should work together to leverage the upcoming Coupled Model Intercomparison Project, Phase 5 (CMIP5; a coordinated set climate model experiments that will be used to support the upcoming IPCC Fifth Assessment) to better benefit water utilities. In the longer term, even with model and downscaling improvements, it is very likely that substantial uncertainty about future climate change at the desired spatial and temporal scales will remain. Nonetheless, there is no doubt the climate is changing, and the challenge is to work with what we have, or what we can reasonably expect to have in the coming years to make the best decisions we can.

A history of the science and politics of climate change: the role of the Intergovernmental Panel on Climate Change

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

Bolin, B.

2007-11-15

In response to growing concern about human-induced global climate change, the UN Intergovernmental Panel on Climate Change (IPCC) was formed in 1988. Written by its first Chairman, this book is a unique overview of the history of the IPCC. It describes and evaluates the intricate interplay between key factors in the science and politics of climate change, the strategy that has been followed, and the regretfully slow pace in getting to grips with the uncertainties that have prevented earlier action being taken. The book also highlights the emerging conflict between establishing a sustainable global energy system and preventing a seriousmore » change in global climate. Contents are: Part I. The Early History of the Climate Change Issue: 1. Nineteenth century discoveries; 2. The natural carbon cycle and life on earth; 3. Global research initiatives in meteorology and climatology; 4. Early international assessments of climate change; Part II. The Climate Change Issue Becomes One of Global Concern: 5. Setting the stage; 6. The scientific basis for a climate convention; 7. Serving the Intergovernmental Negotiating Committee; 8. The Second IPP Assessment Report; 9. In the aftermath of the IPCC Second Assessment; 10. The Kyoto Protocol is agreed and a third assessment begun; 11. A decade of hesitance and slow progress; Part III. A Turning Point in Addressing Climate Change?: 12. Key scientific finding of prime political relevance; 13. Climate change and the future global energy supply system; Concluding remarks. 9 figs.« less

Combining wood anatomy and stable isotope variations in a 600-year multi-parameter climate reconstruction from Corsican black pine

NASA Astrophysics Data System (ADS)

Szymczak, Sonja; Hetzer, Timo; Bräuning, Achim; Joachimski, Michael M.; Leuschner, Hanns-Hubert; Kuhlemann, Joachim

2014-10-01

We present a new multi-parameter dataset from Corsican black pine growing on the island of Corsica in the Western Mediterranean basin covering the period AD 1410-2008. Wood parameters measured include tree-ring width, latewood width, earlywood width, cell lumen area, cell width, cell wall thickness, modelled wood density, as well as stable carbon and oxygen isotopes. We evaluated the relationships between different parameters and determined the value of the dataset for climate reconstructions. Correlation analyses revealed that carbon isotope ratios are influenced by cell parameters determining cell size, whereas oxygen isotope ratios are influenced by cell parameters determining the amount of transportable water in the xylem. A summer (June to August) precipitation reconstruction dating back to AD 1185 was established based on tree-ring width. No long-term trends or pronounced periods with extreme high/low precipitation are recorded in our reconstruction, indicating relatively stable moisture conditions over the entire time period. By comparing the precipitation reconstruction with a summer temperature reconstruction derived from the carbon isotope chronologies, we identified summers with extreme climate conditions, i.e. warm-dry, warm-wet, cold-dry and cold-wet. Extreme climate conditions during summer months were found to influence cell parameter characteristics. Cold-wet summers promote the production of broad latewood composed of wide and thin-walled tracheids, while warm-wet summers promote the production of latewood with small thick-walled cells. The presented dataset emphasizes the potential of multi-parameter wood analysis from one tree species over long time scales.

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-01-01

Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We apply support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicts model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures are determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations are the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Potential impacts of climate change on soil erosion vulnerability across the conterminous United States

Treesearch

C. Segura; G. Sun; S. McNulty; Y. Zhang

2014-01-01

Rainfall runoff erosivity (R) is one key climate factor that controls water erosion. Quantifying the effects of climate change-induced erosivity change is important for identifying critical regions prone to soil erosion under a changing environment. In this study we first evaluate the changes of R from 1970 to 2090 across the United States under nine climate conditions...

Anticipating changes to future connectivity within a network of marine protected areas.

PubMed

Coleman, Melinda A; Cetina-Heredia, Paulina; Roughan, Moninya; Feng, Ming; van Sebille, Erik; Kelaher, Brendan P

2017-09-01

Continental boundary currents are projected to be altered under future scenarios of climate change. As these currents often influence dispersal and connectivity among populations of many marine organisms, changes to boundary currents may have dramatic implications for population persistence. Networks of marine protected areas (MPAs) often aim to maintain connectivity, but anticipation of the scale and extent of climatic impacts on connectivity are required to achieve this critical conservation goal in a future of climate change. For two key marine species (kelp and sea urchins), we use oceanographic modelling to predict how continental boundary currents are likely to change connectivity among a network of MPAs spanning over 1000 km of coastline off the coast of eastern Australia. Overall change in predicted connectivity among pairs of MPAs within the network did not change significantly over and above temporal variation within climatic scenarios, highlighting the need for future studies to incorporate temporal variation in dispersal to robustly anticipate likely change. However, the intricacies of connectivity between different pairs of MPAs were noteworthy. For kelp, poleward connectivity among pairs of MPAs tended to increase in the future, whereas equatorward connectivity tended to decrease. In contrast, for sea urchins, connectivity among pairs of MPAs generally decreased in both directions. Self-seeding within higher-latitude MPAs tended to increase, and the role of low-latitude MPAs as a sink for urchins changed significantly in contrasting ways. These projected changes have the potential to alter important genetic parameters with implications for adaptation and ecosystem vulnerability to climate change. Considering such changes, in the context of managing and designing MPA networks, may ensure that conservation goals are achieved into the future. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Deterministic or Probabilistic - Robustness or Resilience: How to Respond to Climate Change?

NASA Astrophysics Data System (ADS)

Plag, H.; Earnest, D.; Jules-Plag, S.

2013-12-01

Our response to climate change is dominated by a deterministic approach that emphasizes the interaction between only the natural and the built environment. But in the non-ergodic world of unprecedented climate change, social factors drive recovery from unforeseen Black Swans much more than natural or built ones. Particularly the sea level rise discussion focuses on deterministic predictions, accounting for uncertainties in major driving processes with a set of forcing scenarios and public deliberations on which of the plausible trajectories is most likely. Science focuses on the prediction of future climate change, and policies focus on mitigation of both climate change itself and its impacts. The deterministic approach is based on two basic assumptions: 1) Climate change is an ergodic process; 2) The urban coast is a robust system. Evidence suggests that these assumptions may not hold. Anthropogenic changes are pushing key parameters of the climate system outside of the natural range of variability from the last 1 Million years, creating the potential for environmental Black Swans. A probabilistic approach allows for non-ergodic processes and focuses more on resilience, hence does not depend on the two assumptions. Recent experience with hurricanes revealed threshold limitations of the built environment of the urban coast, which, once exceeded, brought to the forefront the importance of the social fabric and social networking in evaluating resilience. Resilience strongly depends on social capital, and building social capital that can create resilience must be a key element in our response to climate change. Although social capital cannot mitigate hazards, social scientists have found that communities rich in strong norms of cooperation recover more quickly than communities without social capital. There is growing evidence that the built environment can affect the social capital of a community, for example public health and perceptions of public safety. This suggests an intriguing hypothesis: disaster risk reduction programs need to account for whether they also facilitate the public trust, cooperation, and communication needed to recover from a disaster. Our work in the Hampton Roads area, where the probability of hazardous flooding and inundation events exceeding the thresholds of the infrastructure is high, suggests that to facilitate the paradigm shift from the deterministic to a probabilistic approach, natural sciences have to focus on hazard probabilities, while engineering and social sciences have to work together to understand how interactions of the built and social environments impact robustness and resilience. The current science-policy relationship needs to be augmented by social structures that can learn from previous unexpected events. In this response to climate change, science does not have the primary goal to reduce uncertainties and prediction errors, but rather to develop processes that can utilize uncertainties and surprises to increase robustness, strengthen resilience, and reduce fragility of the social systems during times when infrastructure fails.

Swimming against the tide: resilience of a riverine turtle to recurrent extreme environmental events

PubMed Central

Jergenson, Abigail M.; Miller, David A. W.; Neuman-Lee, Lorin A.; Warner, Daniel A.; Janzen, Fredric J.

2014-01-01

Extreme environmental events (EEEs) are likely to exert deleterious effects on populations. From 1996 to 2012 we studied the nesting dynamics of a riverine population of painted turtles (Chrysemys picta) that experienced seven years with significantly definable spring floods. We used capture–mark–recapture methods to estimate the relationships between more than 5 m and more than 6 m flood events and population parameters. Contrary to expectations, flooding was not associated with annual differences in survival, recruitment or annual population growth rates of the adult female segment of the population. These findings suggest that female C. picta exhibit resiliency to key EEE, which are expected to increase in frequency under climate change. PMID:24621555

Watershed Adaptation Measures to Climate Change Impacts: A case of Kiha Watershed in Albertine Graben

NASA Astrophysics Data System (ADS)

Zizinga, A.

2017-12-01

Watershed Adaptation Measures to Climate Change Impacts: A case of Kiha Watershed in Albertine GrabenAlex Zizinga1, Moses Tenywa2, Majaliwa Jackson Gilbert1, 1Makerere University, Department of Environmental Sciences, O Box 7062, Kampala, Uganda 1Makerere University, Department of Agricultural Production, P.O Box 7062, Kampala, Uganda Corresponding author: azizinga@caes.mak.ac.ug AbstractThe most pressing issues local communities in Uganda are facing result from land-use and land cover changes exacerbated by climate change impacts. A key issue is the documentation of land-cover changes visible with the ongoing clearance of remaining forests, bush-lands and wetlands for expanding farmland for sugarcane production, producing charcoal and collecting firewood for local distilleries using imported molasses. Decision-makers, resource managers, farmers and practitioners must build their capacity for adaptive measures. Here we present the potential impacts of climate change on watershed hydrological processes in the River Kiha Watershed, located in Western Uganda, Lake Albert Water Management Zone, by using social learning techniques incorporating water users, local stakeholders and researchers. The research team examined different farming and economic activities within the watershed to assess their impacts on catchment water resources, namely on water quality and discharge of river Kiha. We present the impacts of locally induced climate change, which are already manifested in increasing seasonal variability of rainfall. The study aims at answering questions posed by local communities and stakeholders about climate change and its effects on livelihood and key resources, specifically water and soils within the Kiha watershed. Key words: Climate change impacts, Social Learning and Watershed Management

Improving and Understanding Climate Models: Scale-Aware Parameterization of Cloud Water Inhomogeneity and Sensitivity of MJO Simulation to Physical Parameters in a Convection Scheme

NASA Astrophysics Data System (ADS)

Xie, Xin

Microphysics and convection parameterizations are two key components in a climate model to simulate realistic climatology and variability of cloud distribution and the cycles of energy and water. When a model has varying grid size or simulations have to be run with different resolutions, scale-aware parameterization is desirable so that we do not have to tune model parameters tailored to a particular grid size. The subgrid variability of cloud hydrometers is known to impact microphysics processes in climate models and is found to highly depend on spatial scale. A scale- aware liquid cloud subgrid variability parameterization is derived and implemented in the Community Earth System Model (CESM) in this study using long-term radar-based ground measurements from the Atmospheric Radiation Measurement (ARM) program. When used in the default CESM1 with the finite-volume dynamic core where a constant liquid inhomogeneity parameter was assumed, the newly developed parameterization reduces the cloud inhomogeneity in high latitudes and increases it in low latitudes. This is due to both the smaller grid size in high latitudes, and larger grid size in low latitudes in the longitude-latitude grid setting of CESM as well as the variation of the stability of the atmosphere. The single column model and general circulation model (GCM) sensitivity experiments show that the new parameterization increases the cloud liquid water path in polar regions and decreases it in low latitudes. Current CESM1 simulation suffers from the bias of both the pacific double ITCZ precipitation and weak Madden-Julian oscillation (MJO). Previous studies show that convective parameterization with multiple plumes may have the capability to alleviate such biases in a more uniform and physical way. A multiple-plume mass flux convective parameterization is used in Community Atmospheric Model (CAM) to investigate the sensitivity of MJO simulations. We show that MJO simulation is sensitive to entrainment rate specification. We found that shallow plumes can generate and sustain the MJO propagation in the model.

