A vulnerability tool for adapting water and aquatic resources to climate change and extremes on the Shoshone National Forest, Wyoming

NASA Astrophysics Data System (ADS)

Rice, J.; Joyce, L. A.; Armel, B.; Bevenger, G.; Zubic, R.

2011-12-01

Climate change introduces a significant challenge for land managers and decision makers managing the natural resources that provide many benefits from forests. These benefits include water for urban and agricultural uses, wildlife habitat, erosion and climate control, aquifer recharge, stream flows regulation, water temperature regulation, and cultural services such as outdoor recreation and aesthetic enjoyment. The Forest Service has responded to this challenge by developing a national strategy for responding to climate change (the National Roadmap for Responding to Climate Change, July 2010). In concert with this national strategy, the Forest Service's Westwide Climate Initiative has conducted 4 case studies on individual Forests in the western U.S to develop climate adaptation tools. Western National Forests are particularly vulnerable to climate change as they have high-mountain topography, diversity in climate and vegetation, large areas of water limited ecosystems, and increasing urbanization. Information about the vulnerability and capacity of resources to adapt to climate change and extremes is lacking. There is an urgent need to provide customized tools and synthesized local scale information about the impacts to resources from future climate change and extremes, as well as develop science based adaptation options and strategies in National Forest management and planning. The case study on the Shoshone National Forest has aligned its objectives with management needs by developing a climate extreme vulnerability tool that guides adaptation options development. The vulnerability tool determines the likely degree to which native Yellowstone cutthroat trout and water availability are susceptible to, or unable to cope with adverse effects of climate change extremes. We spatially categorize vulnerability for water and native trout resources using exposure, sensitivity, and adaptive capacity indicators that use minimum and maximum climate and GIS data. Results show that the vulnerability of water availability may increase in areas that have less storage and become more dominated by rain instead of snow. Native trout habitat was found to improve in some areas from warmer temperatures suggesting future refugia habitat may need to be a focus of conservation efforts. The climate extreme vulnerability tool provides Forest Service resource managers science based information that guides adaptation strategy development; prioritize conservation projects; guides monitoring efforts, and helps promote more resilient ecosystems undergoing the effects of climate change.

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

NASA Astrophysics Data System (ADS)

Bennett, Katrina E.; Urrego Blanco, Jorge R.; Jonko, Alexandra; Bohn, Theodore J.; Atchley, Adam L.; Urban, Nathan M.; Middleton, Richard S.

2018-01-01

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. 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. We find that snow-dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.

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.

Decision-support tools for Extreme Weather and Climate Events in the Northeast United States

NASA Astrophysics Data System (ADS)

Kumar, S.; Lowery, M.; Whelchel, A.

2013-12-01

Decision-support tools were assessed for the 2013 National Climate Assessment technical input document, "Climate Change in the Northeast, A Sourcebook". The assessment included tools designed to generate and deliver actionable information to assist states and highly populated urban and other communities in assessment of climate change vulnerability and risk, quantification of effects, and identification of adaptive strategies in the context of adaptation planning across inter-annual, seasonal and multi-decadal time scales. State-level adaptation planning in the Northeast has generally relied on qualitative vulnerability assessments by expert panels and stakeholders, although some states have undertaken initiatives to develop statewide databases to support vulnerability assessments by urban and local governments, and state agencies. The devastation caused by Superstorm Sandy in October 2012 has raised awareness of the potential for extreme weather events to unprecedented levels and created urgency for action, especially in coastal urban and suburban communities that experienced pronounced impacts - especially in New Jersey, New York and Connecticut. Planning approaches vary, but any adaptation and resiliency planning process must include the following: - Knowledge of the probable change in a climate variable (e.g., precipitation, temperature, sea-level rise) over time or that the climate variable will attain a certain threshold deemed to be significant; - Knowledge of intensity and frequency of climate hazards (past, current or future events or conditions with potential to cause harm) and their relationship with climate variables; - Assessment of climate vulnerabilities (sensitive resources, infrastructure or populations exposed to climate-related hazards); - Assessment of relative risks to vulnerable resources; - Identification and prioritization of adaptive strategies to address risks. Many organizations are developing decision-support tools to assist in the urban planning process by addressing some of these needs. In this paper we highlight the decision tools available today, discuss their application in selected case studies, and present a gap analysis with opportunities for innovation and future work.

Accounting for adaptive capacity and uncertainty in assessments of species' climate-change vulnerability.

PubMed

Wade, Alisa A; Hand, Brian K; Kovach, Ryan P; Luikart, Gordon; Whited, Diane C; Muhlfeld, Clint C

2017-02-01

Climate-change vulnerability assessments (CCVAs) are valuable tools for assessing species' vulnerability to climatic changes, yet failure to include measures of adaptive capacity and to account for sources of uncertainty may limit their effectiveness. We took a more comprehensive approach that incorporates exposure, sensitivity, and capacity to adapt to climate change. We applied our approach to anadromous steelhead trout (Oncorhynchus mykiss) and nonanadromous bull trout (Salvelinus confluentus), threatened salmonids within the Columbia River Basin (U.S.A.). We quantified exposure on the basis of scenarios of future stream temperature and flow, and we represented sensitivity and capacity to adapt to climate change with metrics of habitat quality, demographic condition, and genetic diversity. Both species were found to be highly vulnerable to climate change at low elevations and in their southernmost habitats. However, vulnerability rankings varied widely depending on the factors (climate, habitat, demographic, and genetic) included in the CCVA and often differed for the 2 species at locations where they were sympatric. Our findings illustrate that CCVA results are highly sensitive to data inputs and that spatial differences can complicate multispecies conservation. Based on our results, we suggest that CCVAs be considered within a broader conceptual and computational framework and be used to refine hypotheses, guide research, and compare plausible scenarios of species' vulnerability to climate change. © 2016 Society for Conservation Biology.

Comparison of four modeling tools for the prediction of potential distribution for non-indigenous weeds in the United States

USGS Publications Warehouse

Magarey, Roger; Newton, Leslie; Hong, Seung C.; Takeuchi, Yu; Christie, Dave; Jarnevich, Catherine S.; Kohl, Lisa; Damus, Martin; Higgins, Steven I.; Miller, Leah; Castro, Karen; West, Amanda; Hastings, John; Cook, Gericke; Kartesz, John; Koop, Anthony

2018-01-01

This study compares four models for predicting the potential distribution of non-indigenous weed species in the conterminous U.S. The comparison focused on evaluating modeling tools and protocols as currently used for weed risk assessment or for predicting the potential distribution of invasive weeds. We used six weed species (three highly invasive and three less invasive non-indigenous species) that have been established in the U.S. for more than 75 years. The experiment involved providing non-U. S. location data to users familiar with one of the four evaluated techniques, who then developed predictive models that were applied to the United States without knowing the identity of the species or its U.S. distribution. We compared a simple GIS climate matching technique known as Proto3, a simple climate matching tool CLIMEX Match Climates, the correlative model MaxEnt, and a process model known as the Thornley Transport Resistance (TTR) model. Two experienced users ran each modeling tool except TTR, which had one user. Models were trained with global species distribution data excluding any U.S. data, and then were evaluated using the current known U.S. distribution. The influence of weed species identity and modeling tool on prevalence and sensitivity effects was compared using a generalized linear mixed model. Each modeling tool itself had a low statistical significance, while weed species alone accounted for 69.1 and 48.5% of the variance for prevalence and sensitivity, respectively. These results suggest that simple modeling tools might perform as well as complex ones in the case of predicting potential distribution for a weed not yet present in the United States. Considerations of model accuracy should also be balanced with those of reproducibility and ease of use. More important than the choice of modeling tool is the construction of robust protocols and testing both new and experienced users under blind test conditions that approximate operational conditions.

Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

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

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climatemore » change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.« less

Limits to health adaptation in a changing climate

NASA Astrophysics Data System (ADS)

Ebi, K. L.

2015-12-01

Introduction: Because the health risks of climate variability and change are not new, it has been assumed that health systems have the capacity, experience, and tools to effectively adapt to changing burdens of climate-sensitive health outcomes with additional climate change. However, as illustrated in the Ebola crisis, health systems in many low-income countries have insufficient capacity to manage current health burdens. These countries also are those most vulnerable to climate change, including changes in food and water safety and security, increases in extreme weather and climate events, and increases in the geographic range, incidence, and seasonality of a variety of infectious diseases. The extent to which they might be able to keep pace with projected risks depends on assumptions of the sustainability of development pathways. At the same time, the magnitude and pattern of climate change will depend on greenhouse gas emission pathways. Methods: Review of the success of health adaptation projects and expert judgment assessment of the degree to which adaptation efforts will be able to keep pace with projected changes in climate variability and change. Results: Health adaptation can reduce the current and projected burdens of climate-sensitive health outcomes over the short term in many countries, but the extent to which it could do so past mid-century will depend on emission and development pathways. Under high emission scenarios, climate change will be rapid and extensive, leading to fundamental shifts in the burden of climate-sensitive health outcomes that will challenging for many countries to manage. Sustainable development pathways could delay but not eliminate associated health burdens. Conclusions: To prepare for and cope with the Anthropocene, health systems need additional adaptation policies and measures to develop more robust health systems, and need to advocate for rapid and significant reductions in greenhouse gas emissions.

Economic Evidence on the Health Impacts of Climate Change in Europe

PubMed Central

Hutton, Guy; Menne, Bettina

2014-01-01

BACKGROUND In responding to the health impacts of climate change, economic evidence and tools inform decision makers of the efficiency of alternative health policies and interventions. In a time when sweeping budget cuts are affecting all tiers of government, economic evidence on health protection from climate change spending enables comparison with other public spending. METHODS The review included 53 countries of the World Health Organization (WHO) European Region. Literature was obtained using a Medline and Internet search of key terms in published reports and peer-reviewed literature, and from institutions working on health and climate change. Articles were included if they provided economic estimation of the health impacts of climate change or adaptation measures to protect health from climate change in the WHO European Region. Economic studies are classified under health impact cost, health adaptation cost, and health economic evaluation (comparing both costs and impacts). RESULTS A total of 40 relevant studies from Europe were identified, covering the health damage or adaptation costs related to the health effects of climate change and response measures to climate-sensitive diseases. No economic evaluation studies were identified of response measures specific to the impacts of climate change. Existing studies vary in terms of the economic outcomes measured and the methods for evaluation of health benefits. The lack of robust health impact data underlying economic studies significantly affects the availability and precision of economic studies. CONCLUSIONS Economic evidence in European countries on the costs of and response to climate-sensitive diseases is extremely limited and fragmented. Further studies are urgently needed that examine health impacts and the costs and efficiency of alternative responses to climate-sensitive health conditions, in particular extreme weather events (other than heat) and potential emerging diseases and other conditions threatening Europe. PMID:25452694

Economic evidence on the health impacts of climate change in europe.

PubMed

Hutton, Guy; Menne, Bettina

2014-01-01

In responding to the health impacts of climate change, economic evidence and tools inform decision makers of the efficiency of alternative health policies and interventions. In a time when sweeping budget cuts are affecting all tiers of government, economic evidence on health protection from climate change spending enables comparison with other public spending. The review included 53 countries of the World Health Organization (WHO) European Region. Literature was obtained using a Medline and Internet search of key terms in published reports and peer-reviewed literature, and from institutions working on health and climate change. Articles were included if they provided economic estimation of the health impacts of climate change or adaptation measures to protect health from climate change in the WHO European Region. Economic studies are classified under health impact cost, health adaptation cost, and health economic evaluation (comparing both costs and impacts). A total of 40 relevant studies from Europe were identified, covering the health damage or adaptation costs related to the health effects of climate change and response measures to climate-sensitive diseases. No economic evaluation studies were identified of response measures specific to the impacts of climate change. Existing studies vary in terms of the economic outcomes measured and the methods for evaluation of health benefits. The lack of robust health impact data underlying economic studies significantly affects the availability and precision of economic studies. Economic evidence in European countries on the costs of and response to climate-sensitive diseases is extremely limited and fragmented. Further studies are urgently needed that examine health impacts and the costs and efficiency of alternative responses to climate-sensitive health conditions, in particular extreme weather events (other than heat) and potential emerging diseases and other conditions threatening Europe.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Future local climate unlike currently observed anywhere

NASA Astrophysics Data System (ADS)

Dahinden, Fabienne; Fischer, Erich M.; Knutti, Reto

2017-08-01

The concept of spatial climate analogs, that is identifying a place with a present-day climate similar to the projections of a place of interest, is a promising method for visualizing and communicating possible effects of climate change. We show that when accounting for seasonal cycles of both temperature and precipitation, it is impossible to find good analogs for projections at many places across the world. For substantial land fractions, primarily in the tropics and subtropics, there are no analogs anywhere with current seasonal cycles of temperature and precipitation matching their projected future conditions. This implies that these places experience the emergence of novel climates. For 1.5 °C global warming about 15% and for 2 °C warming about 21% of the global land is projected to experience novel climates, whereas for a 4 °C warming the corresponding novel climates may emerge on more than a third of the global land fraction. Similar fractions of today’s climates, mainly found in the tropics, subtropics and polar north, are anticipated to disappear in the future. Note that the exact quantification of the land fraction is sensitive to the threshold selection. Novel and disappearing climates may have serious consequences for impacts that are sensitive to the full seasonal cycle of temperature and precipitation. For individual seasons, however, spatial analogs may still be a powerful tool for climate change communication.

Accounting for adaptive capacity and uncertainty in assessments of species’ climate-change vulnerability

USGS Publications Warehouse

Wade, Alisa A.; Hand, Brian K.; Kovach, Ryan; Luikart, Gordon; Whited, Diane; Muhlfeld, Clint C.

2016-01-01

Climate change vulnerability assessments (CCVAs) are valuable tools for assessing species’ vulnerability to climatic changes, yet failure to include measures of adaptive capacity and to account for sources of uncertainty may limit their effectiveness. Here, we provide a more comprehensive CCVA approach that incorporates all three elements used for assessing species’ climate change vulnerability: exposure, sensitivity, and adaptive capacity. We illustrate our approach using case studies of two threatened salmonids with different life histories – anadromous steelhead trout (Oncorhynchus mykiss) and non-anadromous bull trout (Salvelinus confluentus) – within the Columbia River Basin, USA. We identified general patterns of high vulnerability in low-elevation and southernmost habitats for both species. However, vulnerability rankings varied widely depending on the factors (climate, habitat, demographic, and genetic) included in the CCVA and often differed for the two species at locations where they were sympatric. Our findings illustrate that CCVA results are highly sensitive to data inputs and that spatial differences can complicate multi-species conservation. Our results highlight how CCVAs should be considered within a broader conceptual and computational framework for refining hypotheses, guiding research, and comparing plausible scenarios of species’ vulnerability for ongoing and projected climate change.

A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence.

PubMed

Edlund, Stefan; Davis, Matthew; Douglas, Judith V; Kershenbaum, Arik; Waraporn, Narongrit; Lessler, Justin; Kaufman, James H

2012-09-18

The role of the Anopheles vector in malaria transmission and the effect of climate on Anopheles populations are well established. Models of the impact of climate change on the global malaria burden now have access to high-resolution climate data, but malaria surveillance data tends to be less precise, making model calibration problematic. Measurement of malaria response to fluctuations in climate variables offers a way to address these difficulties. Given the demonstrated sensitivity of malaria transmission to vector capacity, this work tests response functions to fluctuations in land surface temperature and precipitation. This study of regional sensitivity of malaria incidence to year-to-year climate variations used an extended Macdonald Ross compartmental disease model (to compute malaria incidence) built on top of a global Anopheles vector capacity model (based on 10 years of satellite climate data). The predicted incidence was compared with estimates from the World Health Organization and the Malaria Atlas. The models and denominator data used are freely available through the Eclipse Foundation's Spatiotemporal Epidemiological Modeller (STEM). Although the absolute scale factor relating reported malaria to absolute incidence is uncertain, there is a positive correlation between predicted and reported year-to-year variation in malaria burden with an averaged root mean square (RMS) error of 25% comparing normalized incidence across 86 countries. Based on this, the proposed measure of sensitivity of malaria to variations in climate variables indicates locations where malaria is most likely to increase or decrease in response to specific climate factors. Bootstrapping measures the increased uncertainty in predicting malaria sensitivity when reporting is restricted to national level and an annual basis. Results indicate a potential 20x improvement in accuracy if data were available at the level ISO 3166-2 national subdivisions and with monthly time sampling. The high spatial resolution possible with state-of-the-art numerical models can identify regions most likely to require intervention due to climate changes. Higher-resolution surveillance data can provide a better understanding of how climate fluctuations affect malaria incidence and improve predictions. An open-source modelling framework, such as STEM, can be a valuable tool for the scientific community and provide a collaborative platform for developing such models.

Stochastic sensitivity analysis of nitrogen pollution to climate change in a river basin with complex pollution sources.

PubMed

Yang, Xiaoying; Tan, Lit; He, Ruimin; Fu, Guangtao; Ye, Jinyin; Liu, Qun; Wang, Guoqing

2017-12-01

It is increasingly recognized that climate change could impose both direct and indirect impacts on the quality of the water environment. Previous studies have mostly concentrated on evaluating the impacts of climate change on non-point source pollution in agricultural watersheds. Few studies have assessed the impacts of climate change on the water quality of river basins with complex point and non-point pollution sources. In view of the gap, this paper aims to establish a framework for stochastic assessment of the sensitivity of water quality to future climate change in a river basin with complex pollution sources. A sub-daily soil and water assessment tool (SWAT) model was developed to simulate the discharge, transport, and transformation of nitrogen from multiple point and non-point pollution sources in the upper Huai River basin of China. A weather generator was used to produce 50 years of synthetic daily weather data series for all 25 combinations of precipitation (changes by - 10, 0, 10, 20, and 30%) and temperature change (increases by 0, 1, 2, 3, and 4 °C) scenarios. The generated daily rainfall series was disaggregated into the hourly scale and then used to drive the sub-daily SWAT model to simulate the nitrogen cycle under different climate change scenarios. Our results in the study region have indicated that (1) both total nitrogen (TN) loads and concentrations are insensitive to temperature change; (2) TN loads are highly sensitive to precipitation change, while TN concentrations are moderately sensitive; (3) the impacts of climate change on TN concentrations are more spatiotemporally variable than its impacts on TN loads; and (4) wide distributions of TN loads and TN concentrations under individual climate change scenario illustrate the important role of climatic variability in affecting water quality conditions. In summary, the large variability in SWAT simulation results within and between each climate change scenario highlights the uncertainty of the impacts of climate change and the need to incorporate extreme conditions in managing water environment and developing climate change adaptation and mitigation strategies.

A network-base analysis of CMIP5 "historical" experiments

NASA Astrophysics Data System (ADS)

Bracco, A.; Foudalis, I.; Dovrolis, C.

2012-12-01

In computer science, "complex network analysis" refers to a set of metrics, modeling tools and algorithms commonly used in the study of complex nonlinear dynamical systems. Its main premise is that the underlying topology or network structure of a system has a strong impact on its dynamics and evolution. By allowing to investigate local and non-local statistical interaction, network analysis provides a powerful, but only marginally explored, framework to validate climate models and investigate teleconnections, assessing their strength, range, and impacts on the climate system. In this work we propose a new, fast, robust and scalable methodology to examine, quantify, and visualize climate sensitivity, while constraining general circulation models (GCMs) outputs with observations. The goal of our novel approach is to uncover relations in the climate system that are not (or not fully) captured by more traditional methodologies used in climate science and often adopted from nonlinear dynamical systems analysis, and to explain known climate phenomena in terms of the network structure or its metrics. Our methodology is based on a solid theoretical framework and employs mathematical and statistical tools, exploited only tentatively in climate research so far. Suitably adapted to the climate problem, these tools can assist in visualizing the trade-offs in representing global links and teleconnections among different data sets. Here we present the methodology, and compare network properties for different reanalysis data sets and a suite of CMIP5 coupled GCM outputs. With an extensive model intercomparison in terms of the climate network that each model leads to, we quantify how each model reproduces major teleconnections, rank model performances, and identify common or specific errors in comparing model outputs and observations.

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.

Improving assessment and modelling of climate change impacts on global terrestrial biodiversity.

PubMed

McMahon, Sean M; Harrison, Sandy P; Armbruster, W Scott; Bartlein, Patrick J; Beale, Colin M; Edwards, Mary E; Kattge, Jens; Midgley, Guy; Morin, Xavier; Prentice, I Colin

2011-05-01

Understanding how species and ecosystems respond to climate change has become a major focus of ecology and conservation biology. Modelling approaches provide important tools for making future projections, but current models of the climate-biosphere interface remain overly simplistic, undermining the credibility of projections. We identify five ways in which substantial advances could be made in the next few years: (i) improving the accessibility and efficiency of biodiversity monitoring data, (ii) quantifying the main determinants of the sensitivity of species to climate change, (iii) incorporating community dynamics into projections of biodiversity responses, (iv) accounting for the influence of evolutionary processes on the response of species to climate change, and (v) improving the biophysical rule sets that define functional groupings of species in global models. Published by Elsevier Ltd.

Development of a sensitivity and uncertainty analysis tool in R for parametrization of the APEX model

USDA-ARS?s Scientific Manuscript database

Hydrologic models are used to simulate the responses of agricultural systems to different inputs and management strategies to identify alternative management practices to cope up with future climate and/or geophysical changes. The Agricultural Policy/Environmental eXtender (APEX) is a model develope...

Applying a simple water-energy balance framework to predict the climate sensitivity of streamflow over the continental United States

NASA Astrophysics Data System (ADS)

Renner, M.; Bernhofer, C.

2011-12-01

The prediction of climate effects on terrestrial ecosystems and water resources is one of the major research questions in hydrology. Conceptual water-energy balance models can be used to gain a first order estimate of how long-term average streamflow is changing with a change in water and energy supply. A common framework for investigation of this question is based on the Budyko hypothesis, which links hydrological response to aridity. Recently, Renner et al. (2011) introduced the CCUW hypothesis, which is based on the assumption that the total efficiency of the catchment ecosystem to use the available water and energy for actual evapotranspiration remains constant even under climate changes. Here, we confront the climate sensitivity approaches (including several versions of Budyko's approach and the CCUW) with data of more than 400 basins distributed over the continental United States. We first map an estimate of the sensitivity of streamflow to changes in precipitation using long-term average data of the period 1949-2003. This provides a hydro-climatic status of the respective basins as well as their expected proportional effect on changes in climate. Next, by splitting the data in two periods, we (i) analyse the long-term average changes in hydro-climatolgy, we (ii) use the different climate sensitivity methods to predict the change in streamflow given the observed changes in water and energy supply and (iii) we apply a quantitative approach to separate the impacts of changes in the long-term average climate from basin characteristics change on streamflow. This allows us to evaluate the observed changes in streamflow as well as to evaluate the impact of basin changes on the validity of climate sensitivity approaches. The apparent increase of streamflow in the majority of basins in the US is dominated by a climate trend towards increased humidity. It is further evident that impacts of changes in basin characteristics appear in parallel with climate changes. There are coherent spatial patterns with basins of increasing catchment efficiency being dominant in the western and central parts of the US. A hot spot of decreasing efficiency is found within the US Midwest. The impact of basin changes on the prediction is large and can be twice as the observed change signal. However, we find that both, the CCUW hypothesis and the approaches using the Budyko hypothesis, show minimal deviations between observed and predicted changes in streamflow for basins where a dominance of climatic changes and low influences of basin changes have been found. Thus, climate sensitivity methods can be regarded as valid tools if we expect climate changes only and neglect any direct anthropogenic influences.

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

Famine Early Warning Systems Network (FEWS NET) Contributions to Strengthening Resilience and Sustainability for the East African Community

NASA Astrophysics Data System (ADS)

Budde, M. E.; Galu, G.; Funk, C. C.; Verdin, J. P.; Rowland, J.

2014-12-01

The Planning for Resilience in East Africa through Policy, Adaptation, Research, and Economic Development (PREPARED) is a multi-organizational project aimed at mainstreaming climate-resilient development planning and program implementation into the East African Community (EAC). The Famine Early Warning Systems Network (FEWS NET) has partnered with the PREPARED project to address three key development challenges for the EAC; 1) increasing resiliency to climate change, 2) managing trans-boundary freshwater biodiversity and conservation and 3) improving access to drinking water supply and sanitation services. USGS FEWS NET has been instrumental in the development of gridded climate data sets that are the fundamental building blocks for climate change adaptation studies in the region. Tools such as the Geospatial Climate Tool (GeoCLIM) have been developed to interpolate time-series grids of precipitation and temperature values from station observations and associated satellite imagery, elevation data, and other spatially continuous fields. The GeoCLIM tool also allows the identification of anomalies and assessments of both their frequency of occurrence and directional trends. A major effort has been put forth to build the capacities of local and regional institutions to use GeoCLIM to integrate their station data (which is not typically available to the public) into improved national and regional gridded climate data sets. In addition to the improvements and capacity building activities related to geospatial analysis tools, FEWS NET will assist in two other areas; 1) downscaling of climate change scenarios and 2) vulnerability impact assessments. FEWS NET will provide expertise in statistical downscaling of Global Climate Model output fields and work with regional institutions to assess results of other downscaling methods. Completion of a vulnerability impact assessment (VIA) involves the examination of sectoral consequences in identified climate "hot spots". FEWS NET will lead the VIA for the agriculture and food security sector, but will also provide key geospatial layers needed by multiple sectors in the areas of exposure, sensitivity, and adaptive capacity. Project implementation will strengthen regional coordination in policy-making, planning, and response to climate change issues.

Tailored stakeholder products help provide a vulnerability and adaptation assessment of Greek forests due to climate change

NASA Astrophysics Data System (ADS)

Giannakopoulos, Christos; Karali, Anna; Roussos, Anargyros

2014-05-01

Greece, being part of the eastern Mediterranean basin, is an area particularly vulnerable to climate change and associated forest fire risk. The aim of this study is to assess the vulnerability of Greek forests to fire risk occurrence and identify potential adaptation options within the context of climate change through continuous interaction with local stakeholders. To address their needs, the following tools for the provision of climate information services were developed: 1. An application providing fire risk forecasts for the following 3 days (http://cirrus.meteo.noa.gr/forecast/bolam/index.htm) was developed from NOA to address the needs of short term fire planners. 2. A web-based application providing long term fire risk and other fire related indices changes due to climate change (time horizon up to 2050 and 2100) was developed in collaboration with the WWF Greece office to address the needs of long term fire policy makers (http://www.oikoskopio.gr/map/). 3. An educational tool was built in order to complement the two web-based tools and to further expand knowledge in fire risk modeling to address the needs for in-depth training. In particular, the second product provided the necessary information to assess the exposure to forest fires. To this aim, maps depicting the days with elevated fire risk (FWI>30) both for the control (1961-1990) and the near future period (2021-2050) were created by the web-application. FWI is a daily index that provides numerical ratings of relative fire potential based solely on weather observations. The meteorological inputs to the FWI System are daily noon values of temperature, air relative humidity, 10m wind speed and precipitation during the previous 24 hours. It was found that eastern lowlands are more exposed to fire risk followed by eastern high elevation areas, for both the control and near future period. The next step towards vulnerability assessment was to address sensitivity, ie the human-environmental conditions that can worsen or ameliorate the hazard. In our study static information concerning fire affecting factors, namely the topography and vegetation, was used to create a fire hazard map in order to assess the sensitivity factor. Land cover types for the year 2007 were combined with topographic information deriving from a digital elevation model order to produce these maps. High elevation continental areas were found to be the most sensitive areas followed by the lowland continental areas. Exposure and sensitivity were combined to produce the overall impact of climate change to forest fire risk. The adaptive capacity is defined by the ability of forests to adapt to changing environmental conditions. To assess the adaptive capacity of Greek forests, a Multi-Criteria Analysis (MCA) tool was implemented and used by the stakeholders. The major proposed adaptation measures for Greek forests included fire prevention measures and the inclusion of the private forest covered areas in the fire fighting. Finally, vulnerability of Greek forest to fire was estimated as the overall impact of climate change minus the forests' adaptive capacity and was found to be medium for most areas in the country. Acknowledgement: This work was supported by the EU project CLIM-RUN under contract FP7-ENV-2010-265192.

Collaborative Research: Quantifying the Uncertainties of Aerosol Indirect Effects and Impacts on Decadal-Scale Climate Variability in NCAR CAM5 and CESM1

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

Nenes, Athanasios

The goal of this proposed project is to assess the climatic importance and sensitivity of aerosol indirect effect (AIE) to cloud and aerosol processes and feedbacks, which include organic aerosol hygroscopicity, cloud condensation nuclei (CCN) activation kinetics, Giant CCN, cloud-scale entrainment, ice nucleation in mixed-phase and cirrus clouds, and treatment of subgrid variability of vertical velocity. A key objective was to link aerosol, cloud microphysics and dynamics feedbacks in CAM5 with a suite of internally consistent and integrated parameterizations that provide the appropriate degrees of freedom to capture the various aspects of the aerosol indirect effect. The proposal integrated newmore » parameterization elements into the cloud microphysics, moist turbulence and aerosol modules used by the NCAR Community Atmospheric Model version 5 (CAM5). The CAM5 model was then used to systematically quantify the uncertainties of aerosol indirect effects through a series of sensitivity tests with present-day and preindustrial aerosol emissions. New parameterization elements were developed as a result of these efforts, and new diagnostic tools & methodologies were also developed to quantify the impacts of aerosols on clouds and climate within fully coupled models. Observations were used to constrain key uncertainties in the aerosol-cloud links. Advanced sensitivity tools were developed and implements to probe the drivers of cloud microphysical variability with unprecedented temporal and spatial scale. All these results have been published in top and high impact journals (or are in the final stages of publication). This proposal has also supported a number of outstanding graduate students.« less

Developing an Ecosystem Services Online Decision Support Tool to Assess the Impacts of Climate Change and Urban Growth in the Santa Cruz Watershed: Where We Live, Work, and Play

USGS Publications Warehouse

Norman, Laura; Tallent-Halsell, Nita; Labiosa, William; Weber, Matt; McCoy, Amy; Hirschboeck, Katie; Callegary, James; van Riper, Charles; Gray, Floyd

2010-01-01

Using respective strengths of the biological, physical, and social sciences, we are developing an online decision support tool, the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM), to help promote the use of information relevant to water allocation and land management in a binational watershed along the U.S.-Mexico border. The SCWEPM will include an ES valuation system within a suite of linked regional driver-response models and will use a multicriteria scenario-evaluation framework that builds on GIS analysis and spatially-explicit models that characterize important ecological, economic, and societal endpoints and consequences that are sensitive to climate patterns, regional water budgets, and regional LULC change in the SCW.

Development of a system emulating the global carbon cycle in Earth system models

NASA Astrophysics Data System (ADS)

Tachiiri, K.; Hargreaves, J. C.; Annan, J. D.; Oka, A.; Abe-Ouchi, A.; Kawamiya, M.