A global satellite environmental data record derived from AMSR-E and AMSR2 microwave Earth observations

NASA Astrophysics Data System (ADS)

Du, Jinyang; Kimball, John S.; Jones, Lucas A.; Kim, Youngwook; Glassy, Joseph; Watts, Jennifer D.

2017-11-01

Spaceborne microwave remote sensing is widely used to monitor global environmental changes for understanding hydrological, ecological, and climate processes. A new global land parameter data record (LPDR) was generated using similar calibrated, multifrequency brightness temperature (Tb) retrievals from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2). The resulting LPDR provides a long-term (June 2002-December 2015) global record of key environmental observations at a 25 km grid cell resolution, including surface fractional open water (FW) cover, atmosphere precipitable water vapor (PWV), daily maximum and minimum surface air temperatures (Tmx and Tmn), vegetation optical depth (VOD), and surface volumetric soil moisture (VSM). Global mapping of the land parameter climatology means and seasonal variability over the full-year records from AMSR-E (2003-2010) and AMSR2 (2013-2015) observation periods is consistent with characteristic global climate and vegetation patterns. Quantitative comparisons with independent observations indicated favorable LPDR performance for FW (R ≥ 0.75; RMSE ≤ 0.06), PWV (R ≥ 0.91; RMSE ≤ 4.94 mm), Tmx and Tmn (R ≥ 0.90; RMSE ≤ 3.48 °C), and VSM (0.63 ≤ R ≤ 0.84; bias-corrected RMSE ≤ 0.06 cm3 cm-3). The LPDR-derived global VOD record is also proportional to satellite-observed NDVI (GIMMS3g) seasonality (R ≥ 0.88) due to the synergy between canopy biomass structure and photosynthetic greenness. Statistical analysis shows overall LPDR consistency but with small biases between AMSR-E and AMSR2 retrievals that should be considered when evaluating long-term environmental trends. The resulting LPDR and potential updates from continuing AMSR2 operations provide for effective global monitoring of environmental parameters related to vegetation activity, terrestrial water storage, and mobility and are suitable for climate and ecosystem studies. The LPDR dataset is publicly available at http://files.ntsg.umt.edu/data/LPDR_v2/.<

Simulation of future groundwater recharge using a climate model ensemble and SAR-image based soil parameter distributions - A case study in an intensively-used Mediterranean catchment.

PubMed

Herrmann, Frank; Baghdadi, Nicolas; Blaschek, Michael; Deidda, Roberto; Duttmann, Rainer; La Jeunesse, Isabelle; Sellami, Haykel; Vereecken, Harry; Wendland, Frank

2016-02-01

We used observed climate data, an ensemble of four GCM-RCM combinations (global and regional climate models) and the water balance model mGROWA to estimate present and future groundwater recharge for the intensively-used Thau lagoon catchment in southern France. In addition to a highly resolved soil map, soil moisture distributions obtained from SAR-images (Synthetic Aperture Radar) were used to derive the spatial distribution of soil parameters covering the full simulation domain. Doing so helped us to assess the impact of different soil parameter sources on the modelled groundwater recharge levels. Groundwater recharge was simulated in monthly time steps using the ensemble approach and analysed in its spatial and temporal variability. The soil parameters originating from both sources led to very similar groundwater recharge rates, proving that soil parameters derived from SAR images may replace traditionally used soil maps in regions where soil maps are sparse or missing. Additionally, we showed that the variance in different GCM-RCMs influences the projected magnitude of future groundwater recharge change significantly more than the variance in the soil parameter distributions derived from the two different sources. For the period between 1950 and 2100, climate change impacts based on the climate model ensemble indicated that overall groundwater recharge will possibly show a low to moderate decrease in the Thau catchment. However, as no clear trend resulted from the ensemble simulations, reliable recommendations for adapting the regional groundwater management to changed available groundwater volumes could not be derived. Copyright © 2015 Elsevier B.V. All rights reserved.

Psychological research and global climate change

NASA Astrophysics Data System (ADS)

Clayton, Susan; Devine-Wright, Patrick; Stern, Paul C.; Whitmarsh, Lorraine; Carrico, Amanda; Steg, Linda; Swim, Janet; Bonnes, Mirilia

2015-07-01

Human behaviour is integral not only to causing global climate change but also to responding and adapting to it. Here, we argue that psychological research should inform efforts to address climate change, to avoid misunderstandings about human behaviour and motivations that can lead to ineffective or misguided policies. We review three key research areas: describing human perceptions of climate change; understanding and changing individual and household behaviour that drives climate change; and examining the human impacts of climate change and adaptation responses. Although much has been learned in these areas, we suggest important directions for further research.

Argumentation as a Strategy for Increasing Preservice Teachers' Understanding of Climate Change, a Key Global Socioscientific Issue

ERIC Educational Resources Information Center

Lambert, Julie L.; Bleicher, Robert E.

2017-01-01

Findings of this study suggest that scientific argumentation can play an effective role in addressing complex socioscientific issues (i.e. global climate change). This research examined changes in preservice teachers' knowledge and perceptions about climate change in an innovative undergraduate-level elementary science methods course. The…

Using Education to Bring Climate Change Adaptation to Pacific Communities

ERIC Educational Resources Information Center

Vize, Sue

2012-01-01

Traditional communities remain a dominant feature in the Pacific and are key players in land and sea management. Fostering improved climate literacy is therefore essential to equip communities to respond to the current and future challenges posed by climate change in the region. Increased understanding and development of skills to respond to the…

Raising Awareness about Climate Change in Pacific Communities

ERIC Educational Resources Information Center

McNamara, Karen Elizabeth

2013-01-01

Community-based climate change projects in the Pacific typically seek to raise the awareness of locals about the consequences of climate change and changing weather patterns. A key concern is that such activities might be done in an ad hoc manner, with little consideration of local relevance, audience and the integration of local experiences and…

School Climate Improvement Action Guide for Noninstructional Staff. School Climate Improvement Resource Package

ERIC Educational Resources Information Center

National Center on Safe Supportive Learning Environments, 2017

2017-01-01

Improving school climate takes time and commitment from a variety of people in a variety of roles. This document outlines key action steps that noninstructional staff--including guidance counselors, social workers, school psychologists, office staff, bus drivers, maintenance and facility staff, and food service staff--can take to support school…

Academic Social Climate--A Key Aspect in Architectural Studies

ERIC Educational Resources Information Center

Davidovitch, Nitza; Casakin, Hernan

2015-01-01

The present research investigates academic social climate in architectural studies as perceived by students. It studies the importance that the various measures of academic social climate have in the studio and in architectural classes. It also investigates the relation between the personal background of students and their sense of academic social…

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.

The Impact of Market Orientation on Patient Safety Climate Among Hospital Nurses.

PubMed

Weng, Rhay-Hung; Chen, Jung-Chien; Pong, Li-Jung; Chen, Li-Mei; Lin, Tzu-Chi

2016-03-01

Improving market orientation and patient safety have become the key concerns of nursing management. For nurses, establishing a patient safety climate is the key to enhancing nursing quality. This study explores how market orientation affects the climate of patient safety among hospital nurses. We proposed adopting a cross-sectional research design and using questionnaires to collect responses from nurses working in two Taiwanese hospitals. Three-hundred and forty-three valid samples were obtained. Multiple regression and path analyses were conducted to test the study. Market orientation was defined as the combination of customer orientation, competitor orientation, and interfunctional coordination. Customer orientation directly affects the climate of patient safety. Although the findings only supported Hypothesis 1, competitor orientation and interfunctional coordination positively affected the patient safety climate through the mediating effects of hospital support for staff. Health care managers could encourage nurses to adopt customer-oriented perspectives to enhance their nursing care. In addition, to enhance competitor orientation, interfunctional coordination, and the patient safety climate, hospital managers could strengthen their support for staff members. © The Author(s) 2014.

Understanding the effect of watershed characteristic on the runoff using SCS curve number

NASA Astrophysics Data System (ADS)

Damayanti, Frieta; Schneider, Karl

2015-04-01

Runoff modeling is a key component in watershed management. The temporal course and amount of runoff is a complex function of a multitude of parameters such as climate, soil, topography, land use, and water management. Against the background of the current rapid environmental change, which is due to both i) man-made changes (e.g. urban development, land use change, water management) as well as ii) changes in the natural systems (e.g. climate change), understanding and predicting the impacts of these changes upon the runoff is very important and affects the wellbeing of many people living in the watershed. A main tool for predictions is hydrologic models. Particularly process based models are the method of choice to assess the impact of land use and climate change. However, many regions which experience large changes in the watersheds can be described as rather data poor, which limits the applicability of such models. This is particularly also true for the Telomoyo Watershed (545 km2) which is located in southern part of Central Java province. The average annual rainfall of the study area reaches 2971 mm. Irrigated paddy field are the dominating land use (35%), followed by built-up area and dry land agriculture. The only available soil map is the FAO soil digital map of the world, which provides rather general soil information. A field survey accompanied by a lab analysis 65 soil samples of was carried out to provide more detailed soil texture information. The soil texture map is a key input in the SCS method to define hydrological soil groups. In the frame of our study on 'Integrated Analysis on Flood Risk of Telomoyo Watershed in Response to the Climate and Land Use Change' funded by the German Academic Exchange service (DAAD) we analyzed the sensitivity of the modeled runoff upon the choice of the method to estimate the CN values using the SCS-CN method. The goal of this study is to analyze the impact of different data sources on the curve numbers and the estimated runoff. CN values were estimated using the field measurements of soil textures for different combinations of land use and topography. To transfer the local soil texture measurements to the watershed domain a statistical analysis using the frequency distribution of the measured soil textures is applied and used to derive the effective CN value for a given land use, topography and soil texture combination. Since the curve numbers change as a function of parameter combinations, the effect of different methods to estimate the curve number upon the runoff is analyzed and compared to the straight forward method of using the data from the FAO soil map.