2010-08-01

Recent studies have indicated that the uncertainty in the global carbon cycle may have a significant impact on the climate. Since state of the art models are too computationally expensive for it to be possible to explore their parametric uncertainty in anything approaching a comprehensive fashion, we have developed a simplified system for investigating this problem. By combining the strong points of general circulation models (GCMs), which contain detailed and complex processes, and Earth system models of intermediate complexity (EMICs), which are quick and capable of large ensembles, we have developed a loosely coupled model (LCM) which can represent the outputs of a GCM-based Earth system model, using much smaller computational resources. We address the problem of relatively poor representation of precipitation within our EMIC, which prevents us from directly coupling it to a vegetation model, by coupling it to a precomputed transient simulation using a full GCM. The LCM consists of three components: an EMIC (MIROC-lite) which consists of a 2-D energy balance atmosphere coupled to a low resolution 3-D GCM ocean (COCO) including an ocean carbon cycle (an NPZD-type marine ecosystem model); a state of the art vegetation model (Sim-CYCLE); and a database of daily temperature, precipitation, and other necessary climatic fields to drive Sim-CYCLE from a precomputed transient simulation from a state of the art AOGCM. The transient warming of the climate system is calculated from MIROC-lite, with the global temperature anomaly used to select the most appropriate annual climatic field from the pre-computed AOGCM simulation which, in this case, is a 1% pa increasing CO2 concentration scenario. By adjusting the effective climate sensitivity (equivalent to the equilibrium climate sensitivity for an energy balance model) of MIROC-lite, the transient warming of the LCM could be adjusted to closely follow the low sensitivity (with an equilibrium climate sensitivity of 4.0 K) version of MIROC3.2. By tuning of the physical and biogeochemical parameters it was possible to reasonably reproduce the bulk physical and biogeochemical properties of previously published CO2 stabilisation scenarios for that model. As an example of an application of the LCM, the behavior of the high sensitivity version of MIROC3.2 (with a 6.3 K equilibrium climate sensitivity) is also demonstrated. Given the highly adjustable nature of the model, we believe that the LCM should be a very useful tool for studying uncertainty in global climate change, and we have named the model, JUMP-LCM, after the name of our research group (Japan Uncertainty Modelling Project).

Navigating the high seas of Federal Programs to ensure usable science delivery

NASA Astrophysics Data System (ADS)

Bachelet, D. M.; Gough, M.; Baker, B.; Sheehan, T.; Mutch, T.; Brown, M.

2016-12-01

Conservation Biology Institute (CBI) has been developing web applications to serve credible and usable information that allows land stewards, as well as the general public, to better understand the challenges posed by on-going environmental change. Working with 18 Landscape Conservation Cooperatives (LCCs), CBI has developed Conservation Atlases that allow users to visualize regional spatial data. Some include specific tools such as the Conservation Blueprint in the South Atlantic LCC conservation atlas which is a living spatial plan that identifies priority areas for shared conservation action based on ecosystem indicator condition and connectivity. More than 400 people from over 100 different organizations have actively participated in its development so far. CBI worked closely with 4 LCCs to design a Landscape Climate Dashboard (http://bit.ly/2atu8Df) that provides CMIP5 climate projections averaged over federally and tribally protected lands in the western US. With support from BLM and Great Basin LCC, a Sagebrush Climate Console provides managers short-term NOAA forecasts, CMIP5 climate projections, regional intactness and site sensitivity over sagebrush extent and grouse range. The USDA Pacific Northwest Climate Hub and the US Forest Service are currently funding a collaborative effort between CBI programmers, USFS and Oregon State University forest geneticists to develop a seedlot source tool for the conterminous US and Alaska. This tool has inspired Great Basin sagebrush restoration scientists who have collected information on seed provenance and will hopefully soon collaborate to help develop the first seed source tool for sagebrush managers. Furthermore, with support from USDA Northwest Climate Hub, CBI's Data Basin site (http://bit.ly/2aLRlhZ) is providing downscaled CMIP5 climate projections and impacts from a Climate Science Center and NOAA Regional Integrated Science Assessment funded project that was the result of a collaborative effort between Oregon State University, University of Idaho, and the University of Washington. With much experience with local and regional managers and federal programs we will show examples of exciting successes and report on some challenges in coordinating exchanges and extracting valuable feedback to improve the usability of web applications.

Desert dust and anthropogenic aerosol interactions in the Community Climate System Model coupled-carbon-climate model

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

Mahowald, Natalie; Rothenberg, D.; Lindsay, Keith

2011-02-01

Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries) and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climatemore » feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.« less

An observationally centred method to quantify local climate change as a distribution

NASA Astrophysics Data System (ADS)

Stainforth, David; Chapman, Sandra; Watkins, Nicholas

2013-04-01

For planning and adaptation, guidance on trends in local climate is needed at the specific thresholds relevant to particular impact or policy endeavours. This requires quantifying trends at specific quantiles in distributions of variables such as daily temperature or precipitation. These non-normal distributions vary both geographically and in time. The trends in the relevant quantiles may not simply follow the trend in the distribution mean. We present a method[1] for analysing local climatic timeseries data to assess which quantiles of the local climatic distribution show the greatest and most robust trends. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily temperature from specific locations across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of the sensitivity of different quantiles of the distributions to changing climate. Geographical location and temperature are treated as independent variables, we thus obtain as outputs how the trend or sensitivity varies with temperature (or occurrence likelihood), and with geographical location. These sensitivities are found to be geographically varying across Europe; as one would expect given the different influences on local climate between, say, Western Scotland and central Italy. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. We discuss methods to quantify the robustness of these observed sensitivities and their statistical likelihood. This also quantifies the level of detail needed from climate models if they are to be used as tools to assess climate change impact. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, in press [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, doi:10.1029/2008JD10201

The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols

NASA Technical Reports Server (NTRS)

Shukla, Sonali P.; Ruane, Alexander Clark

2014-01-01

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, and water (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models' responses to CTW changes (Rotter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012). To fulfill this need, the Coordinated Climate-Crop Modeling Project (C3MP) (Ruane et al., 2014) was initiated within the Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013). The submitted results from C3MP Phase 1 (February 15, 2013-December 31, 2013) are currently being analyzed. This chapter serves to present and update the C3MP protocols, discuss the initial participation and general findings, comment on needed adjustments, and describe continued and future development. AgMIP aims to improve substantially the climate, crop, and economic simulation tools that are used to characterize the agricultural sector, to assess future world food security under changing climate conditions, and to enhance adaptation capacity both globally and regionally. To understand better and improve the modeled crop responses, AgMIP has conducted detailed crop model intercomparisons at closely observed field sites for wheat (Asseng et al., 2013), rice (Li et al., in review), maize (Bassu et al., 2014), and sugarcane (Singels et al., 2013). A coordinated modeling exercise was one of the original motivations for AgMIP, and C3MP provides rapid estimation of crop responses to CO2, water, and temperature (CTW) changes, adding dimension and insight into the crop model intercomparisons, while facilitating interactions within the global community of modelers. C3MP also contributes a fast-track, multi-model climate sensitivity assessment for the AgMIP climate and crop modeling teams on Research Track 2 (Fig. 1), which seeks to understand the impact of projected climatic changes on crop production and food security (Rosenzweig et al., 2013; Ruane et al., 2014).

Lakes as sentinels of climate change

PubMed Central

Adrian, Rita; O’Reilly, Catherine M.; Zagarese, Horacio; Baines, Stephen B.; Hessen, Dag O.; Keller, Wendel; Livingstone, David M.; Sommaruga, Ruben; Straile, Dietmar; Van Donk, Ellen; Weyhenmeyer, Gesa A.; Winder, Monika

2010-01-01

While there is a general sense that lakes can act as sentinels of climate change, their efficacy has not been thoroughly analyzed. We identified the key response variables within a lake that act as indicators of the effects of climate change on both the lake and the catchment. These variables reflect a wide range of physical, chemical, and biological responses to climate. However, the efficacy of the different indicators is affected by regional response to climate change, characteristics of the catchment, and lake mixing regimes. Thus, particular indicators or combinations of indicators are more effective for different lake types and geographic regions. The extraction of climate signals can be further complicated by the influence of other environmental changes, such as eutrophication or acidification, and the equivalent reverse phenomena, in addition to other land-use influences. In many cases, however, confounding factors can be addressed through analytical tools such as detrending or filtering. Lakes are effective sentinels for climate change because they are sensitive to climate, respond rapidly to change, and integrate information about changes in the catchment. PMID:20396409

Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems?

NASA Astrophysics Data System (ADS)

Safaei, S.; Haghnegahdar, A.; Razavi, S.

2016-12-01

Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.

An Environmental Scan Tool to Assess District and School Readiness to Support Transgender and Gender Diverse Youth

ERIC Educational Resources Information Center

Savage, Todd A.; Springborg, Heidi; Lagerstrom, Leslie

2017-01-01

It is important that districts and schools do everything they can to create and maintain school climates and environments that are sensitive and responsive to the various educational, social, emotional, and behavioral needs of transgender and gender diverse students, regardless of the actual presence of a student who identifies as something other…

NOAA Climate Information and Tools for Decision Support Services

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.

2013-12-01

NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to provision of information that will help guide long-term preparedness for severe weather events and extreme conditions as well as climate variability and change GFCS recently summarized examples of existing initiatives to advance provision of climate services in the 2012 publication Climate ExChange. In this publication, NWS introduced the new Local Climate Analysis Tool (LCAT), a tool that is used to conduct local climate studies that are needed to create efficient and reliable guidance for DSS. LCAT allows for analyzing trends in local climate variables and identifying local impacts of climate variability (e.g., ENSO) on weather and water conditions. In addition to LCAT, NWS, working in partnership with the North East Regional Climate center, released xmACIS version 2, a climate data mining tool, for NWS field operations. During this talk we will demonstrate LCAT and xmACIS as well as outline several examples of their application to DSS and its potential use for achieving GFCS goals. The examples include LCAT-based temperature analysis for energy decisions, guidance on weather and water events leading to increased algal blooms and red tide months in advance, local climate sensitivities to droughts, probabilities of hot/cold conditions and their potential impacts on agriculture and fish kills or fish stress.

A new statistical tool for NOAA local climate studies

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Meyers, J. C.; Hollingshead, A.

2011-12-01

The National Weather Services (NWS) Local Climate Analysis Tool (LCAT) is evolving out of a need to support and enhance the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) field offices' ability to efficiently access, manipulate, and interpret local climate data and characterize climate variability and change impacts. LCAT will enable NOAA's staff to conduct regional and local climate studies using state-of-the-art station and reanalysis gridded data and various statistical techniques for climate analysis. The analysis results will be used for climate services to guide local decision makers in weather and climate sensitive actions and to deliver information to the general public. LCAT will augment current climate reference materials with information pertinent to the local and regional levels as they apply to diverse variables appropriate to each locality. The LCAT main emphasis is to enable studies of extreme meteorological and hydrological events such as tornadoes, flood, drought, severe storms, etc. LCAT will close a very critical gap in NWS local climate services because it will allow addressing climate variables beyond average temperature and total precipitation. NWS external partners and government agencies will benefit from the LCAT outputs that could be easily incorporated into their own analysis and/or delivery systems. Presently we identified five existing requirements for local climate: (1) Local impacts of climate change; (2) Local impacts of climate variability; (3) Drought studies; (4) Attribution of severe meteorological and hydrological events; and (5) Climate studies for water resources. The methodologies for the first three requirements will be included in the LCAT first phase implementation. Local rate of climate change is defined as a slope of the mean trend estimated from the ensemble of three trend techniques: (1) hinge, (2) Optimal Climate Normals (running mean for optimal time periods), (3) exponentially-weighted moving average. Root mean squared error is used to determine the best fit of trend to the observations with the least error. The studies of climate variability impacts on local extremes use composite techniques applied to various definitions of local variables: from specified percentiles to critical thresholds. Drought studies combine visual capabilities of Google maps with statistical estimates of drought severity indices. The process of development will be linked to local office interactions with users to ensure the tool will meet their needs as well as provide adequate training. A rigorous internal and tiered peer-review process will be implemented to ensure the studies are scientifically-sound that will be published and submitted to the local studies catalog (database) and eventually to external sources, such as the Climate Portal.

Biotic and Climatic Velocity Identify Contrasting Areas of Vulnerability to Climate Change.

PubMed

Carroll, Carlos; Lawler, Joshua J; Roberts, David R; Hamann, Andreas

2015-01-01

Metrics that synthesize the complex effects of climate change are essential tools for mapping future threats to biodiversity and predicting which species are likely to adapt in place to new climatic conditions, disperse and establish in areas with newly suitable climate, or face the prospect of extirpation. The most commonly used of such metrics is the velocity of climate change, which estimates the speed at which species must migrate over the earth's surface to maintain constant climatic conditions. However, "analog-based" velocities, which represent the actual distance to where analogous climates will be found in the future, may provide contrasting results to the more common form of velocity based on local climate gradients. Additionally, whereas climatic velocity reflects the exposure of organisms to climate change, resultant biotic effects are dependent on the sensitivity of individual species as reflected in part by their climatic niche width. This has motivated development of biotic velocity, a metric which uses data on projected species range shifts to estimate the velocity at which species must move to track their climatic niche. We calculated climatic and biotic velocity for the Western Hemisphere for 1961-2100, and applied the results to example ecological and conservation planning questions, to demonstrate the potential of such analog-based metrics to provide information on broad-scale patterns of exposure and sensitivity. Geographic patterns of biotic velocity for 2954 species of birds, mammals, and amphibians differed from climatic velocity in north temperate and boreal regions. However, both biotic and climatic velocities were greatest at low latitudes, implying that threats to equatorial species arise from both the future magnitude of climatic velocities and the narrow climatic tolerances of species in these regions, which currently experience low seasonal and interannual climatic variability. Biotic and climatic velocity, by approximating lower and upper bounds on migration rates, can inform conservation of species and locally-adapted populations, respectively, and in combination with backward velocity, a function of distance to a source of colonizers adapted to a site's future climate, can facilitate conservation of diversity at multiple scales in the face of climate change.