Fifth IPCC Assessment Report Now Out

NASA Astrophysics Data System (ADS)

Kundzewicz, Zbigniew W.

2014-01-01

The Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) is now available. It provides policymakers with an assessment of information on climate change, its impacts and possible response options (adaptation and mitigation). Summaries for policymakers of three reports of IPCC working groups and of the Synthesis Report have now been approved by IPCC plenaries. This present paper reports on the most essential findings in AR5. It briefly informs on the contents of reports of all IPCC working groups. It discusses the physical science findings, therein observed changes (ubiquitous warming, shrinking cryosphere, sea level rise, changes in precipitation and extremes, and biogeochemical cycles). It deals with the drivers of climate change, progress in climate system understanding (evaluation of climate models, quantification of climate system responses), and projections for the future. It reviews impacts, adaptation and vulnerability, including observed changes, key risks, key reasons for concern, sectors and systems, and managing risks and building resilience. Finally, mitigation of climate change is discussed, including greenhouse gas emissions in the past, present and future, and mitigation in sectors. It is hoped that the present article will encourage the readership of this journal to dive into the AR5 report that provides a wealth of useful information.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

NASA Astrophysics Data System (ADS)

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-05-01

climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

USGS Publications Warehouse

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-01-01

Natural climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Predicting lodgepole pine site index from climatic parameters in Alberta.

Treesearch

Robert A. Monserud; Shongming Huang; Yuqing Yang

2006-01-01

We sought to evaluate the impact of climatic variables on site productivity of lodgepole pine (Pinus contorta var. latifolia Engelm.) for the province of Alberta. Climatic data were obtained from the Alberta Climate Model, which is based on 30-year normals from the provincial weather station network. Mapping methods were based...

Climate Prediction Center - Monitoring and Data

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News monthly data, time series, and maps for various climate parameters, such as precipitation, temperature Oscillations (ENSO) and other climate patterns such as the North Atlantic and Pacific Decadal Oscillations, and

Social representations of climate change in Swedish lay focus groups: local or distant, gradual or catastrophic?

PubMed

Wibeck, Victoria

2014-02-01

This paper explores social representations of climate change, investigating how climate change is discussed by Swedish laypeople interacting in focus group interviews. The analysis focuses on prototypical examples and metaphors, which were key devices for objectifying climate change representations. The paper analyzes how the interaction of focus group participants with other speakers, ideas, arguments, and broader social representations shaped their representations of climate change. Climate change was understood as a global but distant issue with severe consequences. There was a dynamic tension between representations of climate change as a gradual vs. unpredictable process. Implications for climate change communication are discussed.

Past climate variability and change in the Arctic and at high latitudes

USGS Publications Warehouse

Alley, Richard B.; Brigham-Grette, Julie; Miller, Gifford H.; Polyak, Leonid; ,; ,; ,

2009-01-01

Paleoclimate records play a key role in our understanding of Earth's past and present climate system and in our confidence in predicting future climate changes. Paleoclimate data help to elucidate past and present active mechanisms of climate change by placing the short instrumental record into a longer term context and by permitting models to be tested beyond the limited time that instrumental measurements have been available.

School Climate and Planned Educational Change: A Review and Critique of the Literature. Working Paper 279.

ERIC Educational Resources Information Center

Kasten, Katherine Lewellan

This paper examines the concept of school climate as a key factor in the success of planned change in elementary schools. Beginning with a general review of the literature on organizational climate and using as its basis three major reviews that appeared in the mid-1970s, the paper defines climate, examines variables that have been used as part of…

Climate change: potential implications for Ireland's biodiversity

NASA Astrophysics Data System (ADS)

Donnelly, Alison

2018-03-01

A national biodiversity and climate change adaptation plan is being developed for Ireland by the Department of Communications, Climate Action, and Environment. In order to inform such a plan, it was necessary to review and synthesize some of the recent literature pertaining to the impact of climate change on biodiversity in Ireland. Published research on this topic fell within three broad categories: (i) changes in the timing of life-cycle events (phenology) of plants, birds, and insects; (ii) changes in the geographic range of some bird species; and (iii) changes in the suitable climatic zones of key habitats and species. The synthesis revealed evidence of (i) a trend towards earlier spring activity of plants, birds, and insects which may result in a change in ecosystem function; (ii) an increase in the number of bird species; and (iii) both increases and decreases in the suitable climatic area of key habitats and species, all of which are expected to impact Ireland's future biodiversity. This process identified data gaps and limitations in available information both of which could be used to inform a focused research strategy. In addition, it raises awareness of the potential implications of climate change for biodiversity in Ireland and elsewhere and demonstrates the need for biodiversity conservation plans to factor climate change into future designs.

Climate change: potential implications for Ireland's biodiversity.

PubMed

Donnelly, Alison

2018-03-12

A national biodiversity and climate change adaptation plan is being developed for Ireland by the Department of Communications, Climate Action, and Environment. In order to inform such a plan, it was necessary to review and synthesize some of the recent literature pertaining to the impact of climate change on biodiversity in Ireland. Published research on this topic fell within three broad categories: (i) changes in the timing of life-cycle events (phenology) of plants, birds, and insects; (ii) changes in the geographic range of some bird species; and (iii) changes in the suitable climatic zones of key habitats and species. The synthesis revealed evidence of (i) a trend towards earlier spring activity of plants, birds, and insects which may result in a change in ecosystem function; (ii) an increase in the number of bird species; and (iii) both increases and decreases in the suitable climatic area of key habitats and species, all of which are expected to impact Ireland's future biodiversity. This process identified data gaps and limitations in available information both of which could be used to inform a focused research strategy. In addition, it raises awareness of the potential implications of climate change for biodiversity in Ireland and elsewhere and demonstrates the need for biodiversity conservation plans to factor climate change into future designs.

Health risks of climate change in the World Health Organization South-East Asia Region.

PubMed

Bowen, Kathryn J; Ebi, Kristie L

2017-09-01

Countries in the World Health Organization (WHO) South-East Asia Region are particularly vulnerable to a changing climate. Changes in extreme weather events, undernutrition and the spread of infectious diseases are projected to increase the number of deaths due to climate change by 2030, indicating the need to strengthen activities for adaptation and mitigation. With support from the WHO Regional Office for South-East Asia and others, countries have started to include climate change as a key consideration in their national public health policies. Further efforts are needed to develop evidence-based responses; garner the necessary support from partner ministries; and access funding for activities related to health and climate change. National action plans for climate change generally identify health as one of their priorities; however, limited information is available on implementation processes, including which ministries and departments would be involved; the time frame; stakeholder responsibilities; and how the projects would be financed. While progress is being made, efforts are needed to increase the capacity of health systems to manage the health risks of climate change in South-East Asia, if population health is to be protected and strengthened while addressing changing weather and climate patterns. Enhancing the resilience of health systems is key to ensuring a sustainable path to improved planetary and population health.

The impacts of climate change in coastal marine systems.

PubMed

Harley, Christopher D G; Randall Hughes, A; Hultgren, Kristin M; Miner, Benjamin G; Sorte, Cascade J B; Thornber, Carol S; Rodriguez, Laura F; Tomanek, Lars; Williams, Susan L

2006-02-01

Anthropogenically induced global climate change has profound implications for marine ecosystems and the economic and social systems that depend upon them. The relationship between temperature and individual performance is reasonably well understood, and much climate-related research has focused on potential shifts in distribution and abundance driven directly by temperature. However, recent work has revealed that both abiotic changes and biological responses in the ocean will be substantially more complex. For example, changes in ocean chemistry may be more important than changes in temperature for the performance and survival of many organisms. Ocean circulation, which drives larval transport, will also change, with important consequences for population dynamics. Furthermore, climatic impacts on one or a few 'leverage species' may result in sweeping community-level changes. Finally, synergistic effects between climate and other anthropogenic variables, particularly fishing pressure, will likely exacerbate climate-induced changes. Efforts to manage and conserve living marine systems in the face of climate change will require improvements to the existing predictive framework. Key directions for future research include identifying key demographic transitions that influence population dynamics, predicting changes in the community-level impacts of ecologically dominant species, incorporating populations' ability to evolve (adapt), and understanding the scales over which climate will change and living systems will respond.

Effects of slope aspect and site elevation on seasonal soil carbon dynamics in a forest catchment in the Austrian Limestone Alps

NASA Astrophysics Data System (ADS)

Kobler, Johannes; Zehetgruber, Bernhard; Jandl, Robert; Dirnböck, Thomas; Schindlbacher, Andreas

2017-04-01

Own to the complexity of landscape morphology, mountainous landscapes are characterized by substantial changes of site parameters (i.e. elevation, slope, aspect) within short distances. As these site parameters affect the spatial-temporal dynamics of landscape climate and therefore the spatial patterns of forest carbon (C) distribution, they pose a substantial impact on landscape-related soil C dynamics. Aspect and elevation form natural temperature gradients and thereby can be used as a surrogate to infer to potential climate change effects on forest C. We aimed at studying how slope aspect affected soil respiration, soil C stocks, tree increment and litter production along two elevation gradients in the Zöbelboden catchment, northern limestone Alps, Austria during 2015 and 2016. A preliminary assessment showed that soil respiration was significantly higher at the west facing slope across all elevations. Soil temperature was only slightly higher at the west facing slope, and warmer soil only partly explained the large difference in soil respiration between east and west facing slopes. Aspect had no clear effect on soil moisture, which seemed to be strongly affected by stocking density at the different forest sites. The dense grassy ground vegetation at some of the sites further seems to play a key role in determining soil respiration rates and litter input. A detailed analysis and C-budgets along the elevation gradients will be presented at the conference.

A physically based analytical model of flood frequency curves

NASA Astrophysics Data System (ADS)

Basso, S.; Schirmer, M.; Botter, G.

2016-09-01

Predicting magnitude and frequency of floods is a key issue in hydrology, with implications in many fields ranging from river science and geomorphology to the insurance industry. In this paper, a novel physically based approach is proposed to estimate the recurrence intervals of seasonal flow maxima. The method links the extremal distribution of streamflows to the stochastic dynamics of daily discharge, providing an analytical expression of the seasonal flood frequency curve. The parameters involved in the formulation embody climate and landscape attributes of the contributing catchment and can be estimated from daily rainfall and streamflow data. Only one parameter, which is linked to the antecedent wetness condition in the watershed, needs to be calibrated on the observed maxima. The performance of the method is discussed through a set of applications in four rivers featuring heterogeneous daily flow regimes. The model provides reliable estimates of seasonal maximum flows in different climatic settings and is able to capture diverse shapes of flood frequency curves emerging in erratic and persistent flow regimes. The proposed method exploits experimental information on the full range of discharges experienced by rivers. As a consequence, model performances do not deteriorate when the magnitude of events with return times longer than the available sample size is estimated. The approach provides a framework for the prediction of floods based on short data series of rainfall and daily streamflows that may be especially valuable in data scarce regions of the world.

Large Eddy Simulation of Heat Entrainment Under Arctic Sea Ice

NASA Astrophysics Data System (ADS)

Ramudu, Eshwan; Gelderloos, Renske; Yang, Di; Meneveau, Charles; Gnanadesikan, Anand

2018-01-01

Arctic sea ice has declined rapidly in recent decades. The faster than projected retreat suggests that free-running large-scale climate models may not be accurately representing some key processes. The small-scale turbulent entrainment of heat from the mixed layer could be one such process. To better understand this mechanism, we model the Arctic Ocean's Canada Basin, which is characterized by a perennial anomalously warm Pacific Summer Water (PSW) layer residing at the base of the mixed layer and a summertime Near-Surface Temperature Maximum (NSTM) within the mixed layer trapping heat from solar radiation. We use large eddy simulation (LES) to investigate heat entrainment for different ice-drift velocities and different initial temperature profiles. The value of LES is that the resolved turbulent fluxes are greater than the subgrid-scale fluxes for most of our parameter space. The results show that the presence of the NSTM enhances heat entrainment from the mixed layer. Additionally there is no PSW heat entrained under the parameter space considered. We propose a scaling law for the ocean-to-ice heat flux which depends on the initial temperature anomaly in the NSTM layer and the ice-drift velocity. A case study of "The Great Arctic Cyclone of 2012" gives a turbulent heat flux from the mixed layer that is approximately 70% of the total ocean-to-ice heat flux estimated from the PIOMAS model often used for short-term predictions. Present results highlight the need for large-scale climate models to account for the NSTM layer.

Communicating climate change and health in the media.

PubMed

Depoux, Anneliese; Hémono, Mathieu; Puig-Malet, Sophie; Pédron, Romain; Flahault, Antoine

2017-01-01

The translation of science from research to real-world change is a central goal of public health. Communication has an essential role to play in provoking a response to climate change. It must first raise awareness, make people feel involved and ultimately motivate them to take action. The goal of this research is to understand how the information related to this issue is being addressed and disseminated to different audiences-public citizens, politicians and key climate change stakeholders. Initial results show that the scientific voice struggles to globally highlight this issue to a general audience and that messages that address the topic do not meet the challenges, going from a dramatic framing to a basic adaptation framing. Communication experts can help inform scientists and policy makers on how to best share information about climate change in an engaging and motivating way. This study gives an insight about the key role of the media and communications in addressing themes relating to climate change and transmitting information to the public in order to take action.

Integrating palaeoenvironmental and climate cyclicities - Optimizing the stratigraphic framework in the non-marine Lower Cretaceous

NASA Astrophysics Data System (ADS)

Sames, Benjamin

2015-04-01

Studies on changing paleoenvironments and climate cycles in non-marine archives of the Cretaceous greenhouse earth are hitherto rare, primarily a result of the lack of high-resolution stratigraphy and correlations to the marine record. On the other hand, recent refinements of the geological time scale have made major advances for the Cretaceous to yield a resolution comparable to that of younger Earth history. In the Cretaceous marine record is now possible to correlate and date short-term sea-level records and their possible relation to climate and/or tectonic events with appropriate resolution. Correlation in the non-marine realm ('continental' aquatic) has long been fraught with considerable problems and limitations, especially on supraregional (i.e., inter-basinal) to global scales, thus often hampering serious attempts at dating and chronological linking of events documented by the respective deposits - let alone appropriate correlation to marine successions. A new interdisciplinary project and multi-proxy study funded by the Austrian Science Fund (FWF) uses the Lower Cretaceous European record (English Wealden) as a test site for the integration of ostracod biostratigraphy and assemblage changes, and cyclostratigraphy (orbitally/climate driven cycles). Ostracods (microcrustaceans with a calcified shell) are the most useful biostratigraphical and palaeoenvironmental tool in Lower Cretaceous non-marine sequences. During the past two decades, research progress in late Mesozoic non-marine ostracods led to their extended applicability, whereas their wide dispersal ability has become a key conside-ration in their supraregional (inter-basinal to global) biostratigraphical utility. The integrative methodology applied in this project, targets the correlation of the ostracod faunal composition change with the variation of geochemical and sedimentological parameters through time and inferences on controlling (palaeoenvironmental) factors and their regulating mechanisms ('climate changes', orbital cycles?). The approach is multiple: 1) Biostratigraphy in the supraregional to global context, 2) cyclostratigraphy using ostracods, lithologic parameters and sediment geochemistry, 3) stable isotope geochemistry, and 4) magnetostratigraphy for chronological control. The methods used, evaluated and optimized within the scope of this project can then be efficiently applied on larger scopes and to larger datasets towards a better linking of marine and non-marine Cretaceous successions, enhancement of resolution in the considerable (particularly Lower) Cretaceous non-marine record, and integration of these data into the Cretaceous timescale.

Getting Decision Makers to the Table: Digestible Facts, a Few Good Friends and Sharing Recipes for Solutions to Climate Change Impacts.

NASA Astrophysics Data System (ADS)

Boudrias, M. A.; Estrada, M.; Gershunov, A.; Silva-Send, N. J.; Young, E.

2014-12-01

Decision makers and community leaders are key audiences to engage in our efforts to improve climate literacy. Climate Education Partners has been working with business leaders, elected officials, tribal leaders, and other Key Influentials in the San Diego Region to enhance the channels of communication outside traditional settings. Over the past year we have interviewed over 90 Key Influential San Diego leaders asking them about their knowledge of climate change and their personal and professional efforts to adapt to and/or mitigate the impacts of climate change. We also engaged them directly in the creation of an innovative educational resource called "San Diego, 2050 is Calling. How will we answer?" Results of the interviews indicate that 90% of these leaders are concerned about climate change, more than 50% are already doing something about the impacts, and the majority of them want more information, greater dialogue and examples of actions taken by other community leaders. We found that repeated engagement of leaders at the San Diego County Water Authority went from basic collaboration in our water tours, to greater participation of their top leaders in a water tour for top decision makers from the City of San Diego, finally culminating with full support of and participation in the 2050 report. The 2050 report represents an integrated approach blending local climate change science, social science education theory and presentation of a suite of solution-driven opportunities for local leaders. The report includes science infographics that illustrate rigorous scientific facts, statements from expert scientists and direct quotes from decision makers, and examples of successful climate change adaptation actions from companies, government groups and others. The video and photography sessions for the 2050 report led to many unexpected discussion among leaders with differing opinions on climate change, greater enthusiasm to participate in outreach activities with other leaders and an increased willingness to share their successes publicly. Climate Education Partners is finding that linking excellent local science with healthy community dialogue is resulting in San Diego leaders and their communities making more informed decisions on how to adapt to climate change now and for all future generations.

The ICARDA agro-climate tool

USDA-ARS?s Scientific Manuscript database

A Visual Basic agro-climate application by climatologists at the International Center for Agricultural Research in the Dry Areas and the U.S. Department of Agriculture is described here. The database from which the application derives climate information consists of weather generator parameters der...

Elevated temperature alters carbon cycling in a model microbial community

NASA Astrophysics Data System (ADS)

Mosier, A.; Li, Z.; Thomas, B. C.; Hettich, R. L.; Pan, C.; Banfield, J. F.

2013-12-01

Earth's climate is regulated by biogeochemical carbon exchanges between the land, oceans and atmosphere that are chiefly driven by microorganisms. Microbial communities are therefore indispensible to the study of carbon cycling and its impacts on the global climate system. In spite of the critical role of microbial communities in carbon cycling processes, microbial activity is currently minimally represented or altogether absent from most Earth System Models. Method development and hypothesis-driven experimentation on tractable model ecosystems of reduced complexity, as presented here, are essential for building molecularly resolved, benchmarked carbon-climate models. Here, we use chemoautotropic acid mine drainage biofilms as a model community to determine how elevated temperature, a key parameter of global climate change, regulates the flow of carbon through microbial-based ecosystems. This study represents the first community proteomics analysis using tandem mass tags (TMT), which enable accurate, precise, and reproducible quantification of proteins. We compare protein expression levels of biofilms growing over a narrow temperature range expected to occur with predicted climate changes. We show that elevated temperature leads to up-regulation of proteins involved in amino acid metabolism and protein modification, and down-regulation of proteins involved in growth and reproduction. Closely related bacterial genotypes differ in their response to temperature: Elevated temperature represses carbon fixation by two Leptospirillum genotypes, whereas carbon fixation is significantly up-regulated at higher temperature by a third closely related genotypic group. Leptospirillum group III bacteria are more susceptible to viral stress at elevated temperature, which may lead to greater carbon turnover in the microbial food web through the release of viral lysate. Overall, this proteogenomics approach revealed the effects of climate change on carbon cycling pathways and other microbial activities. When scaled to more complex ecosystems and integrated into Earth System Models, this approach could significantly improve predictions of global carbon-climate feedbacks. Experiments such as these are a critical first step designed at understanding climate change impacts in order to better predict ecosystem adaptations, assess the viability of mitigation strategies, and inform relevant policy decisions.

Assessing the impact of model and climate uncertainty in malaria simulations for the Kenyan Highlands.

NASA Astrophysics Data System (ADS)

Tompkins, A. M.; Thomson, M. C.

2017-12-01

Simulations of the impact of climate variations on a vector-bornedisease such as malaria are subject to a number of sources ofuncertainty. These include the model structure and parameter settingsin addition to errors in the climate data and the neglect of theirspatial heterogeneity, especially over complex terrain. We use aconstrained genetic algorithm to confront these two sources ofuncertainty for malaria transmission in the highlands of Kenya. Thetechnique calibrates the parameter settings of a process-based,mathematical model of malaria transmission to vary within theirassessed level of uncertainty and also allows the calibration of thedriving climate data. The simulations show that in highland settingsclose to the threshold for sustained transmission, the uncertainty inclimate is more important to address than the malaria modeluncertainty. Applications of the coupled climate-malaria modelling system are briefly presented.