Biotic and Climatic Velocity Identify Contrasting Areas of Vulnerability to Climate Change

PubMed Central

Carroll, Carlos; Lawler, Joshua J.; Roberts, David R.; Hamann, Andreas

2015-01-01

Metrics that synthesize the complex effects of climate change are essential tools for mapping future threats to biodiversity and predicting which species are likely to adapt in place to new climatic conditions, disperse and establish in areas with newly suitable climate, or face the prospect of extirpation. The most commonly used of such metrics is the velocity of climate change, which estimates the speed at which species must migrate over the earth’s surface to maintain constant climatic conditions. However, “analog-based” velocities, which represent the actual distance to where analogous climates will be found in the future, may provide contrasting results to the more common form of velocity based on local climate gradients. Additionally, whereas climatic velocity reflects the exposure of organisms to climate change, resultant biotic effects are dependent on the sensitivity of individual species as reflected in part by their climatic niche width. This has motivated development of biotic velocity, a metric which uses data on projected species range shifts to estimate the velocity at which species must move to track their climatic niche. We calculated climatic and biotic velocity for the Western Hemisphere for 1961–2100, and applied the results to example ecological and conservation planning questions, to demonstrate the potential of such analog-based metrics to provide information on broad-scale patterns of exposure and sensitivity. Geographic patterns of biotic velocity for 2954 species of birds, mammals, and amphibians differed from climatic velocity in north temperate and boreal regions. However, both biotic and climatic velocities were greatest at low latitudes, implying that threats to equatorial species arise from both the future magnitude of climatic velocities and the narrow climatic tolerances of species in these regions, which currently experience low seasonal and interannual climatic variability. Biotic and climatic velocity, by approximating lower and upper bounds on migration rates, can inform conservation of species and locally-adapted populations, respectively, and in combination with backward velocity, a function of distance to a source of colonizers adapted to a site’s future climate, can facilitate conservation of diversity at multiple scales in the face of climate change. PMID:26466364

Mapping the changing pattern of local climate as an observed distribution

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nicholas

2013-04-01

It is at local scales that the impacts of climate change will be felt directly and at which adaptation planning decisions must be made. This requires quantifying the geographical patterns in trends at specific quantiles in distributions of variables such as daily temperature or precipitation. Here we focus on these local changes and on the way observational data can be analysed to inform us about the pattern of local climate change. We present a method[1] for analysing local climatic timeseries data to assess which quantiles of the local climatic distribution show the greatest and most robust trends. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily temperature from specific locations across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of the sensitivity of different quantiles of the distributions to changing climate. Geographical location and temperature are treated as independent variables, we thus obtain as outputs the pattern of variation in sensitivity with temperature (or occurrence likelihood), and with geographical location. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. We discuss methods to quantify and map the robustness of these observed sensitivities and their statistical likelihood. This also quantifies the level of detail needed from climate models if they are to be used as tools to assess climate change impact. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, in press [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, doi:10.1029/2008JD10201

Testing the reliability of δ13C of tree rings as climate tool in Pistacia khinjuk of Syrian desert

NASA Astrophysics Data System (ADS)

Caracuta, Valentina; Fiorentino, Girolamo

2010-05-01

High-resolution measures of past climate variations have been found to be of a critical importance for understanding anthropic resilience in drought-sensitive areas. The hills (Jebels) Abu-Rujmain and Abd al Aziz, with their 350 millimetre of rain and their steppe-forest spreading in the middle of the flat syrian desert, represent an unicum where analysing the effect of short term climate changes on pastoral communities. Thanks to a cooperation project in Syrian Arab republic with CIHEAM-Mediterranean Agronomic Institute of Bari -Italy (Rationalization of Ras El Ain Irrigation systems), we were allowed to carry out dendroclimate and carbon isotope analyses on tree-rings of local Pistacia khinjuk, a long-lived wood taxon, in order to test their reliability as tool for determining annual and seasonal rainfall/temperature variations. Comparison between the last 25 year rainfall and temperature values of the nearby meteorological stations and dendro-isotopes values have been carried out to point out which factor mostly affect the growth pattern of the trees in that particular area.

Thru-life impacts of driver aggression, climate, cabin thermal management, and battery thermal management on battery electric vehicle utility

NASA Astrophysics Data System (ADS)

Neubauer, Jeremy; Wood, Eric

2014-08-01

Battery electric vehicles (BEVs) offer the potential to reduce both oil imports and greenhouse gas emissions, but have a limited utility that is affected by driver aggression and effects of climate-both directly on battery temperature and indirectly through the loads of cabin and battery thermal management systems. Utility is further affected as the battery wears through life in response to travel patterns, climate, and other factors. In this paper we apply the National Renewable Energy Laboratory's Battery Lifetime Analysis and Simulation Tool for Vehicles (BLAST-V) to examine the sensitivity of BEV utility to driver aggression and climate effects over the life of the vehicle. We find the primary challenge to cold-climate BEV operation to be inefficient cabin heating systems, and to hot-climate BEV operation to be high peak on-road battery temperatures and excessive battery degradation. Active cooling systems appear necessary to manage peak battery temperatures of aggressive, hot-climate drivers, which can then be employed to maximize thru-life vehicle utility.

Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands.

PubMed

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

2015-01-01

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

Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands

PubMed Central

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

2015-01-01

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

Impacts of Climate Anomalies on the Vegetation Patterns in the Arid and Semi-Arid Zones of Uzbekistan

NASA Astrophysics Data System (ADS)

Dildora, Aralova; Toderich, Kristina; Dilshod, Gafurov

2016-08-01

Steadily rising temperature anomalies in last decades are causing changes in vegetation patterns for sensitive to climate change in arid and semi-arid dryland ecosystems. After desiccation of the Aral Sea, Uzbekistan has been left with the challenge to develop drought and heat stress monitoring system and tools (e.g., to monitor vegetation status and/crop pattern dynamics) with using remote sensing technologies in broad scale. This study examines several climate parameters, NDVI and drought indexes within geostatistical method to predict further vegetation status in arid and semi-arid zones of landscapes. This approaches aimed to extract and utilize certain variable environmental data (temperature and precipitation) for assessment and inter-linkages of vegetation cover dynamics, specifically related to predict degraded and recovered zones or desertification process in the drylands due to scarcity of water resources and high risks of climate anomalies in fragile ecosystem of Uzbekistan.

Climate information for public health: the role of the IRI climate data library in an integrated knowledge system.

PubMed

del Corral, John; Blumenthal, M Benno; Mantilla, Gilma; Ceccato, Pietro; Connor, Stephen J; Thomson, Madeleine C

2012-09-01

Public health professionals are increasingly concerned about the potential impact of climate variability and change on health outcomes. Protecting public health from the vagaries of climate requires new working relationships between the public health sector and the providers of climate data and information. The Climate Information for Public Health Action initiative at the International Research Institute for Climate and Society (IRI) is designed to increase the public health community's capacity to understand, use and demand appropriate climate data and climate information to mitigate the public health impacts of the climate. Significant challenges to building the capacity of health professionals to use climate information in research and decision-making include the difficulties experienced by many in accessing relevant and timely quality controlled data and information in formats that can be readily incorporated into specific analysis with other data sources. We present here the capacities of the IRI climate data library and show how we have used it to build an integrated knowledge system in the support of the use of climate and environmental information in climate-sensitive decision-making with respect to health. Initiated as an aid facilitating exploratory data analysis for climate scientists, the IRI climate data library has emerged as a powerful tool for interdisciplinary researchers focused on topics related to climate impacts on society, including health.

Local Climate Zones Classification to Urban Planning in the Mega City of São Paulo - SP, Brazil

NASA Astrophysics Data System (ADS)

Gonçalves Santos, Rafael; Saraiva Lopes, António Manuel; Prata-Shimomura, Alessandra

2017-04-01

Local Climate Zones Classification to Urban Planning in the Mega city of São Paulo - SP, Brazil Tropical megacities have presented a strong trend in growing urban. Urban management in megacities has as one of the biggest challenges is the lack of integration of urban climate and urban planning to promote ecologically smart cities. Local Climatic Zones (LCZs) are considered as important and recognized tool for urban climate management. Classes are local in scale, climatic in nature, and zonal in representation. They can be understood as regions of uniform surface cover, structure, material and human activity that have to a unique climate response. As an initial tool to promote urban climate planning, LCZs represent a simple composition of different land coverages (buildings, vegetation, soils, rock, roads and water). LCZs are divided in 17 classes, they are based on surface cover (built fraction, soil moisture, albedo), surface structure (sky view factor, roughness height) and cultural activity (anthropogenic heat flux). The aim of this study is the application of the LCZs classification system in the megacity of São Paulo, Brazil. Located at a latitude of 23° 21' and longitude 46° 44' near to the Tropic of Capricorn, presenting humid subtropical climate (Cfa) with diversified topographies. The megacity of São Paulo currently concentrates 11.890.000 inhabitants is characterized by large urban conglomerates with impermeable surfaces and high verticalization, having as result high urban heat island intensity. The result indicates predominance in urban zones of Compact low-rise, Compact Mid-rise, Compact High-rise and Open Low-rise. Non-urban regions are mainly covered by dense vegetation and water. The LCZs classification system promotes significant advantages for climate sensitive urban planning in the megacity of São Paulo. They offers new perspectives to the management of temperature and urban ventilation and allows the formulation of urban planning guidelines and climatic. Key words: Local Climatic Zones; Urban Panning; Megacities; São Paulo.

Validation of the Hospital Ethical Climate Survey for older people care.

PubMed

Suhonen, Riitta; Stolt, Minna; Katajisto, Jouko; Charalambous, Andreas; Olson, Linda L

2015-08-01

The exploration of the ethical climate in the care settings for older people is highlighted in the literature, and it has been associated with various aspects of clinical practice and nurses' jobs. However, ethical climate is seldom studied in the older people care context. Valid, reliable, feasible measures are needed for the measurement of ethical climate. This study aimed to test the reliability, validity, and sensitivity of the Hospital Ethical Climate Survey in healthcare settings for older people. A non-experimental cross-sectional study design was employed, and a survey using questionnaires, including the Hospital Ethical Climate Survey was used for data collection. Data were analyzed using descriptive statistics, inferential statistics, and multivariable methods. Survey data were collected from a sample of nurses working in the care settings for older people in Finland (N = 1513, n = 874, response rate = 58%) in 2011. This study was conducted according to good scientific inquiry guidelines, and ethical approval was obtained from the university ethics committee. The mean score for the Hospital Ethical Climate Survey total was 3.85 (standard deviation = 0.56). Cronbach's alpha was 0.92. Principal component analysis provided evidence for factorial validity. LISREL provided evidence for construct validity based on goodness-of-fit statistics. Pearson's correlations of 0.68-0.90 were found between the sub-scales and the Hospital Ethical Climate Survey. The Hospital Ethical Climate Survey was found able to reveal discrimination across care settings and proved to be a valid and reliable tool for measuring ethical climate in care settings for older people and sensitive enough to reveal variations across various clinical settings. The Finnish version of the Hospital Ethical Climate Survey, used mainly in the hospital settings previously, proved to be a valid instrument to be used in the care settings for older people. Further studies are due to analyze the factor structure and some items of the Hospital Ethical Climate Survey. © The Author(s) 2014.

Local indicators of climate change: The potential contribution of local knowledge to climate research

PubMed Central

Reyes-García, Victoria; Fernández-Llamazares, Álvaro; Guèze, Maximilien; Garcés, Ariadna; Mallo, Miguel; Vila-Gómez, Margarita; Vilaseca, Marina

2016-01-01

Local knowledge has been proposed as a place-based tool to ground-truth climate models and to narrow their geographic sensitivity. To assess the potential role of local knowledge in our quest to understand better climate change and its impacts, we first need to critically review the strengths and weaknesses of local knowledge of climate change and the potential complementarity with scientific knowledge. With this aim, we conducted a systematic, quantitative meta-analysis of published peer-reviewed documents reporting local indicators of climate change (including both local observations of climate change and observed impacts on the biophysical and the social systems). Overall, primary data on the topic are not abundant, the methodological development is incipient, and the geographical extent is unbalanced. On the 98 case studies documented, we recorded the mention of 746 local indicators of climate change, mostly corresponding to local observations of climate change (40%), but also to observed impacts on the physical (23%), the biological (19%), and the socioeconomic (18%) systems. Our results suggest that, even if local observations of climate change are the most frequently reported type of change, the rich and fine-grained knowledge in relation to impacts on biophysical systems could provide more original contributions to our understanding of climate change at local scale. PMID:27642368

Decadal-scale sensitivity of Northeast Greenland ice flow to errors in surface mass balance using ISSM

NASA Astrophysics Data System (ADS)

Schlegel, N.-J.; Larour, E.; Seroussi, H.; Morlighem, M.; Box, J. E.

2013-06-01

The behavior of the Greenland Ice Sheet, which is considered a major contributor to sea level changes, is best understood on century and longer time scales. However, on decadal time scales, its response is less predictable due to the difficulty of modeling surface climate, as well as incomplete understanding of the dynamic processes responsible for ice flow. Therefore, it is imperative to understand how modeling advancements, such as increased spatial resolution or more comprehensive ice flow equations, might improve projections of ice sheet response to climatic trends. Here we examine how a finely resolved climate forcing influences a high-resolution ice stream model that considers longitudinal stresses. We simulate ice flow using a two-dimensional Shelfy-Stream Approximation implemented within the Ice Sheet System Model (ISSM) and use uncertainty quantification tools embedded within the model to calculate the sensitivity of ice flow within the Northeast Greenland Ice Stream to errors in surface mass balance (SMB) forcing. Our results suggest that the model tends to smooth ice velocities even when forced with extreme errors in SMB. Indeed, errors propagate linearly through the model, resulting in discharge uncertainty of 16% or 1.9 Gt/yr. We find that mass flux is most sensitive to local errors but is also affected by errors hundreds of kilometers away; thus, an accurate SMB map of the entire basin is critical for realistic simulation. Furthermore, sensitivity analyses indicate that SMB forcing needs to be provided at a resolution of at least 40 km.

Regional Community Climate Simulations with variable resolution meshes in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Zarzycki, C. M.; Gettelman, A.; Callaghan, P.

2017-12-01

Accurately predicting weather extremes such as precipitation (floods and droughts) and temperature (heat waves) requires high resolution to resolve mesoscale dynamics and topography at horizontal scales of 10-30km. Simulating such resolutions globally for climate scales (years to decades) remains computationally impractical. Simulating only a small region of the planet is more tractable at these scales for climate applications. This work describes global simulations using variable-resolution static meshes with multiple dynamical cores that target the continental United States using developmental versions of the Community Earth System Model version 2 (CESM2). CESM2 is tested in idealized, aquaplanet and full physics configurations to evaluate variable mesh simulations against uniform high and uniform low resolution simulations at resolutions down to 15km. Different physical parameterization suites are also evaluated to gauge their sensitivity to resolution. Idealized variable-resolution mesh cases compare well to high resolution tests. More recent versions of the atmospheric physics, including cloud schemes for CESM2, are more stable with respect to changes in horizontal resolution. Most of the sensitivity is due to sensitivity to timestep and interactions between deep convection and large scale condensation, expected from the closure methods. The resulting full physics model produces a comparable climate to the global low resolution mesh and similar high frequency statistics in the high resolution region. Some biases are reduced (orographic precipitation in the western United States), but biases do not necessarily go away at high resolution (e.g. summertime JJA surface Temp). The simulations are able to reproduce uniform high resolution results, making them an effective tool for regional climate studies and are available in CESM2.

weather@home 2: validation of an improved global-regional climate modelling system

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.

2017-05-01

Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.

Separating sensitivity from exposure in assessing extinction risk from climate change.

PubMed

Dickinson, Maria G; Orme, C David L; Suttle, K Blake; Mace, Georgina M

2014-11-04

Predictive frameworks of climate change extinction risk generally focus on the magnitude of climate change a species is expected to experience and the potential for that species to track suitable climate. A species' risk of extinction from climate change will depend, in part, on the magnitude of climate change the species experiences, its exposure. However, exposure is only one component of risk. A species' risk of extinction will also depend on its intrinsic ability to tolerate changing climate, its sensitivity. We examine exposure and sensitivity individually for two example taxa, terrestrial amphibians and mammals. We examine how these factors are related among species and across regions and how explicit consideration of each component of risk may affect predictions of climate change impacts. We find that species' sensitivities to climate change are not congruent with their exposures. Many highly sensitive species face low exposure to climate change and many highly exposed species are relatively insensitive. Separating sensitivity from exposure reveals patterns in the causes and drivers of species' extinction risk that may not be evident solely from predictions of climate change. Our findings emphasise the importance of explicitly including sensitivity and exposure to climate change in assessments of species' extinction risk.

Separating sensitivity from exposure in assessing extinction risk from climate change

PubMed Central

Dickinson, Maria G.; Orme, C. David L.; Suttle, K. Blake; Mace, Georgina M.

2014-01-01

Predictive frameworks of climate change extinction risk generally focus on the magnitude of climate change a species is expected to experience and the potential for that species to track suitable climate. A species' risk of extinction from climate change will depend, in part, on the magnitude of climate change the species experiences, its exposure. However, exposure is only one component of risk. A species' risk of extinction will also depend on its intrinsic ability to tolerate changing climate, its sensitivity. We examine exposure and sensitivity individually for two example taxa, terrestrial amphibians and mammals. We examine how these factors are related among species and across regions and how explicit consideration of each component of risk may affect predictions of climate change impacts. We find that species' sensitivities to climate change are not congruent with their exposures. Many highly sensitive species face low exposure to climate change and many highly exposed species are relatively insensitive. Separating sensitivity from exposure reveals patterns in the causes and drivers of species' extinction risk that may not be evident solely from predictions of climate change. Our findings emphasise the importance of explicitly including sensitivity and exposure to climate change in assessments of species' extinction risk. PMID:25367429

Developing perturbations for Climate Change Impact Assessments

NASA Astrophysics Data System (ADS)

Hewitson, Bruce

Following the 2001 Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report [TAR; IPCC, 2001], and the paucity of climate change impact assessments from developing nations, there has been a significant growth in activities to redress this shortcoming. However, undertaking impact assessments (in relation to malaria, crop stress, regional water supply, etc.) is contingent on available climate-scale scenarios at time and space scales of relevance to the regional issues of importance. These scales are commonly far finer than even the native resolution of the Global Climate Models (GCMs) (the principal tools for climate change research), let alone the skillful resolution (scales of aggregation at which GCM observational error is acceptable for a given application) of GCMs.Consequently, there is a growing demand for regional-scale scenarios, which in turn are reliant on techniques to downscale from GCMs, such as empirical downscaling or nested Regional Climate Models (RCMs). These methods require significant skill, experiential knowledge, and computational infrastructure in order to derive credible regional-scale scenarios. In contrast, it is often the case that impact assessment researchers in developing nations have inadequate resources with limited access to scientists in the broader international scientific community who have the time and expertise to assist. However, where developing effective downscaled scenarios is problematic, it is possible that much useful information can still be obtained for impact assessments by examining the system sensitivity to largerscale climate perturbations. Consequently, one may argue that the early phase of assessing sensitivity and vulnerability should first be characterized by evaluation of the first-order impacts, rather than immediately addressing the finer, secondary factors that are dependant on scenarios derived through downscaling.

How does the sensitivity of climate affect stratospheric solar radiation management?

NASA Astrophysics Data System (ADS)

Ricke, K.; Rowlands, D. J.; Ingram, W.; Keith, D.; Morgan, M. G.

2011-12-01

If implementation of proposals to engineer the climate through solar radiation management (SRM) ever occurs, it is likely to be contingent upon climate sensitivity. Despite this, no modeling studies have examined how the effectiveness of SRM forcings differs between the typical Atmosphere-Ocean General Circulation Models (AOGCMs) with climate sensitivities close to the Coupled Model Intercomparison Project (CMIP) mean and ones with high climate sensitivities. Here, we use a perturbed physics ensemble modeling experiment to examine variations in the response of climate to SRM under different climate sensitivities. When SRM is used as a substitute for mitigation its ability to maintain the current climate state gets worse with increased climate sensitivity and with increased concentrations of greenhouse gases. However, our results also demonstrate that the potential of SRM to slow climate change, even at the regional level, grows with climate sensitivity. On average, SRM reduces regional rates of temperature change by more than 90 percent and rates of precipitation change by more than 50 percent in these higher sensitivity model configurations. To investigate how SRM might behave in models with high climate sensitivity that are also consistent with recent observed climate change we perform a "perturbed physics" ensemble (PPE) modelling experiment with the climateprediction.net (cpdn) version of the HadCM3L AOGCM. Like other perturbed physics climate modelling experiments, we simulate past and future climate scenarios using a wide range of model parameter combinations that both reproduce past climate within a specified level of accuracy and simulate future climates with a wide range of climate sensitivities. We chose 43 members ("model versions") from a subset of the 1,550 from the British Broadcasting Corporation (BBC) climateprediction.net project that have data that allow restarts. We use our results to explore how much assessments of SRM that use best-estimate models, and so near-median climate sensitivity, may be ignoring important contingencies associated with implementing SRM in reality. A primary motivation for studying SRM via the injection of aerosols in the stratosphere is to evaluate its potential effectiveness as "insurance" in the case of higher-than-expected climate response to global warming. We find that this is precisely when SRM appears to be least effective in returning regional climates to their baseline states and reducing regional rates of precipitation change. On the other hand, given the very high regional temperature anomalies associated with rising greenhouse gas concentrations in high sensitivity models, it is also where SRM is most effective in reducing rates of change relative to a no SRM alternative.

Beyond equilibrium climate sensitivity

NASA Astrophysics Data System (ADS)

Knutti, Reto; Rugenstein, Maria A. A.; Hegerl, Gabriele C.

2017-10-01

Equilibrium climate sensitivity characterizes the Earth's long-term global temperature response to increased atmospheric CO2 concentration. It has reached almost iconic status as the single number that describes how severe climate change will be. The consensus on the 'likely' range for climate sensitivity of 1.5 °C to 4.5 °C today is the same as given by Jule Charney in 1979, but now it is based on quantitative evidence from across the climate system and throughout climate history. The quest to constrain climate sensitivity has revealed important insights into the timescales of the climate system response, natural variability and limitations in observations and climate models, but also concerns about the simple concepts underlying climate sensitivity and radiative forcing, which opens avenues to better understand and constrain the climate response to forcing. Estimates of the transient climate response are better constrained by observed warming and are more relevant for predicting warming over the next decades. Newer metrics relating global warming directly to the total emitted CO2 show that in order to keep warming to within 2 °C, future CO2 emissions have to remain strongly limited, irrespective of climate sensitivity being at the high or low end.

BASINS and WEPP Climate Assessment Tools (CAT): Case ...

EPA Pesticide Factsheets

This draft report supports application of two recently developed water modeling tools, the BASINS and WEPP climate assessment tools. The report presents a series of short case studies designed to illustrate the capabilities of these tools for conducting scenario based assessments of the potential future effects of climate change on water resources. This report presents a series of short, illustrative case studies using the BASINS and WEPP climate assessment tools.

A method for screening climate change-sensitive infectious diseases.

PubMed

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

2015-01-14

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

A Method for Screening Climate Change-Sensitive Infectious Diseases

PubMed Central

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

2015-01-01

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

Inhomogeneous Forcing and Transient Climate Sensitivity

NASA Technical Reports Server (NTRS)

Shindell, Drew T.

2014-01-01

Understanding climate sensitivity is critical to projecting climate change in response to a given forcing scenario. Recent analyses have suggested that transient climate sensitivity is at the low end of the present model range taking into account the reduced warming rates during the past 10-15 years during which forcing has increased markedly. In contrast, comparisons of modelled feedback processes with observations indicate that the most realistic models have higher sensitivities. Here I analyse results from recent climate modelling intercomparison projects to demonstrate that transient climate sensitivity to historical aerosols and ozone is substantially greater than the transient climate sensitivity to CO2. This enhanced sensitivity is primarily caused by more of the forcing being located at Northern Hemisphere middle to high latitudes where it triggers more rapid land responses and stronger feedbacks. I find that accounting for this enhancement largely reconciles the two sets of results, and I conclude that the lowest end of the range of transient climate response to CO2 in present models and assessments (less than 1.3 C) is very unlikely.

Sensitivity of the projected hydroclimatic environment of the Delaware River basin to formulation of potential evapotranspiration

USGS Publications Warehouse

Williamson, Tanja N.; Nystrom, Elizabeth A.; Milly, Paul C.D.

2016-01-01

The Delaware River Basin (DRB) encompasses approximately 0.4 % of the area of the United States (U.S.), but supplies water to 5 % of the population. We studied three forested tributaries to quantify the potential climate-driven change in hydrologic budget for two 25-year time periods centered on 2030 and 2060, focusing on sensitivity to the method of estimating potential evapotranspiration (PET) change. Hydrology was simulated using the Water Availability Tool for Environmental Resources (Williamson et al. 2015). Climate-change scenarios for four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCMs) and two Representative Concentration Pathways (RCPs) were used to derive monthly change factors for temperature (T), precipitation (PPT), and PET according to the energy-based method of Priestley and Taylor (1972). Hydrologic simulations indicate a general increase in annual (especially winter) streamflow (Q) as early as 2030 across the DRB, with a larger increase by 2060. This increase in Q is the result of (1) higher winter PPT, which outweighs an annual actual evapotranspiration (AET) increase and (2) (for winter) a major shift away from storage of PPT as snow pack. However, when PET change is evaluated instead using the simpler T-based method of Hamon (1963), the increases in Q are small or even negative. In fact, the change of Q depends as much on PET method as on time period or RCP. This large sensitivity and associated uncertainty underscore the importance of exercising caution in the selection of a PET method for use in climate-change analyses.

BASINs and WEPP Climate Assessment Tools (CAT): Case ...

EPA Pesticide Factsheets

EPA announced the release of the final report, BASINs and WEPP Climate Assessment Tools (CAT): Case Study Guide to Potential Applications. This report supports application of two recently developed water modeling tools, the Better Assessment Science Integrating point & Non-point Sources (BASINS) and the Water Erosion Prediction Project Climate Assessment Tool (WEPPCAT). The report presents a series of short case studies designed to illustrate the capabilities of these tools for conducting scenario based assessments of the potential effects of climate change on streamflow and water quality. This report presents a series of short, illustrative case studies using the BASINS and WEPP climate assessment tools.

Assessing the Impact of Climate Change on Extreme Streamflow and Reservoir Operation for Nuuanu Watershed, Oahu, Hawaii

NASA Astrophysics Data System (ADS)

Leta, O. T.; El-Kadi, A. I.; Dulaiova, H.

2016-12-01

Extreme events, such as flooding and drought, are expected to occur at increased frequencies worldwide due to climate change influencing the water cycle. This is particularly critical for tropical islands where the local freshwater resources are very sensitive to climate. This study examined the impact of climate change on extreme streamflow, reservoir water volume and outflow for the Nuuanu watershed, using the Soil and Water Assessment Tool (SWAT) model. Based on the sensitive parameters screened by the Latin Hypercube-One-factor-At-a-Time (LH-OAT) method, SWAT was calibrated and validated to daily streamflow using the SWAT Calibration and Uncertainty Program (SWAT-CUP) at three streamflow gauging stations. Results showed that SWAT adequately reproduced the observed daily streamflow hydrographs at all stations. This was verified with Nash-Sutcliffe Efficiency that resulted in acceptable values of 0.58 to 0.88, whereby more than 90% of observations were bracketed within 95% model prediction uncertainty interval for both calibration and validation periods, signifying the potential applicability of SWAT for future prediction. The climate change impact on extreme flows, reservoir water volume and outflow was assessed under the Representative Concentration Pathways of 4.5 and 8.5 scenarios. We found wide changes in extreme peak and low flows ranging from -44% to 20% and -50% to -2%, respectively, compared to baseline. Consequently, the amount of water stored in Nuuanu reservoir will be decreased up to 27% while the corresponding outflow rates are expected to decrease up to 37% relative to the baseline. In addition, the stored water and extreme flows are highly sensitive to rainfall change when compared to temperature and solar radiation changes. It is concluded that the decrease in extreme low and peak flows can have serious consequences, such as flooding, drought, with detrimental effects on riparian ecological functioning. This study's results are expected to aid in reservoir operation as well as in identifying appropriate climate change adaptation strategies.

Climate Sensitivity, Sea Level, and Atmospheric Carbon Dioxide

NASA Technical Reports Server (NTRS)

Hansen, James; Sato, Makiko; Russell, Gary; Kharecha, Pushker

2013-01-01

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3+/-1deg C for a 4 W/sq m CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3-4deg C for a 4 W/sq m CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.

Phenological sensitivity to climate across taxa and trophic levels.

PubMed

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

2016-07-14

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

The Effects of Climate Sensitivity and Carbon Cycle Interactions on Mitigation Policy Stringency

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

Calvin, Katherine V.; Bond-Lamberty, Benjamin; Edmonds, James A.

2015-07-01

Climate sensitivity and climate-carbon cycle feedbacks interact to determine how global carbon and energy cycles will change in the future. While the science of these connections is well documented, their economic implications are not well understood. Here we examine the effect of climate change on the carbon cycle, the uncertainty in climate outcomes inherent in any given policy target, and the economic implications. We examine three policy scenarios—a no policy “Reference” (REF) scenario, and two policies that limit total radiative forcing—with four climate sensitivities using a coupled integrated assessment model. Like previous work, we find that, within a given scenario,more » there is a wide range of temperature change and sea level rise depending on the realized climate sensitivity. We expand on this previous work to show that temperature-related feedbacks on the carbon cycle result in more mitigation required as climate sensitivity increases. Thus, achieving a particular radiative forcing target becomes increasingly expensive as climate sensitivity increases.« less

Combining analytical frameworks to assess livelihood vulnerability to climate change and analyse adaptation options.

PubMed

Reed, M S; Podesta, G; Fazey, I; Geeson, N; Hessel, R; Hubacek, K; Letson, D; Nainggolan, D; Prell, C; Rickenbach, M G; Ritsema, C; Schwilch, G; Stringer, L C; Thomas, A D

2013-10-01

Experts working on behalf of international development organisations need better tools to assist land managers in developing countries maintain their livelihoods, as climate change puts pressure on the ecosystem services that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories and methods. This review therefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change, whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change.

Combining analytical frameworks to assess livelihood vulnerability to climate change and analyse adaptation options☆

PubMed Central

Reed, M.S.; Podesta, G.; Fazey, I.; Geeson, N.; Hessel, R.; Hubacek, K.; Letson, D.; Nainggolan, D.; Prell, C.; Rickenbach, M.G.; Ritsema, C.; Schwilch, G.; Stringer, L.C.; Thomas, A.D.

2013-01-01

Experts working on behalf of international development organisations need better tools to assist land managers in developing countries maintain their livelihoods, as climate change puts pressure on the ecosystem services that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories and methods. This review therefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change, whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change. PMID:25844020

Climate project screening tool: an aid for climate change adaptation

Treesearch

Toni Lyn Morelli; Sharon Yeh; Nikola M. Smith; Mary Beth Hennessy; Constance I. Millar

2012-01-01

To address the impacts of climate change, land managers need techniques for incorporating adaptation into ongoing or impending projects. We present a new tool, the Climate Project Screening Tool (CPST), for integrating climate change considerations into project planning as well as for developing concrete adaptation options for land managers. We designed CPST as part of...