Differential Response to Soil Salinity in Endangered Key Tree Cactus: Implications for Survival in a Changing Climate

PubMed Central

Goodman, Joie; Maschinski, Joyce; Hughes, Phillip; McAuliffe, Joe; Roncal, Julissa; Powell, Devon; Sternberg, Leonel O'reilly

2012-01-01

Understanding reasons for biodiversity loss is essential for developing conservation and management strategies and is becoming increasingly urgent with climate change. Growing at elevations <1.4 m in the Florida Keys, USA, the endangered Key tree cactus (Pilosocereus robinii) experienced 84 percent loss of total stems from 1994 to 2007. The most severe losses of 99 and 88 percent stems occurred in the largest populations in the Lower Keys, where nine storms with high wind velocities and storm surges, occurred during this period. In contrast, three populations had substantial stem proliferation. To evaluate possible mortality factors related to changes in climate or forest structure, we examined habitat variables: soil salinity, elevation, canopy cover, and habitat structure near 16 dying or dead and 18 living plants growing in the Lower Keys. Soil salinity and elevation were the preliminary factors that discriminated live and dead plants. Soil salinity was 1.5 times greater, but elevation was 12 cm higher near dead plants than near live plants. However, distribution-wide stem loss was not significantly related to salinity or elevation. Controlled salinity trials indicated that salt tolerance to levels above 40 mM NaCl was related to maternal origin. Salt sensitive plants from the Lower Keys had less stem growth, lower root:shoot ratios, lower potassium: sodium ratios and lower recovery rate, but higher δ 13C than a salt tolerant lineage of unknown origin. Unraveling the genetic structure of salt tolerant and salt sensitive lineages in the Florida Keys will require further genetic tests. Worldwide rare species restricted to fragmented, low-elevation island habitats, with little or no connection to higher ground will face challenges from climate change-related factors. These great conservation challenges will require traditional conservation actions and possibly managed relocation that must be informed by studies such as these. PMID:22403670

Differential response to soil salinity in endangered key tree cactus: implications for survival in a changing climate.

PubMed

Goodman, Joie; Maschinski, Joyce; Hughes, Phillip; McAuliffe, Joe; Roncal, Julissa; Powell, Devon; Sternberg, Leonel O'reilly

2012-01-01

Understanding reasons for biodiversity loss is essential for developing conservation and management strategies and is becoming increasingly urgent with climate change. Growing at elevations <1.4 m in the Florida Keys, USA, the endangered Key tree cactus (Pilosocereus robinii) experienced 84 percent loss of total stems from 1994 to 2007. The most severe losses of 99 and 88 percent stems occurred in the largest populations in the Lower Keys, where nine storms with high wind velocities and storm surges, occurred during this period. In contrast, three populations had substantial stem proliferation. To evaluate possible mortality factors related to changes in climate or forest structure, we examined habitat variables: soil salinity, elevation, canopy cover, and habitat structure near 16 dying or dead and 18 living plants growing in the Lower Keys. Soil salinity and elevation were the preliminary factors that discriminated live and dead plants. Soil salinity was 1.5 times greater, but elevation was 12 cm higher near dead plants than near live plants. However, distribution-wide stem loss was not significantly related to salinity or elevation. Controlled salinity trials indicated that salt tolerance to levels above 40 mM NaCl was related to maternal origin. Salt sensitive plants from the Lower Keys had less stem growth, lower root:shoot ratios, lower potassium: sodium ratios and lower recovery rate, but higher δ (13)C than a salt tolerant lineage of unknown origin. Unraveling the genetic structure of salt tolerant and salt sensitive lineages in the Florida Keys will require further genetic tests. Worldwide rare species restricted to fragmented, low-elevation island habitats, with little or no connection to higher ground will face challenges from climate change-related factors. These great conservation challenges will require traditional conservation actions and possibly managed relocation that must be informed by studies such as these.

Urban climate, weather and sustainability

NASA Astrophysics Data System (ADS)

Mills, Gerald

As concentrated areas of human activities, urban areas and urbanization are key drivers of global environmental change and pose a challenge to the achievement of sustainability. One of the key goals of sustainable development is to separate increases in non-renewable resource use (particularly fossil fuels) from economic growth. This is to be accomplished by modifying individual practices, encouraging technological innovation and redesigning systems of production and consumption. Settlements represent a scale at which significant advances on each of these can be made and where there is an existing management structure. However, urban areas currently consume a disproportionate share of the Earth's resources and urbanization has modified local climate and weather significantly, usually to the detriment of urban dwellers. There is now a lengthy history of urban climate study that links existing settlement form to climatic consequences yet, there is little evidence that climate information is incorporated into urban designs or that the climatic impact of different plans is considered. Consequently, opportunities for planning sustainable urban forms that are suitable to local climates and promote energy conservation and healthy atmospheres are not taken and much effort is later expended in `fixing' problems that emerge. This paper will outline the links between urban climate and sustainability, identify gaps in our urban climate knowledge and discuss the opportunities and barriers to the application of this knowledge to urban design and planning.

Preliminary Error Budget for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

NASA Technical Reports Server (NTRS)

Thome, Kurtis; Gubbels, Timothy; Barnes, Robert

2011-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) plans to observe climate change trends over decadal time scales to determine the accuracy of climate projections. The project relies on spaceborne earth observations of SI-traceable variables sensitive to key decadal change parameters. The mission includes a reflected solar instrument retrieving at-sensor reflectance over the 320 to 2300 nm spectral range with 500-m spatial resolution and 100-km swath. Reflectance is obtained from the ratio of measurements of the earth s surface to those while viewing the sun relying on a calibration approach that retrieves reflectance with uncertainties less than 0.3%. The calibration is predicated on heritage hardware, reduction of sensor complexity, adherence to detector-based calibration standards, and an ability to simulate in the laboratory on-orbit sources in both size and brightness to provide the basis of a transfer to orbit of the laboratory calibration including a link to absolute solar irradiance measurements. The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those in the IPCC Report. 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 Project will implement a spaceborne earth observation mission designed to provide rigorous SI traceable observations (i.e., radiance, reflectance, and refractivity) that are sensitive to a wide range of key decadal change variables, including: 1) Surface temperature and atmospheric temperature profile 2) Atmospheric water vapor profile 3) Far infrared water vapor greenhouse 4) Aerosol properties and anthropogenic aerosol direct radiative forcing 5) Total and spectral solar irradiance 6) Broadband reflected and emitted radiative fluxes 7) Cloud properties 8) Surface albedo There are two methods the CLARREO mission will rely on to achieve these critical decadal change benchmarks: direct and reference inter-calibration. A quantitative analysis of the strengths and weaknesses of the two methods has led to the recommended CLARREO mission approach. The project consists of two satellites launched into 90-degree, precessing orbits separated by 90 degrees. The instrument suite receiver on each spacecraft includes one emitted infrared spectrometer, two reflected solar spectrometers: dividing the spectrum from ultraviolet through near infrared, and one global navigation receiver for radio occultation. The measurements will be acquired for a period of three years minimum, with a five-year lifetime goal, enabling follow-on missions to extend the climate record over the decades needed to understand climate change. The current work concentrates on the reflected solar instrument giving an overview of its design and calibration approach. The calibration description includes the approach to achieving an SI-traceable system on orbit. The calibration overview is followed by a preliminary error budget based on techniques currently in place at the National Institute of Standards and Technology (NIST).

Climates Past, Present, and Yet-to-Come Shape Climate Change Vulnerabilities.

PubMed

Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R

2017-10-01

Climate change is altering life at multiple scales, from genes to ecosystems. Predicting the vulnerability of populations to climate change is crucial to mitigate negative impacts. We suggest that regional patterns of spatial and temporal climatic variation scaled to the traits of an organism can predict where and why populations are most vulnerable to climate change. Specifically, historical climatic variation affects the sensitivity and response capacity of populations to climate change by shaping traits and the genetic variation in those traits. Present and future climatic variation can affect both climate change exposure and population responses. We provide seven predictions for how climatic variation might affect the vulnerability of populations to climate change and suggest key directions for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Linking the Weather Generator with Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Farda, Ales; Skalak, Petr; Huth, Radan

2013-04-01

One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking the stochastic weather generator with the climate model output. The present contribution, in which the parametric daily surface weather generator (WG) M&Rfi is linked to the RCM output, follows two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate Regional Climate Model at 25 km resolution. The WG parameters are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series (including probability of wet day occurrence). (2) Presenting a methodology for linking the WG with RCM output. This methodology, which is based on merging information from observations and RCM, may be interpreted as a downscaling procedure, whose product is a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series in the first step, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with gridded RCM weather series and spatially scarcer observations. The quality of the weather series produced by the resultant gridded WG will be assessed in terms of selected climatic characteristics (focusing on characteristics related to variability and extremes of surface temperature and precipitation). Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

Interactions between land use, climate and hydropower in Scotland

NASA Astrophysics Data System (ADS)

Sample, James

2015-04-01

To promote the transition towards a low carbon economy, the Scottish Government has adopted ambitious energy targets, including generating all electricity from renewable sources by 2020. To achieve this, continued investment will be required across a range of sustainable technologies. Hydropower has a long history in Scotland and the present-day operational capacity of ~1.5 GW makes a substantial contribution to the national energy budget. In addition, there remains potential for ~500 MW of further development, mostly in the form of small to medium size run-of-river schemes. Climate change is expected to lead to an intensification of the global hydrological cycle, leading to changes in both the magnitude and seasonality of river flows. There may also be indirect effects, such as changing land use, enhanced evapotranspiration rates and an increased demand for irrigation, all of which could affect the water available for energy generation. Preliminary assessments of hydropower commonly use flow duration curves (FDCs) to estimate the power generation potential at proposed new sites. In this study, we use spatially distributed modelling to generate daily and monthly FDCs on a 1 km by 1 km grid across Scotland, using a variety of future land use and climate change scenarios. Parameter-related uncertainty in the model has been constrained using Bayesian Markov Chain Monte Carlo (MCMC) techniques to derive posterior probability distributions for key model parameters. Our results give an indication of the sensitivity and vulnerability of Scotland's run-of-river hydropower resources to possible changes in climate and land use. The effects are spatially variable and the range of uncertainty is sometimes large, but consistent patterns do emerge. For example, many locations are predicted to experience enhanced seasonality, with significantly lower power generation potential in the summer months and greater potential during the autumn and winter. Some sites may require infrastructural changes in order to continue operating at optimum efficiency. We discuss the implications and limitations of our results, and highlight design and adaptation options for maximising the resilience of hydropower installations under changing future flow patterns.

Effects of harvest and climate on population dynamics of northern bobwhites in south Florida

USGS Publications Warehouse

Rolland, V.; Hostetler, J.A.; Hines, T.C.; Johnson, F.A.; Percival, H.F.; Oli, M.K.

2011-01-01

Context Hunting-related (hereafter harvest) mortality is assumed to be compensatory in many exploited species. However, when harvest mortality is additive, hunting can lead to population declines, especially on public land where hunting pressure can be intense. Recent studies indicate that excessive hunting may have contributed to the decline of a northern bobwhite (Colinus virginianus) population in south Florida. Aims This study aimed to estimate population growth rates to determine potential and actual contribution of vital rates to annual changes in population growth rates, and to evaluate the role of harvest and climatic variables on bobwhite population decline. Methods We used demographic parameters estimated from a six-year study to parameterise population matrix models and conduct prospective and retrospective perturbation analyses. Key results The stochastic population growth rate (?? S=0.144) was proportionally more sensitive to adult winter survival and survival of fledglings, nests and broods from first nesting attempts; the same variables were primarily responsible for annual changes in population growth rate. Demographic parameters associated with second nesting attempts made virtually no contribution to population growth rate. All harvest scenarios consistently revealed a substantial impact of harvest on bobwhite population dynamics. If the lowest harvest level recorded in the study period (i.e. 0.08 birds harvested per day per km2 in 2008) was applied, S would increase by 32.1%. Winter temperatures and precipitation negatively affected winter survival, and precipitation acted synergistically with harvest in affecting winter survival. Conclusions Our results suggest that reduction in winter survival due to overharvest has been an important cause of the decline in our study population, but that climatic factors might have also played a role. Thus, for management actions to be effective, assessing the contribution of primary (e.g. harvesting) but also secondary factors (e.g. climate) to population decline may be necessary. Implications Reducing hunting pressure would be necessary for the recovery of the bobwhite population at our study site. In addition, an adaptive harvest management strategy that considers weather conditions in setting harvest quota would help reverse the population decline further. ?? 2011 CSIRO.