Integrating Climate Change Adaptation into Public Health Practice: Using Adaptive Management to Increase Adaptive Capacity and Build Resilience

PubMed Central

McDowell, Julia Z.; Luber, George

2011-01-01

Background: Climate change is expected to have a range of health impacts, some of which are already apparent. Public health adaptation is imperative, but there has been little discussion of how to increase adaptive capacity and resilience in public health systems. Objectives: We explored possible explanations for the lack of work on adaptive capacity, outline climate–health challenges that may lie outside public health’s coping range, and consider changes in practice that could increase public health’s adaptive capacity. Methods: We conducted a substantive, interdisciplinary literature review focused on climate change adaptation in public health, social learning, and management of socioeconomic systems exhibiting dynamic complexity. Discussion: There are two competing views of how public health should engage climate change adaptation. Perspectives differ on whether climate change will primarily amplify existing hazards, requiring enhancement of existing public health functions, or present categorically distinct threats requiring innovative management strategies. In some contexts, distinctly climate-sensitive health threats may overwhelm public health’s adaptive capacity. Addressing these threats will require increased emphasis on institutional learning, innovative management strategies, and new and improved tools. Adaptive management, an iterative framework that embraces uncertainty, uses modeling, and integrates learning, may be a useful approach. We illustrate its application to extreme heat in an urban setting. Conclusions: Increasing public health capacity will be necessary for certain climate–health threats. Focusing efforts to increase adaptive capacity in specific areas, promoting institutional learning, embracing adaptive management, and developing tools to facilitate these processes are important priorities and can improve the resilience of local public health systems to climate change. PMID:21997387

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Evaluating financial risk management strategies under climate change for hydropower producers on the Great Lakes

NASA Astrophysics Data System (ADS)

Meyer, Eliot S.; Characklis, Gregory W.; Brown, Casey

2017-03-01

Hydropower on the Great Lakes makes up a substantial fraction of regional electricity generation capacity. Hydropower producers on the Niagara River (flowing between lakes Erie and Ontario) operate as run-of-river, and changing lake levels alter interlake flows reducing both generation and revenues. Index-based insurance contracts, wherein contract payouts are linked to lake levels, offer a tool for mitigating this risk. As a potentially useful tool, pricing of financial insurance is typically based on historical behavior of the index. However, uncertainty with respect to the impacts of climate change on lake level behavior and how this might translate to increased (or decreased) risk for those selling or buying the insurance remains unexplored. Portfolios of binary index-insurance contracts are developed for hydropower producers on the Niagara River, and their performance is evaluated under a range of climate scenarios. Climate Informed Decision Analysis is used to inform the sensitivity of these portfolios to potential shifts in long-term, climatological variations in water level behavior. Under historical conditions, hydropower producers can use portfolios costing 0.5% of mean revenues to increase their minimum revenue threshold by approximately 18%. However, a one standard deviation decrease in the 50 year mean water level potentially doubles the frequency with which these portfolios would underperform from the perspective of a potential insurer. Trade-offs between portfolio cost and the frequency of underperformance are investigated over a range of climate futures.

Development of a simplified urban water balance model (WABILA).

PubMed

Henrichs, M; Langner, J; Uhl, M

2016-01-01

During the last decade, water sensitive urban design (WSUD) has become more and more accepted. However, there is not any simple tool or option available to evaluate the influence of these measures on the local water balance. To counteract the impact of new settlements, planners focus on mitigating increases in runoff through installation of infiltration systems. This leads to an increasing non-natural groundwater recharge and decreased evapotranspiration. Simple software tools which evaluate or simulate the effect of WSUD on the local water balance are still needed. The authors developed a tool named WABILA (Wasserbilanz) that could support planners for optimal WSUD. WABILA is an easy-to-use planning tool that is based on simplified regression functions for established measures and land covers. Results show that WSUD has to be site-specific, based on climate conditions and the natural water balance.

A pseudoproxy assessment of data assimilation for reconstructing the atmosphere-ocean dynamics of hydroclimate extremes

NASA Astrophysics Data System (ADS)

Steiger, Nathan J.; Smerdon, Jason E.

2017-10-01

Because of the relatively brief observational record, the climate dynamics that drive multiyear to centennial hydroclimate variability are not adequately characterized and understood. Paleoclimate reconstructions based on data assimilation (DA) optimally fuse paleoclimate proxies with the dynamical constraints of climate models, thus providing a coherent dynamical picture of the past. DA is therefore an important new tool for elucidating the mechanisms of hydroclimate variability over the last several millennia. But DA has so far remained untested for global hydroclimate reconstructions. Here we explore whether or not DA can be used to skillfully reconstruct global hydroclimate variability along with the driving climate dynamics. Through a set of idealized pseudoproxy experiments, we find that an established DA reconstruction approach can in principle be used to reconstruct hydroclimate at both annual and seasonal timescales. We find that the skill of such reconstructions is generally highest near the proxy sites. This set of reconstruction experiments is specifically designed to estimate a realistic upper bound for the skill of this DA approach. Importantly, this experimental framework allows us to see where and for what variables the reconstruction approach may never achieve high skill. In particular for tree rings, we find that hydroclimate reconstructions depend critically on moisture-sensitive trees, while temperature reconstructions depend critically on temperature-sensitive trees. Real-world DA-based reconstructions will therefore likely require a spatial mixture of temperature- and moisture-sensitive trees to reconstruct both temperature and hydroclimate variables. Additionally, we illustrate how DA can be used to elucidate the dynamical mechanisms of drought with two examples: tropical drivers of multiyear droughts in the North American Southwest and in equatorial East Africa. This work thus provides a foundation for future DA-based hydroclimate reconstructions using real-proxy networks while also highlighting the utility of this important tool for hydroclimate research.

Background sampling and transferability of species distribution model ensembles under climate change

NASA Astrophysics Data System (ADS)

Iturbide, Maialen; Bedia, Joaquín; Gutiérrez, José Manuel

2018-07-01

Species Distribution Models (SDMs) constitute an important tool to assist decision-making in environmental conservation and planning. A popular application of these models is the projection of species distributions under climate change conditions. Yet there are still a range of methodological SDM factors which limit the transferability of these models, contributing significantly to the overall uncertainty of the resulting projections. An important source of uncertainty often neglected in climate change studies comes from the use of background data (a.k.a. pseudo-absences) for model calibration. Here, we study the sensitivity to pseudo-absence sampling as a determinant factor for SDM stability and transferability under climate change conditions, focusing on European wide projections of Quercus robur as an illustrative case study. We explore the uncertainty in future projections derived from ten pseudo-absence realizations and three popular SDMs (GLM, Random Forest and MARS). The contribution of the pseudo-absence realization to the uncertainty was higher in peripheral regions and clearly differed among the tested SDMs in the whole study domain, being MARS the most sensitive - with projections differing up to a 40% for different realizations - and GLM the most stable. As a result we conclude that parsimonious SDMs are preferable in this context, avoiding complex methods (such as MARS) which may exhibit poor model transferability. Accounting for this new source of SDM-dependent uncertainty is crucial when forming multi-model ensembles to undertake climate change projections.

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.

Climate Sensitivity in the Anthropocene

NASA Technical Reports Server (NTRS)

Previdi, M.; Liepert, B. G.; Peteet, Dorothy M.; Hansen, J.; Beerling, D. J.; Broccoli, A. J.; Frolking, S.; Galloway, J. N.; Heimann, M.; LeQuere, C.;

Time-dependent climate sensitivity and the legacy of anthropogenic greenhouse gas emissions

PubMed Central

Zeebe, Richard E.

2013-01-01

Climate sensitivity measures the response of Earth’s surface temperature to changes in forcing. The response depends on various climate processes that feed back on the initial forcing on different timescales. Understanding climate sensitivity is fundamental to reconstructing Earth’s climatic history as well as predicting future climate change. On timescales shorter than centuries, only fast climate feedbacks including water vapor, lapse rate, clouds, and snow/sea ice albedo are usually considered. However, on timescales longer than millennia, the generally higher Earth system sensitivity becomes relevant, including changes in ice sheets, vegetation, ocean circulation, biogeochemical cycling, etc. Here, I introduce the time-dependent climate sensitivity, which unifies fast-feedback and Earth system sensitivity. I show that warming projections, which include a time-dependent climate sensitivity, exhibit an enhanced feedback between surface warming and ocean CO2 solubility, which in turn leads to higher atmospheric CO2 levels and further warming. Compared with earlier studies, my results predict a much longer lifetime of human-induced future warming (23,000–165,000 y), which increases the likelihood of large ice sheet melting and major sea level rise. The main point regarding the legacy of anthropogenic greenhouse gas emissions is that, even if the fast-feedback sensitivity is no more than 3 K per CO2 doubling, there will likely be additional long-term warming from slow climate feedbacks. Time-dependent climate sensitivity also helps explaining intense and prolonged warming in response to massive carbon release as documented for past events such as the Paleocene–Eocene Thermal Maximum. PMID:23918402

Time-dependent climate sensitivity and the legacy of anthropogenic greenhouse gas emissions.

PubMed

Zeebe, Richard E

2013-08-20

Climate sensitivity measures the response of Earth's surface temperature to changes in forcing. The response depends on various climate processes that feed back on the initial forcing on different timescales. Understanding climate sensitivity is fundamental to reconstructing Earth's climatic history as well as predicting future climate change. On timescales shorter than centuries, only fast climate feedbacks including water vapor, lapse rate, clouds, and snow/sea ice albedo are usually considered. However, on timescales longer than millennia, the generally higher Earth system sensitivity becomes relevant, including changes in ice sheets, vegetation, ocean circulation, biogeochemical cycling, etc. Here, I introduce the time-dependent climate sensitivity, which unifies fast-feedback and Earth system sensitivity. I show that warming projections, which include a time-dependent climate sensitivity, exhibit an enhanced feedback between surface warming and ocean CO2 solubility, which in turn leads to higher atmospheric CO2 levels and further warming. Compared with earlier studies, my results predict a much longer lifetime of human-induced future warming (23,000-165,000 y), which increases the likelihood of large ice sheet melting and major sea level rise. The main point regarding the legacy of anthropogenic greenhouse gas emissions is that, even if the fast-feedback sensitivity is no more than 3 K per CO2 doubling, there will likely be additional long-term warming from slow climate feedbacks. Time-dependent climate sensitivity also helps explaining intense and prolonged warming in response to massive carbon release as documented for past events such as the Paleocene-Eocene Thermal Maximum.

Climate sensitivity, sea level and atmospheric carbon dioxide

PubMed Central

Hansen, James; Sato, Makiko; Russell, Gary; Kharecha, Pushker

2013-01-01

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3±1°C for a 4 W m−2 CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3–4°C for a 4 W m−2 CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change. PMID:24043864

Climate sensitivity, sea level and atmospheric carbon dioxide.

PubMed

Hansen, James; Sato, Makiko; Russell, Gary; Kharecha, Pushker

2013-10-28

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3±1(°)C for a 4 W m(-2) CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3-4(°)C for a 4 W m(-2) CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.

Sensitivity of river discharge to the quality of external meteorological forcings

NASA Astrophysics Data System (ADS)

Materia, S.; Dirmeyer, P.; Guo, Z.; Alessandri, A.; Navarra, A.

2009-09-01

Large-scale river routing models are essential tools to close the hydrological cycle in fully coupled climate models. Moreover, the availability of a realistic routing scheme is a powerful instrument to assess the validity of land surface parameterization, which has been recognized to be a crucial component of the global climate. This study is dedicated to assess the sensitivity of river discharge to the variation of external meteorological forcing. The Land Surface Scheme created at the Center for Ocean, Land and Atmosphere Studies (COLA), the SSiB model, was constrained with different meteorological fields. The resulting surface and sub-surface runoffs were used as forcing data for the HD River Routing Scheme. As expected, river flow is mainly sensitive to precipitation variability, but changes in radiative forcing affect discharge as well, presumably due to the interaction with evaporation. Also, this analysis provided an estimate of the sensitivity of river discharge to precipitation variations. A few areas, like Central and Eastern Asia, Southern and Central Europe and the majority of the US, show a magnified response of river discharge to a given percentage change in precipitation. Hence, an amplified effect of droughts following the reduction in precipitation, as it is indicated by many climate scenarios, may occur in places such as the Mediterranean. Conversely, increasing summer precipitation foreseen in Southern and Eastern Asia may amplify floods in one the poorest and most populated regions in the world. These results can be used for the definition and assessment of new strategies for land use and water management in the near future.

State-dependent climate sensitivity in past warm climates and its implications for future climate projections.

PubMed

Caballero, Rodrigo; Huber, Matthew

2013-08-27

Projections of future climate depend critically on refined estimates of climate sensitivity. Recent progress in temperature proxies dramatically increases the magnitude of warming reconstructed from early Paleogene greenhouse climates and demands a close examination of the forcing and feedback mechanisms that maintained this warmth and the broad dynamic range that these paleoclimate records attest to. Here, we show that several complementary resolutions to these questions are possible in the context of model simulations using modern and early Paleogene configurations. We find that (i) changes in boundary conditions representative of slow "Earth system" feedbacks play an important role in maintaining elevated early Paleogene temperatures, (ii) radiative forcing by carbon dioxide deviates significantly from pure logarithmic behavior at concentrations relevant for simulation of the early Paleogene, and (iii) fast or "Charney" climate sensitivity in this model increases sharply as the climate warms. Thus, increased forcing and increased slow and fast sensitivity can all play a substantial role in maintaining early Paleogene warmth. This poses an equifinality problem: The same climate can be maintained by a different mix of these ingredients; however, at present, the mix cannot be constrained directly from climate proxy data. The implications of strongly state-dependent fast sensitivity reach far beyond the early Paleogene. The study of past warm climates may not narrow uncertainty in future climate projections in coming centuries because fast climate sensitivity may itself be state-dependent, but proxies and models are both consistent with significant increases in fast sensitivity with increasing temperature.

Climate Action Planning Tool | NREL

Science.gov Websites

NREL's Climate Action Planning Tool provides a quick, basic estimate of how various technology options can contribute to an overall climate action plan for your research campus. Use the tool to

Sensitivity of agricultural runoff loads to rising levels of CO2 and climate change in the San Joaquin Valley watershed of California.

PubMed

Ficklin, Darren L; Luo, Yuzhou; Luedeling, Eike; Gatzke, Sarah E; Zhang, Minghua

2010-01-01

The Soil and Water Assessment Tool (SWAT) was used to assess the impact of climate change on sediment, nitrate, phosphorus and pesticide (diazinon and chlorpyrifos) runoff in the San Joaquin watershed in California. This study used modeling techniques that include variations of CO(2), temperature, and precipitation to quantify these responses. Precipitation had a greater impact on agricultural runoff compared to changes in either CO(2) concentration or temperature. Increase of precipitation by +/-10% and +/-20% generally changed agricultural runoff proportionally. Solely increasing CO(2) concentration resulted in an increase in nitrate, phosphorus, and chlorpyrifos yield by 4.2, 7.8, and 6.4%, respectively, and a decrease in sediment and diazinon yield by 6.3 and 5.3%, respectively, in comparison to the present-day reference scenario. Only increasing temperature reduced yields of all agricultural runoff components. The results suggest that agricultural runoff in the San Joaquin watershed is sensitive to precipitation, temperature, and CO(2) concentration changes.

Using sensitive montane amphibian species as indicators of hydroclimatic change in meadow ecosystems of the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Peek, R.; Viers, J.; Yarnell, S. M.

2012-12-01

Climate change can affect sensitive species and ecosystems in many ways, yet sparse data and the inability to apply various climate models at functional spatial scales often prevents relevant research from being utilized in conservation management plans. Climate change has been linked to declines and disturbances in a multitude of species and habitats, and in California, one of the greatest climatic concerns is the predicted reduction in mountain snowpack and associated snowmelt. These decreases in natural storage of water as snow in mountain regions can affect the timing and variability of critical snowmelt runoff periods—important seasonal signals that species in montane ecosystems have evolved life history strategies around—leading to greater intra-annual variability and diminished summer and fall stream flows. Although many species distribution models exist, few provide ways to integrate continually updated and revised Global Climate Models (GCMs), hydrologic data unique to a watershed, and ecological responses that can be incorporated into conservation strategies. This study documents a novel and applicable method of combining boosted regression tree (BRT) modeling and species distributions with hydroclimatic data as a potential management tool for conservation. Boosted regression trees are suitable for ecological distribution modeling because they can reduce both bias and variance, as well as handle sharp discontinuities common in sparsely sampled species or large study areas. This approach was used to quantify the effects of hydroclimatic changes on the distribution of key riparian-associated amphibian species in montane meadow habitats in the Sierra Nevada at the sub-watershed level. Based on modeling using current species range maps in conjunction with three climate scenarios (near, mid, and far), extreme range contractions were observed for all sensitive species (southern long-toed salamander, mountain yellow-legged frog, Yosemite toad) by the year 2100. Among many environmental and hydroclimatic variables used in the model, snowpack and snowmelt (runoff) variables were consistently among the most informative in predicting species occupancy. Few sub-watersheds contained greater than 50% probability of species occupancy throughout the modeled time period; however several core areas were identified as more resilient to climate change for each species. There was overlap among species in areas that were predicted to remain hydroclimatically stable, particularly in sub-watersheds that contain high meadow density. Quantifying these areas of habitat stability, or "resiliency", may ultimately be the most useful outcome of BRT modeling, with the flexibility to utilize multiple GCMs at varying scales. Ultimately managers need to consider both short term and long term conservation goals by identifying and protecting suitable habitat areas most resilient to climate change to give multiple species the best chance to persist. This approach provides a unique tool for conservation management which can be easily applied to a variety of data and species, and provides useful knowledge at both near and long term time scales.

Identifying Decision Support Tools to Bridge Climate and Agricultural Needs in the Midwest

NASA Astrophysics Data System (ADS)

Hall, B. L.; Kluck, D. R.; Hatfield, J.; Black, C.; Kellner, O.; Woloszyn, M.; Timlin, M. S.

2015-12-01

Climate monitoring tools designed to help stakeholders reduce climate impacts have been developed for the primary Midwest field crops of corn and soybean. However, the region also produces vital livestock and specialty crops that currently lack similar climate monitoring and projection tools. In autumn 2015, the National Oceanic and Atmospheric Administration's (NOAA's) National Integrated Drought Information System (NIDIS) and Midwestern Regional Climate Center (MRCC) partnered with the US Department of Agriculture's Midwest Climate Hub to convene agriculture stakeholders, climate scientists, and climate service specialists to discuss climate impacts and needs for these two, often under-represented, sectors. The goals of this workshop were to (1) identify climate impacts that specialty crops and livestock producers face within the Midwest, (2) develop an understanding of the types of climate and weather information and tools currently available in the Midwest that could be applied to decision making, and (3) discover the types of climate and weather information and tools needed to address concerns of specialty crop and livestock commodities across the Midwest. This presentation will discuss the workshop and provide highlights of the outcomes that developed into strategic plans for the future to better serve these sectors of agriculture in the Midwest.

Climate matching as a tool for predicting potential North American spread of Brown Treesnakes

USGS Publications Warehouse

Rodda, Gordon H.; Reed, Robert N.; Jarnevich, Catherine S.; Witmer, G.W.; Pitt, W. C.; Fagerstone, K.A.

2007-01-01

Climate matching identifies extralimital destinations that could be colonized by a potential invasive species on the basis of similarity to climates found in the species’ native range. Climate is a proxy for the factors that determine whether a population will reproduce enough to offset mortality. Previous climate matching models (e.g., Genetic Algorithm for Rule-set Prediction [GARP]) for brown treesnakes (Boiga irregularis) were unsatisfactory, perhaps because the models failed to allow different combinations of climate attributes to influence a species’ range limits in different parts of the range. Therefore, we explored the climate space described by bivariate parameters of native range temperature and rainfall, allowing up to two months of aestivation in the warmer portions of the range, or four months of hibernation in temperate climes. We found colonization area to be minimally sensitive to assumptions regarding hibernation temperature thresholds. Although brown treesnakes appear to be limited by dry weather in the interior of Australia, aridity rarely limits potential distribution in most of the world. Potential colonization area in North America is limited primarily by cold. Climatically suitable portions of the United States (US) mainland include the Central Valley of California, mesic patches in the Southwest, and the southeastern coastal plain from Texas to Virginia.

CCDST: A free Canadian climate data scraping tool

NASA Astrophysics Data System (ADS)

Bonifacio, Charmaine; Barchyn, Thomas E.; Hugenholtz, Chris H.; Kienzle, Stefan W.

2015-02-01

In this paper we present a new software tool that automatically fetches, downloads and consolidates climate data from a Web database where the data are contained on multiple Web pages. The tool is called the Canadian Climate Data Scraping Tool (CCDST) and was developed to enhance access and simplify analysis of climate data from Canada's National Climate Data and Information Archive (NCDIA). The CCDST deconstructs a URL for a particular climate station in the NCDIA and then iteratively modifies the date parameters to download large volumes of data, remove individual file headers, and merge data files into one output file. This automated sequence enhances access to climate data by substantially reducing the time needed to manually download data from multiple Web pages. To this end, we present a case study of the temporal dynamics of blowing snow events that resulted in ~3.1 weeks time savings. Without the CCDST, the time involved in manually downloading climate data limits access and restrains researchers and students from exploring climate trends. The tool is coded as a Microsoft Excel macro and is available to researchers and students for free. The main concept and structure of the tool can be modified for other Web databases hosting geophysical data.

Research on Climate and Dengue in Malaysia: A Systematic Review.

PubMed

Hii, Yien Ling; Zaki, Rafdzah Ahmad; Aghamohammadi, Nasrin; Rocklöv, Joacim

2016-03-01

Dengue is a climate-sensitive infectious disease. Climate-based dengue early warning may be a simple, low-cost, and effective tool for enhancing surveillance and control. Scientific studies on climate and dengue in local context form the basis for advancing the development of a climate-based early warning system. This study aims to review the current status of scientific studies in climate and dengue and the prospect or challenges of such research on a climate-based dengue early warning system in a dengue-endemic country, taking Malaysia as a case study. We reviewed the relationship between climate and dengue derived from statistical modeling, laboratory tests, and field studies. We searched electronic databases including PubMed, Scopus, EBSCO (MEDLINE), Web of Science, and the World Health Organization publications, and assessed climate factors and their influence on dengue cases, mosquitoes, and virus and recent development in the field of climate and dengue. Few studies in Malaysia have emphasized the relationship between climate and dengue. Climatic factors such as temperature, rainfall, and humidity are associated with dengue; however, these relationships were not consistent. Climate change projections for Malaysia show a mounting risk for dengue in the future. Scientific studies on climate and dengue enhance dengue surveillance in the long run. It is essential for institutions in Malaysia to promote research on climate and vector-borne diseases to advance the development of climate-based early warning systems. Together, effective strategies that improve existing research capacity, maximize the use of limited resources, and promote local-international partnership are crucial for sustaining research on climate and health.

State-dependent climate sensitivity in past warm climates and its implications for future climate projections

PubMed Central

Caballero, Rodrigo; Huber, Matthew

2013-01-01

Projections of future climate depend critically on refined estimates of climate sensitivity. Recent progress in temperature proxies dramatically increases the magnitude of warming reconstructed from early Paleogene greenhouse climates and demands a close examination of the forcing and feedback mechanisms that maintained this warmth and the broad dynamic range that these paleoclimate records attest to. Here, we show that several complementary resolutions to these questions are possible in the context of model simulations using modern and early Paleogene configurations. We find that (i) changes in boundary conditions representative of slow “Earth system” feedbacks play an important role in maintaining elevated early Paleogene temperatures, (ii) radiative forcing by carbon dioxide deviates significantly from pure logarithmic behavior at concentrations relevant for simulation of the early Paleogene, and (iii) fast or “Charney” climate sensitivity in this model increases sharply as the climate warms. Thus, increased forcing and increased slow and fast sensitivity can all play a substantial role in maintaining early Paleogene warmth. This poses an equifinality problem: The same climate can be maintained by a different mix of these ingredients; however, at present, the mix cannot be constrained directly from climate proxy data. The implications of strongly state-dependent fast sensitivity reach far beyond the early Paleogene. The study of past warm climates may not narrow uncertainty in future climate projections in coming centuries because fast climate sensitivity may itself be state-dependent, but proxies and models are both consistent with significant increases in fast sensitivity with increasing temperature. PMID:23918397

Sensitivity of the Antarctic surface mass balance to oceanic perturbations

NASA Astrophysics Data System (ADS)

Kittel, C.; Amory, C.; Agosta, C.; Fettweis, X.

2017-12-01

Regional climate models (RCMs) are suitable numerical tools to study the surface mass balance (SMB) of the wide polar ice sheets due to their high spatial resolution and polar-adapted physics. Nonetheless, RCMs are driven at their boundaries and over the ocean by reanalysis or global climate model (GCM) products and are thus influenced by potential biases in these large-scale fields. These biases can be significant for both the atmosphere and the sea surface conditions (i.e. sea ice concentration and sea surface temperature). With the RCM MAR, a set of sensitivity experiments has been realized to assess the direct response of the SMB of the Antarctic ice sheet to oceanic perturbations. MAR is forced by ERA-Interim and anomalies based on mean GCM biases are introduced in sea surface conditions. Results show significant increases (decreases) of liquid and solid precipitation due to biases related to warm (cold) oceans. As precipitation is mainly caused by low-pressure systems that intrude into the continent and do not penetrate far inland, coastal areas are more sensitive than inland regions. Furthermore, warm ocean representative biases lead to anomalies as large as anomalies simulated by other RCMs or GCMs for the end of the 21st century.

An integrated land change model for projecting future climate and land change scenarios

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Lamsal, Aashis; Liu, Zhihua; Hawbaker, Todd J.

2013-01-01

Climate change will have myriad effects on ecosystems worldwide, and natural and anthropogenic disturbances will be key drivers of these dynamics. In addition to climatic effects, continual expansion of human settlement into fire-prone forests will alter fire regimes, increase human vulnerability, and constrain future forest management options. There is a need for modeling tools to support the simulation and assessment of new management strategies over large regions in the context of changing climate, shifting development patterns, and an expanding wildland-urban interface. To address this need, we developed a prototype land change simulator that combines human-driven land use change (derived from the FORE-SCE model) with natural disturbances and vegetation dynamics (derived from the LADS model) and incorporates novel feedbacks between human land use and disturbance regimes. The prototype model was implemented in a test region encompassing the Denver metropolitan area along with its surrounding forested and agricultural landscapes. Initial results document the feasibility of integrated land change modeling at a regional scale but also highlighted conceptual and technical challenges for this type of model integration. Ongoing development will focus on improving climate sensitivities and modeling constraints imposed by climate change and human population growth on forest management activities.

Magnetic Minerals in Soils and Paleosols as Recorders of Paleoclimate

NASA Astrophysics Data System (ADS)

Maxbauer, Daniel P.

It is a fundamental challenge for geologists to create quantitative estimates of rainfall and temperature in past climates. Yet, records of past climates are integral for understanding the complexities of earth system dynamics. The research presented in this dissertation begins to establish a framework for reconstructing paleoclimates using the magnetic properties of fossilized soils. Magnetic minerals are ubiquitous in soils, and their composition, grain size, and concentration is often directly related to the ambient climatic conditions that were present during soil formation. Using rock magnetic methods, it is possible to sensitively characterize the magnetic mineral assemblages in natural materials - including soils and paleosols. The fundamentals of rock magnetism and many of the common methods used in rock magnetic applications are presented in chapter 2 and chapter 3, respectively. Chapter 4 reviews the physical, chemical, and biological factors that affect magnetic mineral assemblages in soils, the magnetic methods we use to characterize them, and the known relationships between magnetic minerals in soils and climate. A critical component to developing replicable tools for reconstructing paleoclimate is developing analytical and statistical tools that are accessible to the greater community. Chapter 5 introduces a new model, MAX UnMix, that was developed as an open-source, online tool for rock magnetic data processing that is designed to be user-friendly and accessible. Two case studies, on both fossil (Chapter 7) and modern (Chapter 6) soils, are presented and discuss many issues related to applying magnetic paleoprecipitation proxies in deep time. Chapter 7 discusses difficulties in disentangling the effects of pedogenesis, diagenesis, and recent surficial weathering in Paleocene-Eocene ( 56-55 Ma) paleosols. Chapter 6 explores the relative influence of soil forming factors (vegetation vs. climate) on controlling the pedogenic formation of magnetic minerals in soils developing across the forest-to-prairie ecotone in NW Minnesota. The body of research presented in this dissertation provides many challenges to future workers, while at the same time highlighting that rock magnetism should be a useful tool for researchers interested in deep time paleoclimates moving forward.

A New Climate Adjustment Tool: An update to EPA’s Storm Water Management Model

EPA Science Inventory

The US EPA’s newest tool, the Stormwater Management Model (SWMM) – Climate Adjustment Tool (CAT) is meant to help municipal stormwater utilities better address potential climate change impacts affecting their operations.

Framework for mapping the drivers of coastal vulnerability and spatial decision making for climate-change adaptation: A case study from Maharashtra, India.

PubMed

Krishnan, Pandian; Ananthan, Pachampalayam Shanmugam; Purvaja, Ramachandran; Joyson Joe Jeevamani, Jeyapaul; Amali Infantina, John; Srinivasa Rao, Cherukumalli; Anand, Arur; Mahendra, Ranganalli Somashekharappa; Sekar, Iyyapa; Kareemulla, Kalakada; Biswas, Amit; Kalpana Sastry, Regulagedda; Ramesh, Ramachandran

2018-05-31

The impacts of climate change are of particular concern to the coastal region of tropical countries like India, which are exposed to cyclones, floods, tsunami, seawater intrusion, etc. Climate-change adaptation presupposes comprehensive assessment of vulnerability status. Studies so far relied either on remote sensing-based spatial mapping of physical vulnerability or on certain socio-economic aspects with limited scope for upscaling or replication. The current study is an attempt to develop a holistic and robust framework to assess the vulnerability of coastal India at different levels. We propose and estimate cumulative vulnerability index (CVI) as a function of exposure, sensitivity and adaptive capacity, at the village level, using nationally comparable and credible datasets. The exposure index (EI) was determined at the village level by decomposing the spatial multi-hazard maps, while sensitivity (SI) and adaptive capacity indices (ACI) were estimated using 23 indicators, covering social and economic aspects. The indicators were identified through the literature review, expert consultations, opinion survey, and were further validated through statistical tests. The socio-economic vulnerability index (SEVI) was constructed as a function of sensitivity and adaptive capacity for planning grassroot-level interventions and adaptation strategies. The framework was piloted in Sindhudurg, a coastal district in Maharashtra, India. It comprises 317 villages, spread across three taluks viz., Devgad, Malvan and Vengurla. The villages in Sindhudurg were ranked based on this multi-criteria approach. Based on CVI values, 92 villages (30%) in Sindhudurg were identified as highly vulnerable. We propose a decision tool for identifying villages vulnerable to changing climate, based on their level of sensitivity and adaptive capacity in a two-dimensional matrix, thus aiding in planning location-specific interventions. Here, vulnerability indicators are classified and designated as 'drivers' (indicators with significantly high values and intervention priority) and 'buffers' (indicators with low-to-moderate values) at the village level. The framework provides for aggregation or decomposition of CVI and other sub-indices, in order to plan spatial contingency plans and enable swift action for climate adaptation.

Climate Local Information over the Mediterranean to Respond User Needs

NASA Astrophysics Data System (ADS)

Ruti, P.