Key ecological responses to nitrogen are altered by climate change

EPA Science Inventory

Here we review the effects of nitrogen and climate (e.g. temperature and precipitation) on four aspects of ecosystem structure and function including hydrologic-coupled nitrogen cycling, carbon cycling, acidification and biodiversity.

Climate services in the tourism sector - examples and market research

NASA Astrophysics Data System (ADS)

Damm, Andrea; Köberl, Judith; Prettenthaler, Franz; Kortschak, Dominik; Hofer, Marianne; Winkler, Claudia

2017-04-01

Tourism is one of the most weather-sensitive sectors. Hence, dealing with weather and climate risks is an important part of operational risk management. WEDDA® (WEather Driven Demand Analysis), developed by Joanneum Research, represents a comprehensive and flexible toolbox for managing weather and climate risks. Modelling the demand for products or services of a particular economic sector or company and its weather and climate sensitivity usually forms the starting and central point of WEDDA®. Coupling the calibrated demand models to either long-term climate scenarios or short-term weather forecasts enables the use of WEDDA® for the following areas of application: (i) implementing short-term forecasting systems for the prediction of the considered indicator; (ii) quantifying the weather risk of a particular economic sector or company using parameters from finance (e.g. Value-at-Risk); (iii) assessing the potential impacts of changing climatic conditions on a particular economic sector or company. WEDDA® for short-term forecasts on the demand for products or services is currently used by various tourism businesses, such as open-air swimming pools, ski areas, and restaurants. It supports tourism and recreation facilities to better cope with (increasing) weather variability by optimizing the disposability of staff, resources and merchandise according to expected demand. Since coping with increasing weather variability forms one of the challenges with respect to climate change, WEDDA® may become an important component within a whole pool of weather and climate services designed to support tourism and recreation facilities to adapt to climate change. Climate change impact assessments at European scale, as conducted in the EU-FP7 project IMPACT2C, provide basic information of climate change impacts on tourism demand not only for individual tourism businesses, but also for regional and national tourism planners and policy makers interested in benchmarks for the vulnerability of their tourism destination. In this project we analysed the impacts of +2 °C global warming on winter tourism demand in ski tourism related regions in Europe. In order to achieve the climate targets, tailored climate information services - for individual businesses as well as at the regional and national level - play an important role. The current market, however, is still in the early stages. In the ongoing H2020 projects EU-MACS (www.eu-macs.eu) and MARCO (www.marco-h2020.eu) (Nov 2016 - Oct 2018) Joanneum Research explores the climate services market in the tourism sector. The current use of climate services is reviewed in detail and in an interactive process key market barriers and enablers will be identified in close collaboration with stakeholders from the tourism industry. The analysis and co-development of new climate services concepts for the tourism sector aims to reduce the gaps between climate services supply and demand.

Biofuel blending reduces particle emissions from aircraft engines at cruise conditions

NASA Astrophysics Data System (ADS)

Moore, Richard H.; Thornhill, Kenneth L.; Weinzierl, Bernadett; Sauer, Daniel; D'Ascoli, Eugenio; Kim, Jin; Lichtenstern, Michael; Scheibe, Monika; Beaton, Brian; Beyersdorf, Andreas J.; Barrick, John; Bulzan, Dan; Corr, Chelsea A.; Crosbie, Ewan; Jurkat, Tina; Martin, Robert; Riddick, Dean; Shook, Michael; Slover, Gregory; Voigt, Christiane; White, Robert; Winstead, Edward; Yasky, Richard; Ziemba, Luke D.; Brown, Anthony; Schlager, Hans; Anderson, Bruce E.

2017-03-01

Aviation-related aerosol emissions contribute to the formation of contrail cirrus clouds that can alter upper tropospheric radiation and water budgets, and therefore climate. The magnitude of air-traffic-related aerosol-cloud interactions and the ways in which these interactions might change in the future remain uncertain. Modelling studies of the present and future effects of aviation on climate require detailed information about the number of aerosol particles emitted per kilogram of fuel burned and the microphysical properties of those aerosols that are relevant for cloud formation. However, previous observational data at cruise altitudes are sparse for engines burning conventional fuels, and no data have previously been reported for biofuel use in-flight. Here we report observations from research aircraft that sampled the exhaust of engines onboard a NASA DC-8 aircraft as they burned conventional Jet A fuel and a 50:50 (by volume) blend of Jet A fuel and a biofuel derived from Camelina oil. We show that, compared to using conventional fuels, biofuel blending reduces particle number and mass emissions immediately behind the aircraft by 50 to 70 per cent. Our observations quantify the impact of biofuel blending on aerosol emissions at cruise conditions and provide key microphysical parameters, which will be useful to assess the potential of biofuel use in aviation as a viable strategy to mitigate climate change.

Cloud Microphysical Properties in Mesoscale Convective Systems: An Intercomparison of Three Tropical Locations

NASA Astrophysics Data System (ADS)

Fontaine, Emmanuel; Leroy, Delphine; Schwarzenboeck, Alfons; Coutris, Pierre; Delanoë, Julien; Protat, Alain; Dezitter, Fabien; Grandin, Alice; Strapp, John W.; Lilie, Lyle E.

2017-04-01

Mesoscale Convective Systems are complex cloud systems which are primarily the result of specific synoptic conditions associated with mesoscale instabilities leading to the development of cumulonimbus type clouds (Houze, 2004). These systems can last several hours and can affect human societies in various ways. In general, weather and climate models use simplistic schemes to describe ice hydrometeors' properties. However, MCS are complex cloud systems where the dynamic, radiative and precipitation processes depend on spatiotemporal location in the MCS (Houze, 2004). As a consequence, hydrometeor growth processes in MCS vary in space and time, thereby impacting shape and concentration of ice crystals and finally CWC. As a consequence, differences in the representation of ice properties in models (Li et al., 2007, 2005) lead to significant disagreements in the quantification of ice cloud effects on climate evolution (Intergovernmental Panel on Climate Change Fourth Assessment Report). An accurate estimation of the spatiotemporal CWC distribution is therefore a key parameter for evaluating and improving numerical weather prediction (Stephens et al., 2002). The main purpose of this study is to show ice microphysical properties of MCS observed in three different locations in the tropical atmosphere: West-African continent, Indian Ocean, and Northern Australia. An intercomparison study is performed in order to quantify how similar or different are the ice hydrometeors' properties in these three regions related to radar reflectivity factors and temperatures observed in respective MCS.

Biofuel blending reduces particle emissions from aircraft engines at cruise conditions.

PubMed

Moore, Richard H; Thornhill, Kenneth L; Weinzierl, Bernadett; Sauer, Daniel; D'Ascoli, Eugenio; Kim, Jin; Lichtenstern, Michael; Scheibe, Monika; Beaton, Brian; Beyersdorf, Andreas J; Barrick, John; Bulzan, Dan; Corr, Chelsea A; Crosbie, Ewan; Jurkat, Tina; Martin, Robert; Riddick, Dean; Shook, Michael; Slover, Gregory; Voigt, Christiane; White, Robert; Winstead, Edward; Yasky, Richard; Ziemba, Luke D; Brown, Anthony; Schlager, Hans; Anderson, Bruce E

2017-03-15

Aviation-related aerosol emissions contribute to the formation of contrail cirrus clouds that can alter upper tropospheric radiation and water budgets, and therefore climate. The magnitude of air-traffic-related aerosol-cloud interactions and the ways in which these interactions might change in the future remain uncertain. Modelling studies of the present and future effects of aviation on climate require detailed information about the number of aerosol particles emitted per kilogram of fuel burned and the microphysical properties of those aerosols that are relevant for cloud formation. However, previous observational data at cruise altitudes are sparse for engines burning conventional fuels, and no data have previously been reported for biofuel use in-flight. Here we report observations from research aircraft that sampled the exhaust of engines onboard a NASA DC-8 aircraft as they burned conventional Jet A fuel and a 50:50 (by volume) blend of Jet A fuel and a biofuel derived from Camelina oil. We show that, compared to using conventional fuels, biofuel blending reduces particle number and mass emissions immediately behind the aircraft by 50 to 70 per cent. Our observations quantify the impact of biofuel blending on aerosol emissions at cruise conditions and provide key microphysical parameters, which will be useful to assess the potential of biofuel use in aviation as a viable strategy to mitigate climate change.

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.

Full uncertainty quantification of N2O and NO emissions using the biogeochemical model LandscapeDNDC on site and regional scale

NASA Astrophysics Data System (ADS)

Haas, Edwin; Santabarbara, Ignacio; Kiese, Ralf; Butterbach-Bahl, Klaus

2017-04-01

Numerical simulation models are increasingly used to estimate greenhouse gas emissions at site to regional / national scale and are outlined as the most advanced methodology (Tier 3) in the framework of UNFCCC reporting. Process-based models incorporate the major processes of the carbon and nitrogen cycle of terrestrial ecosystems and are thus thought to be widely applicable at various conditions and spatial scales. Process based modelling requires high spatial resolution input data on soil properties, climate drivers and management information. The acceptance of model based inventory calculations depends on the assessment of the inventory's uncertainty (model, input data and parameter induced uncertainties). In this study we fully quantify the uncertainty in modelling soil N2O and NO emissions from arable, grassland and forest soils using the biogeochemical model LandscapeDNDC. We address model induced uncertainty (MU) by contrasting two different soil biogeochemistry modules within LandscapeDNDC. The parameter induced uncertainty (PU) was assessed by using joint parameter distributions for key parameters describing microbial C and N turnover processes as obtained by different Bayesian calibration studies for each model configuration. Input data induced uncertainty (DU) was addressed by Bayesian calibration of soil properties, climate drivers and agricultural management practices data. For the MU, DU and PU we performed several hundred simulations each to contribute to the individual uncertainty assessment. For the overall uncertainty quantification we assessed the model prediction probability, followed by sampled sets of input datasets and parameter distributions. Statistical analysis of the simulation results have been used to quantify the overall full uncertainty of the modelling approach. With this study we can contrast the variation in model results to the different sources of uncertainties for each ecosystem. Further we have been able to perform a fully uncertainty analysis for modelling N2O and NO emissions from arable, grassland and forest soils necessary for the comprehensibility of modelling results. We have applied the methodology to a regional inventory to assess the overall modelling uncertainty for a regional N2O and NO emissions inventory for the state of Saxony, Germany.

Uncertainty quantification of Antarctic contribution to sea-level rise using the fast Elementary Thermomechanical Ice Sheet (f.ETISh) model

NASA Astrophysics Data System (ADS)

Bulthuis, Kevin; Arnst, Maarten; Pattyn, Frank; Favier, Lionel

2017-04-01

Uncertainties in sea-level rise projections are mostly due to uncertainties in Antarctic ice-sheet predictions (IPCC AR5 report, 2013), because key parameters related to the current state of the Antarctic ice sheet (e.g. sub-ice-shelf melting) and future climate forcing are poorly constrained. Here, we propose to improve the predictions of Antarctic ice-sheet behaviour using new uncertainty quantification methods. As opposed to ensemble modelling (Bindschadler et al., 2013) which provides a rather limited view on input and output dispersion, new stochastic methods (Le Maître and Knio, 2010) can provide deeper insight into the impact of uncertainties on complex system behaviour. Such stochastic methods usually begin with deducing a probabilistic description of input parameter uncertainties from the available data. Then, the impact of these input parameter uncertainties on output quantities is assessed by estimating the probability distribution of the outputs by means of uncertainty propagation methods such as Monte Carlo methods or stochastic expansion methods. The use of such uncertainty propagation methods in glaciology may be computationally costly because of the high computational complexity of ice-sheet models. This challenge emphasises the importance of developing reliable and computationally efficient ice-sheet models such as the f.ETISh ice-sheet model (Pattyn, 2015), a new fast thermomechanical coupled ice sheet/ice shelf model capable of handling complex and critical processes such as the marine ice-sheet instability mechanism. Here, we apply these methods to investigate the role of uncertainties in sub-ice-shelf melting, calving rates and climate projections in assessing Antarctic contribution to sea-level rise for the next centuries using the f.ETISh model. We detail the methods and show results that provide nominal values and uncertainty bounds for future sea-level rise as a reflection of the impact of the input parameter uncertainties under consideration, as well as a ranking of the input parameter uncertainties in the order of the significance of their contribution to uncertainty in future sea-level rise. In addition, we discuss how limitations posed by the available information (poorly constrained data) pose challenges that motivate our current research.

Using dry and wet year hydroclimatic extremes to guide future hydrologic projections

NASA Astrophysics Data System (ADS)

Oni, Stephen; Futter, Martyn; Ledesma, Jose; Teutschbein, Claudia; Buttle, Jim; Laudon, Hjalmar

2016-07-01

There are growing numbers of studies on climate change impacts on forest hydrology, but limited attempts have been made to use current hydroclimatic variabilities to constrain projections of future climatic conditions. Here we used historical wet and dry years as a proxy for expected future extreme conditions in a boreal catchment. We showed that runoff could be underestimated by at least 35 % when dry year parameterizations were used for wet year conditions. Uncertainty analysis showed that behavioural parameter sets from wet and dry years separated mainly on precipitation-related parameters and to a lesser extent on parameters related to landscape processes, while uncertainties inherent in climate models (as opposed to differences in calibration or performance metrics) appeared to drive the overall uncertainty in runoff projections under dry and wet hydroclimatic conditions. Hydrologic model calibration for climate impact studies could be based on years that closely approximate anticipated conditions to better constrain uncertainty in projecting extreme conditions in boreal and temperate regions.

Parameter Uncertainty on AGCM-simulated Tropical Cyclones

NASA Astrophysics Data System (ADS)

He, F.

2015-12-01

This work studies the parameter uncertainty on tropical cyclone (TC) simulations in Atmospheric General Circulation Models (AGCMs) using the Reed-Jablonowski TC test case, which is illustrated in Community Atmosphere Model (CAM). It examines the impact from 24 parameters across the physical parameterization schemes that represent the convection, turbulence, precipitation and cloud processes in AGCMs. The one-at-a-time (OAT) sensitivity analysis method first quantifies their relative importance on TC simulations and identifies the key parameters to the six different TC characteristics: intensity, precipitation, longwave cloud radiative forcing (LWCF), shortwave cloud radiative forcing (SWCF), cloud liquid water path (LWP) and ice water path (IWP). Then, 8 physical parameters are chosen and perturbed using the Latin-Hypercube Sampling (LHS) method. The comparison between OAT ensemble run and LHS ensemble run shows that the simulated TC intensity is mainly affected by the parcel fractional mass entrainment rate in Zhang-McFarlane (ZM) deep convection scheme. The nonlinear interactive effect among different physical parameters is negligible on simulated TC intensity. In contrast, this nonlinear interactive effect plays a significant role in other simulated tropical cyclone characteristics (precipitation, LWCF, SWCF, LWP and IWP) and greatly enlarge their simulated uncertainties. The statistical emulator Extended Multivariate Adaptive Regression Splines (EMARS) is applied to characterize the response functions for nonlinear effect. Last, we find that the intensity uncertainty caused by physical parameters is in a degree comparable to uncertainty caused by model structure (e.g. grid) and initial conditions (e.g. sea surface temperature, atmospheric moisture). These findings suggest the importance of using the perturbed physics ensemble (PPE) method to revisit tropical cyclone prediction under climate change scenario.

Relative importance of local- and large-scale drivers of alpine soil microarthropod communities.

PubMed

Mitchell, Ruth J; Urpeth, Hannah M; Britton, Andrea J; Black, Helaina; Taylor, Astrid R

2016-11-01

Nitrogen (N) deposition and climate are acknowledged drivers of change in biodiversity and ecosystem function at large scales. However, at a local scale, their impact on functions and community structure of organisms is filtered by drivers like habitat quality and food quality/availability. This study assesses the relative impact of large-scale factors, N deposition and climate (rainfall and temperature), versus local-scale factors of habitat quality and food quality/availability on soil fauna communities at 15 alpine moss-sedge heaths along an N deposition gradient in the UK. Habitat quality and food quality/availability were the primary drivers of microarthropod communities. No direct impacts of N deposition on the microarthropod community were observed, but induced changes in habitat quality (decline in moss cover and depth) and food quality (decreased vegetation C:N) associated with increased N deposition strongly suggest an indirect impact of N. Habitat quality and climate explained variation in the composition of the Oribatida, Mesostigmata, and Collembola communities, while only habitat quality significantly impacted the Prostigmata. Food quality and prey availability were important in explaining the composition of the oribatid and mesostigmatid mite communities, respectively. This study shows that, in alpine habitats, soil microarthropod community structure responds most strongly to local-scale variation in habitat quality and food availability rather than large-scale variation in climate and pollution. However, given the strong links between N deposition and the key habitat quality parameters, we conclude that N deposition indirectly drives changes in the soil microarthropod community, suggesting a mechanism by which large-scale drivers indirectly impacts these functionally important groups.

Predicting forest attributes from climate data using a recursive partitioning and regression tree algorithm

Treesearch

Greg C. Liknes; Christopher W. Woodall; Charles H. Perry

2009-01-01

Climate information frequently is included in geospatial modeling efforts to improve the predictive capability of other data sources. The selection of an appropriate climate data source requires consideration given the number of choices available. With regard to climate data, there are a variety of parameters (e.g., temperature, humidity, precipitation), time intervals...

Effects of climate on growth traits of river red gum are determined by respiration parameters

Treesearch

Richard S. Criddle; Thimmappa S. Anekonda; Sharon Tong; John N. Church; F. Thomas Ledig; Lee D. Hansen

2000-01-01

Temperature is the major uncontrollable climate variable in plantation forestry. Matching plants to climate is essential for optimizing growth. Matching is usually done with field trials because of the lack of a predictive relation between laboratory measurements of physiological responses and climatic factors affecting growth. This paper evaluates the potential of...

An Investigation of the Radiative Effects and Climate Feedbacks of Sea Ice Sources of Sea Salt Aerosol

NASA Astrophysics Data System (ADS)

Horowitz, H. M.; Alexander, B.; Bitz, C. M.; Jaegle, L.; Burrows, S. M.

2017-12-01

In polar regions, sea ice is a major source of sea salt aerosol through lofting of saline frost flowers or blowing saline snow from the sea ice surface. Under continued climate warming, an ice-free Arctic in summer with only first-year, more saline sea ice in winter is likely. Previous work has focused on climate impacts in summer from increasing open ocean sea salt aerosol emissions following complete sea ice loss in the Arctic, with conflicting results suggesting no net radiative effect or a negative climate feedback resulting from a strong first aerosol indirect effect. However, the radiative forcing from changes to the sea ice sources of sea salt aerosol in a future, warmer climate has not previously been explored. Understanding how sea ice loss affects the Arctic climate system requires investigating both open-ocean and sea ice sources of sea-salt aerosol and their potential interactions. Here, we implement a blowing snow source of sea salt aerosol into the Community Earth System Model (CESM) dynamically coupled to the latest version of the Los Alamos sea ice model (CICE5). Snow salinity is a key parameter affecting blowing snow sea salt emissions and previous work has assumed constant regional snow salinity over sea ice. We develop a parameterization for dynamic snow salinity in the sea ice model and examine how its spatial and temporal variability impacts the production of sea salt from blowing snow. We evaluate and constrain the snow salinity parameterization using available observations. Present-day coupled CESM-CICE5 simulations of sea salt aerosol concentrations including sea ice sources are evaluated against in situ and satellite (CALIOP) observations in polar regions. We then quantify the present-day radiative forcing from the addition of blowing snow sea salt aerosol with respect to aerosol-radiation and aerosol-cloud interactions. The relative contributions of sea ice vs. open ocean sources of sea salt aerosol to radiative forcing in polar regions is discussed.

Uncertainties in Past and Future Global Water Availability

NASA Astrophysics Data System (ADS)

Sheffield, J.; Kam, J.

2014-12-01

Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.

Assessment of climate change effects on mountain ecosystems through a cross-site analysis in the Alps and Apennines.

PubMed

Rogora, M; Frate, L; Carranza, M L; Freppaz, M; Stanisci, A; Bertani, I; Bottarin, R; Brambilla, A; Canullo, R; Carbognani, M; Cerrato, C; Chelli, S; Cremonese, E; Cutini, M; Di Musciano, M; Erschbamer, B; Godone, D; Iocchi, M; Isabellon, M; Magnani, A; Mazzola, L; Morra di Cella, U; Pauli, H; Petey, M; Petriccione, B; Porro, F; Psenner, R; Rossetti, G; Scotti, A; Sommaruga, R; Tappeiner, U; Theurillat, J-P; Tomaselli, M; Viglietti, D; Viterbi, R; Vittoz, P; Winkler, M; Matteucci, G

2018-05-15

Mountain ecosystems are sensitive and reliable indicators of climate change. Long-term studies may be extremely useful in assessing the responses of high-elevation ecosystems to climate change and other anthropogenic drivers from a broad ecological perspective. Mountain research sites within the LTER (Long-Term Ecological Research) network are representative of various types of ecosystems and span a wide bioclimatic and elevational range. Here, we present a synthesis and a review of the main results from ecological studies in mountain ecosystems at 20 LTER sites in Italy, Switzerland and Austria covering in most cases more than two decades of observations. We analyzed a set of key climate parameters, such as temperature and snow cover duration, in relation to vascular plant species composition, plant traits, abundance patterns, pedoclimate, nutrient dynamics in soils and water, phenology and composition of freshwater biota. The overall results highlight the rapid response of mountain ecosystems to climate change, with site-specific characteristics and rates. As temperatures increased, vegetation cover in alpine and subalpine summits increased as well. Years with limited snow cover duration caused an increase in soil temperature and microbial biomass during the growing season. Effects on freshwater ecosystems were also observed, in terms of increases in solutes, decreases in nitrates and changes in plankton phenology and benthos communities. This work highlights the importance of comparing and integrating long-term ecological data collected in different ecosystems for a more comprehensive overview of the ecological effects of climate change. Nevertheless, there is a need for (i) adopting co-located monitoring site networks to improve our ability to obtain sound results from cross-site analysis, (ii) carrying out further studies, in particular short-term analyses with fine spatial and temporal resolutions to improve our understanding of responses to extreme events, and (iii) increasing comparability and standardizing protocols across networks to distinguish local patterns from global patterns. Copyright © 2017 Elsevier B.V. All rights reserved.

Effective Social Media Practices for Communicating Climate Change Science to Community Leaders

NASA Astrophysics Data System (ADS)

Estrada, M.; DeBenedict, C.; Bruce, L.

2016-12-01

Climate Education Partners (CEP) uses an action research approach to increase climate knowledge and informed decision-making among key influential (KI) leaders in San Diego county. Social media has been one method for disseminating knowledge. During CEP's project years, social media use has proliferated. To capitalize on this trend, CEP iteratively developed a strategic method to engage KIs. First, as with all climate education, CEP identified the audience. Three primary Facebook and Twitter audiences were CEP's internal team, local KIs, and strategic partner organizations. Second, post contents were chosen based on interest to CEP key audiences and followed CEP's communications message triangle, which incorporates the Tripartite Integration Model of Social Influence (TIMSI). This message triangle focuses on San Diegan's valued quality of life, future challenges we face due to the changing climate, and ways in which we are working together to protect our quality of life for future generations. Third, an editorial calendar was created to carefully time posts, which capitalize on when target audiences were using social media most and to maintain consistency. The results of these three actions were significant. Results attained utilizing Facebook and Twitter data, which tracks post reach, total followers/likes, and engagement (likes, comments, mentions, shares). For example we found that specifically mentioning KIs resulted in more re-tweets and resulted in reaching a broader audience. Overall, data shows that CEP's reach to audiences of like-minded individuals and organizations now extends beyond CEP's original local network and reached more than 20,000 accounts on Twitter this year (compared with 460 on Twitter the year before). In summary, through posting and participating in the online conversation strategically, CEP disseminated key educational climate resources and relevant climate change news to educate and engage target audience and amplify our work.

Decision-Makers As Messengers Of Climate Change Impacts And Ambassadors For Their Communities.

NASA Astrophysics Data System (ADS)

Boudrias, M. A.; DeBenedict, C.; Bruce, L.; Estrada, M.; Hedge, N.; Silva-Send, N. J.

2016-12-01

Over the past several years there have been many coordinated efforts to improve climate change literacy of diverse audiences. The challenge has been to balance science content with audience-specific messaging with a goal to reach solutions and build community resilience. In the San Diego Region, Climate Education Partners (CEP) has been working with business leaders, elected officials, tribal leaders, and other community leaders to develop a suite of programs and activities to enhance the channels of communication outside traditional settings. CEP has employed a multidisciplinary approach that integrates climate science, social and learning sciences and effective communication strategies to create innovative resources and new approaches to climate change communication in order to engage audiences more effectively. We have interviewed over 140 key San Diego leaders and invited them to serve as ambassadors to the project by engaging them directly in the creation of a variety of innovative educational resources as well as serving as spokespersons for outreach activities. Our program has evolved from having only scientists, educators and community practitioners serve as presenters to strategically and deliberately engaging a mix of scientists, educators and decision makers as the conveyers of key messages. Our protocol for events includes preparing all speakers in advance, researching our audience, creating a script, immediate debriefs of each activity and a qualitative and quantitative assessment of each event. Two examples of this integrated approach will show how to engage decision-makers more deeply: (1) coastal flooding tour as a place-based activity and (2) impact videos that blend climate science, local personal stories and key messages from decision makers themselves. For climate change communication to be successful in the future, we will need creative and coordinated approaches.

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.

Constructing optimal ensemble projections for predictive environmental modelling in Northern Eurasia

NASA Astrophysics Data System (ADS)

Anisimov, Oleg; Kokorev, Vasily

2013-04-01

Large uncertainties in climate impact modelling are associated with the forcing climate data. This study is targeted at the evaluation of the quality of GCM-based climatic projections in the specific context of predictive environmental modelling in Northern Eurasia. To accomplish this task, we used the output from 36 CMIP5 GCMs from the IPCC AR-5 data base for the control period 1975-2005 and calculated several climatic characteristics and indexes that are most often used in the impact models, i.e. the summer warmth index, duration of the vegetation growth period, precipitation sums, dryness index, thawing degree-day sums, and the annual temperature amplitude. We used data from 744 weather stations in Russia and neighbouring countries to analyze the spatial patterns of modern climatic change and to delineate 17 large regions with coherent temperature changes in the past few decades. GSM results and observational data were averaged over the coherent regions and compared with each other. Ultimately, we evaluated the skills of individual models, ranked them in the context of regional impact modelling and identified top-end GCMs that "better than average" reproduce modern regional changes of the selected meteorological parameters and climatic indexes. Selected top-end GCMs were used to compose several ensembles, each combining results from the different number of models. Ensembles were ranked using the same algorithm and outliers eliminated. We then used data from top-end ensembles for the 2000-2100 period to construct the climatic projections that are likely to be "better than average" in predicting climatic parameters that govern the state of environment in Northern Eurasia. The ultimate conclusions of our study are the following. • High-end GCMs that demonstrate excellent skills in conventional atmospheric model intercomparison experiments are not necessarily the best in replicating climatic characteristics that govern the state of environment in Northern Eurasia, and independent model evaluation on regional level is necessary to identify "better than average" GCMs. • Each of the ensembles combining results from several "better than average" models replicate selected meteorological parameters and climatic indexes better than any single GCM. The ensemble skills are parameter-specific and depend on models it consists of. The best results are not necessarily those based on the ensemble comprised by all "better than average" models. • Comprehensive evaluation of climatic scenarios using specific criteria narrows the range of uncertainties in environmental projections.

Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

NASA Astrophysics Data System (ADS)

Abdolghafoorian, A.; Farhadi, L.

2017-12-01

Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and water (SHAW) model. In addition, the feasibility of extending this algorithm to use remote sensing observations that have low temporal resolution is examined by assimilating the limited number of land surface moisture and temperature observations.

Authoritative School Climate and Suspension Rates in Middle Schools: Implications for Reducing the Racial Disparity in School Discipline

ERIC Educational Resources Information Center

Heilbrun, Anna; Cornell, Dewey; Konold, Timothy

2018-01-01

The overuse of school suspensions has been linked to a host of negative outcomes, including racial disparities in discipline. School climate initiatives have shown promise in reducing these disparities. The present study used the Authoritative School Climate Survey--which measures disciplinary structure and student support as key measures of…

A Climate for Self-Efficacy: The Relationship between School Climate and Teacher Efficacy for Inclusion

ERIC Educational Resources Information Center

Hosford, Susan; O'Sullivan, Siobhán

2016-01-01

Teacher efficacy represents a key construct in exploring successful implementation of inclusive policy. Teachers' impression of school climate is shown to relate to teacher efficacy; however, few studies pay due deference to its context/specific conceptualisation, with a particular lacuna in research noted in an Irish mainstream primary school…

Long-term trends in climate and hydrology in an agricultural headwater watershed of central Pennsylvania, USA

USDA-ARS?s Scientific Manuscript database

Climate change has emerged as a key issue facing agriculture and water resources in the US. Long-term (1968-2012) temperature, precipitation and streamflow data from a small (7.3 km2) watershed in east-central Pennsylvania was used to examine climatic and hydrologic trends in the context of recent c...

Global change in forests: responses of species, communities, and biomes

Treesearch

Andrew J. Hansen; Ronald P. Neilson; Virginia H. Dale; Curtis H. Flather; Louis R. Iverson; David J. Currie; Sarah Shafer; Rosamonde Cook; Partick J. Bartlein

2001-01-01

This article serves as a primer on forest biodiversity as a key component of global change. We first synthesize current knowledge of interactions among climate, land use, and biodiversity. We then summarize the results of new analyses on the potential effects of human-induced climate change on forest biodiversity. Our models project how possible future climates may...

Climate change may restrict dryland forest regeneration in the 21st century

Treesearch

M. D. Petrie; J. B. Bradford; R. M. Hubbard; W. K. Lauenroth; C. M. Andrews; D. R. Schlaepfer

2017-01-01

The persistence and geographic expansion of dryland forests in the 21st century will be influenced by how climate change supports the demographic processes associated with tree regeneration. Yet, the way that climate change may alter regeneration is unclear. We developed a quantitative framework that estimates forest regeneration potential (RP) as a function of key...

Educational Faculty Perceptions of the Learning Climate in a Juvenile Justice Residential Facility

ERIC Educational Resources Information Center

Cox, Carolyn; Visker, Joseph; Hartman, Ashley

2011-01-01

The majority of educational faculty from a juvenile justice residential detention facility in rural Northeast Missouri who participated in a learning climate survey of their school seemed to agree that the environment for staff and students was generally physically safe and emotionally supportive; key factors for a positive learning climate. By…

Meteorology and Climate Inspire Secondary Science Students

ERIC Educational Resources Information Center

Charlton-Perez, Andrew; Dacre, Helen; Maskell, Kathy; Reynolds, Ross; South, Rachel; Wood, Curtis

2010-01-01

As part of its National Science and Engineering Week activities in 2009 and 2010, the University of Reading organised two open days for 60 local key stage 4 pupils. The theme of both open days was "How do we predict weather and climate?" Making use of the students' familiarity with weather and climate, several concepts of relevance to secondary…

Teaching in the Age of Humans: Helping Students Think about Climate Change

ERIC Educational Resources Information Center

Smith, Grinell

2017-01-01

To convey the magnitude and rapidity of current climate change and the severity of predictions for the next century, I present essential climate science information using four key sets of data and contextualize that information with personal anecdotes. I then consider the reasons for the large gap between the scientific consensus about…

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...

Balancing the Tensions and Meeting the Conceptual Challenges of Education for Sustainable Development and Climate Change

ERIC Educational Resources Information Center

Blum, Nicole; Nazir, Joanne; Breiting, Soren; Goh, Kim Chuan; Pedretti, Erminia

2013-01-01

This paper addresses one of the key challenges for work on education, sustainable development and climate change: the overall conceptualisation of central ideas such as Environmental Education (EE), Education for Sustainable Development (ESD) and Climate Change Education (CCE). What do these concepts mean in diverse contexts and amongst diverse…