2012-12-01

CLIM-RUN aims at developing a protocol for applying new methodologies and improved modeling and downscaling tools for the provision of adequate climate information at regional to local scale that is relevant to and usable by different sectors of society (policymakers, industry, cities, etc.). Differently from current approaches, CLIM-RUN will develop a bottom-up protocol directly involving stakeholders early in the process with the aim of identifying well defined needs at the regional to local scale. The improved modeling and downscaling tools will then be used to optimally respond to these specific needs. The protocol is assessed by application to relevant case studies involving interdependent sectors, primarily tourism and energy, and natural hazards (wild fires) for representative target areas (mountainous regions, coastal areas, islands). The region of interest for the project is the Greater Mediterranean area, which is particularly important for two reasons. First, the Mediterranean is a recognized climate change hot-spot, i.e. a region particularly sensitive and vulnerable to global warming. Second, while a number of countries in Central and Northern Europe have already in place well developed climate service networks (e.g. the United Kingdom and Germany), no such network is available in the Mediterranean. CLIM-RUN is thus also intended to provide the seed for the formation of a Mediterranean basin-side climate service network which would eventually converge into a pan-European network. The general time horizon of interest for the project is the future period 2010-2050, a time horizon that encompasses the contributions of both inter-decadal variability and greenhouse-forced climate change. In particular, this time horizon places CLIM-RUN within the context of a new emerging area of research, that of decadal prediction, which will provide a strong potential for novel research.

Chinese insurance agents in "bad barrels": a multilevel analysis of the relationship between ethical leadership, ethical climate and business ethical sensitivity.

PubMed

Zhang, Na; Zhang, Jian

2016-01-01

The moral hazards and poor public image of the insurance industry, arising from insurance agents' unethical behavior, affect both the normal operation of an insurance company and decrease applicants' confidence in the company. Contrarily, these scandals may demonstrate that the organizations were "bad barrels" in which insurance agents' unethical decisions were supported or encouraged by the organization's leadership or climate. The present study brings two organization-level factors (ethical leadership and ethical climate) together and explores the role of ethical climate on the relationship between the ethical leadership and business ethical sensitivity of Chinese insurance agents. Through the multilevel analysis of 502 insurance agents from 56 organizations, it is found that organizational ethical leadership is positively related to the organizational ethical climate; organizational ethical climate is positively related to business ethical sensitivity, and organizational ethical climate fully mediates the relationship between organizational ethical leadership and business ethical sensitivity. Organizational ethical climate plays a completely mediating role in the relationship between organizational ethical leadership and business ethical sensitivity. The integrated model of ethical leadership, ethical climate and business ethical sensitivity makes several contributions to ethics theory, research and management.

Time variation of effective climate sensitivity in GCMs

NASA Astrophysics Data System (ADS)

Williams, K. D.; Ingram, W. J.; Gregory, J. M.

2009-04-01

Effective climate sensitivity is often assumed to be constant (if uncertain), but some previous studies of General Circulation Model (GCM) simulations have found it varying as the simulation progresses. This complicates the fitting of simple models to such simulations, as well as having implications for the estimation of climate sensitivity from observations. This study examines the evolution of the feedbacks determining the climate sensitivity in GCMs submitted to the Coupled Model Intercomparison Project. Apparent centennial-timescale variations of effective climate sensitivity during stabilisation to a forcing can be considered an artefact of using conventional forcings which only allow for instantaneous effects and stratospheric adjustment. If the forcing is adjusted for processes occurring on timescales which are short compared to the climate stabilisation timescale then there is little centennial timescale evolution of effective climate sensitivity in any of the GCMs. We suggest that much of the apparent variation in effective climate sensitivity identified in previous studies is actually due to the comparatively fast forcing adjustment. Persistent differences are found in the strength of the feedbacks between the coupled atmosphere - ocean (AO) versions and their atmosphere - mixed-layer ocean (AML) counterparts, (the latter are often assumed to give the equilibrium climate sensitivity of the AOGCM). The AML model can typically only estimate the equilibrium climate sensitivity of the parallel AO version to within about 0.5K. The adjustment to the forcing to account for comparatively fast processes varies in magnitude and sign between GCMs, as well as differing between AO and AML versions of the same model. There is evidence from one AOGCM that the forcing adjustment may take a couple of decades, with implications for observationally based estimates of equilibrium climate sensitivity. We suggest that at least some of the spread in 21st century global temperature predictions between GCMs is due to differing adjustment processes, hence work to understand these differences should be a priority.

Detecting extinction risk from climate change by IUCN Red List criteria.

PubMed

Keith, David A; Mahony, Michael; Hines, Harry; Elith, Jane; Regan, Tracey J; Baumgartner, John B; Hunter, David; Heard, Geoffrey W; Mitchell, Nicola J; Parris, Kirsten M; Penman, Trent; Scheele, Ben; Simpson, Christopher C; Tingley, Reid; Tracy, Christopher R; West, Matt; Akçakaya, H Resit

2014-06-01

Anthropogenic climate change is a key threat to global biodiversity. To inform strategic actions aimed at conserving biodiversity as climate changes, conservation planners need early warning of the risks faced by different species. The IUCN Red List criteria for threatened species are widely acknowledged as useful risk assessment tools for informing conservation under constraints imposed by limited data. However, doubts have been expressed about the ability of the criteria to detect risks imposed by potentially slow-acting threats such as climate change, particularly because criteria addressing rates of population decline are assessed over time scales as short as 10 years. We used spatially explicit stochastic population models and dynamic species distribution models projected to future climates to determine how long before extinction a species would become eligible for listing as threatened based on the IUCN Red List criteria. We focused on a short-lived frog species (Assa darlingtoni) chosen specifically to represent potential weaknesses in the criteria to allow detailed consideration of the analytical issues and to develop an approach for wider application. The criteria were more sensitive to climate change than previously anticipated; lead times between initial listing in a threatened category and predicted extinction varied from 40 to 80 years, depending on data availability. We attributed this sensitivity primarily to the ensemble properties of the criteria that assess contrasting symptoms of extinction risk. Nevertheless, we recommend the robustness of the criteria warrants further investigation across species with contrasting life histories and patterns of decline. The adequacy of these lead times for early warning depends on practicalities of environmental policy and management, bureaucratic or political inertia, and the anticipated species response times to management actions. © 2014 Society for Conservation Biology.

Web Tools Streamline Climate Preparedness and Resilience Planning and Implementation for Water Resources Infrastructure

NASA Astrophysics Data System (ADS)

White, K. D.; Friedman, D.; Schechter, J.; Foley, P.; Mueller, C.; Baker, B.; Huber, M.; Veatch, W.

2016-12-01

Observed and projected impacts of climate change are pronounced on the hydrologic cycle because of the sensitivity of hydroclimatic variables to changes in temperature. Well-documented climate change impacts to the hydrologic cycle include increases in extreme heat conditions, coastal flooding, heavy precipitation, and drought frequency and magnitude, all of which can combine in surprising ways to pose regionally varying threats to public health and safety, ecosystem functions, and the economy. Climate preparedness and resilience activities are therefore necessary for water infrastructure which provides flood risk reduction, navigation, water supply, ecosystem restoration, and hydropower services. Because this water infrastructure entails long lifetimes, up to or beyond 100 years, and significant public investment, accurate and timely information about climate impacts over both the near-and far-term is required to plan and implement climate preparedness and resilience measures. Engineers are natural translators of science into actionable information to support this type of decision-making, because they understand both the important physical processes and the processes, laws, standards, and criteria required for the planning and design of public infrastructure. Though engineers are capable of the data management activities needed to ingest, transform, and prepare climate information for use in these decisions, the US Army Corps of Engineers (USACE) has chosen to emphasize analysis of information over data management. In doing so, the USACE is developing and using web tools with visualization capabilities to streamline climate preparedness and resilience planning and implementation while ensuring repeatable analytical results nationally. Examples discussed here include calculation of sea level change, including a comparison of mean sea level and other tidal statistics against scenarios of change; detection of abrupt and slowly varying nonstationarities in observed hydrologic data; and evaluations of projected flow frequency and duration that help to characterize future conditions and facilitate comparisons to observed conditions.

Local perceptions of climate change validated by scientific evidence in the Himalayas.

PubMed

Chaudhary, Pashupati; Bawa, Kamaljit S

2011-10-23

The Himalayas are assumed to be undergoing rapid climate change, with serious environmental, social and economic consequences for more than two billion people. However, data on the extent of climate change or its impact on the region are meagre. Based on local knowledge, we report perceived changes in climate and consequences of such changes for biodiversity and agriculture. Our analyses are based on 250 household interviews administered in 18 villages, and focused group discussions conducted in 10 additional villages in Darjeeling Hills, West Bengal, India and Ilam district of Nepal. There is a widespread feeling that weather is getting warmer, the water sources are drying up, the onset of summer and monsoon has advanced during last 10 years and there is less snow on mountains than before. Local perceptions of the impact of climate change on biodiversity included early budburst and flowering, new agricultural pests and weeds and appearance of mosquitoes. People at high altitudes appear more sensitive to climate change than those at low altitudes. Most local perceptions conform to scientific data. Local knowledge can be rapidly and efficiently gathered using systematic tools. Such knowledge can allow scientists to test specific hypotheses, and policy makers to design mitigation and adaptation strategies for climate change, especially in an extraordinarily important part of our world that is experiencing considerable change.

Elucidating Critical Zone Process Interactions with an Integrated Hydrology Model in a Headwaters Research Catchment

NASA Astrophysics Data System (ADS)

Collins, C.; Maxwell, R. M.

2017-12-01

Providence Creek (P300) watershed is an alpine headwaters catchment located at the Southern Sierra Critical Zone Observatory (SSCZO). Evidence of groundwater-dependent vegetation and drought-induced tree mortality at P300 along with the effect of subsurface characterization on mountain ecohydrology motivates this study. A hyper resolution integrated hydrology model of this site, along with extensive instrumentation, provides an opportunity to study the effects of lateral groundwater flow on vegetation's tolerance to drought. ParFlow-CLM is a fully integrated surface-subsurface model that is driven with reconstructed meteorology, such as the North American Land Data Assimilation System project phase 2 (NLDAS-2) dataset. However, large-scale data products mute orographic effects on climate at smaller scales. Climate variables often do not behave uniformly in highly heterogeneous mountain regions. Therefore, forcing physically-based integrated hydrologic models—especially of mountain headwaters catchments—with a large-scale data product is a major challenge. Obtaining reliable observations in complex terrain is challenging and while climate data products introduce uncertainties likewise, documented discrepancies between several data products and P300 observations suggest these data products may suffice. To tackle these issues, a suite of simulations was run to parse out (1) the effects of climate data source (data products versus observations) and (2) the effects of climate data spatial variability. One tool for evaluating the effect of climate data on model outputs is the relationship between latent head flux (LH) and evapotranspiration (ET) partitioning with water table depth (WTD). This zone of LH sensitivity to WTD is referred to as the "critical zone." Preliminary results suggest that these critical zone relationships are preserved despite forcing albeit significant shifts in magnitude. These results demonstrate that integrated hydrology models are sensitive to climate data thereby impacting the accuracy of hydrologic modeling of headwaters catchments used for water management and planning purposes and exploring the effects of climate change perturbations.

Building Quantitative Hydrologic Storylines from Process-based Models for Managing Water Resources in the U.S. Under Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, J.; Gutmann, E. D.; Clark, M. P.; Nijssen, B.; Vano, J. A.; Addor, N.; Wood, A.; Newman, A. J.; Mizukami, N.; Brekke, L. D.; Rasmussen, R.; Mendoza, P. A.

2016-12-01

Climate change narratives for water-resource applications must represent the change signals contextualized by hydroclimatic process variability and uncertainty at multiple scales. Building narratives of plausible change includes assessing uncertainties across GCM structure, internal climate variability, climate downscaling methods, and hydrologic models. Work with this linked modeling chain has dealt mostly with GCM sampling directed separately to either model fidelity (does the model correctly reproduce the physical processes in the world?) or sensitivity (of different model responses to CO2 forcings) or diversity (of model type, structure, and complexity). This leaves unaddressed any interactions among those measures and with other components in the modeling chain used to identify water-resource vulnerabilities to specific climate threats. However, time-sensitive, real-world vulnerability studies typically cannot accommodate a full uncertainty ensemble across the whole modeling chain, so a gap has opened between current scientific knowledge and most routine applications for climate-changed hydrology. To close that gap, the US Army Corps of Engineers, the Bureau of Reclamation, and the National Center for Atmospheric Research are working on techniques to subsample uncertainties objectively across modeling chain components and to integrate results into quantitative hydrologic storylines of climate-changed futures. Importantly, these quantitative storylines are not drawn from a small sample of models or components. Rather, they stem from the more comprehensive characterization of the full uncertainty space for each component. Equally important from the perspective of water-resource practitioners, these quantitative hydrologic storylines are anchored in actual design and operations decisions potentially affected by climate change. This talk will describe part of our work characterizing variability and uncertainty across modeling chain components and their interactions using newly developed observational data, models and model outputs, and post-processing tools for making the resulting quantitative storylines most useful in practical hydrology applications.

Impact of plastic mulching on nitrous oxide emissions in China's arid agricultural region under climate change conditions

NASA Astrophysics Data System (ADS)

Yu, Yongxiang; Tao, Hui; Jia, Hongtao; Zhao, Chengyi

2017-06-01

The denitrification-decomposition (DNDC) model is a useful tool for integrating the effects of agricultural practices and climate change on soil nitrous oxide (N2O) emissions from agricultural ecosystems. In this study, the DNDC model was evaluated against observations and used to simulate the effect of plastic mulching on soil N2O emissions and crop growth. The DNDC model performed well in simulating temporal variations in N2O emissions and plant growth during the observation period, although it slightly underestimated the cumulative N2O emissions, and was able to simulate the effects of plastic mulching on N2O emissions and crop yield. Both the observations and simulations demonstrated that the application of plastic film increased cumulative N2O emissions and cotton lint yield compared with the non-mulched treatment. The sensitivity test showed that the N2O emissions and lint yield were sensitive to changes in climate and management practices, and the application of plastic film made the N2O emissions and lint yield less sensitive to changes in temperature and irrigation. Although the simulations showed that the beneficial impacts of plastic mulching on N2O emissions were not gained under high fertilizer and irrigation scenarios, our simulations suggest that the application of plastic film effectively reduced soil N2O emissions while promoting yields under suitable fertilizer rates and irrigation. Compared with the baseline scenario, future climate change significantly increased N2O emissions by 15-17% without significantly influencing the lint yields in the non-mulched treatment; in the mulched treatment, climate change significantly promoted the lint yield by 5-6% and significantly reduced N2O emissions by 14% in the RCP4.5 and RCP8.5 scenarios. Overall, our results demonstrate that the application of plastic film is an efficient way to address increased N2O emissions and simultaneously enhance crop yield in the future.

Sensitivity of Glacier Mass Balance Estimates to the Selection of WRF Cloud Microphysics Parameterization in the Indus River Watershed

NASA Astrophysics Data System (ADS)

Johnson, E. S.; Rupper, S.; Steenburgh, W. J.; Strong, C.; Kochanski, A.

2017-12-01

Climate model outputs are often used as inputs to glacier energy and mass balance models, which are essential glaciological tools for testing glacier sensitivity, providing mass balance estimates in regions with little glaciological data, and providing a means to model future changes. Climate model outputs, however, are sensitive to the choice of physical parameterizations, such as those for cloud microphysics, land-surface schemes, surface layer options, etc. Furthermore, glacier mass balance (MB) estimates that use these climate model outputs as inputs are likely sensitive to the specific parameterization schemes, but this sensitivity has not been carefully assessed. Here we evaluate the sensitivity of glacier MB estimates across the Indus Basin to the selection of cloud microphysics parameterizations in the Weather Research and Forecasting Model (WRF). Cloud microphysics parameterizations differ in how they specify the size distributions of hydrometeors, the rate of graupel and snow production, their fall speed assumptions, the rates at which they convert from one hydrometeor type to the other, etc. While glacier MB estimates are likely sensitive to other parameterizations in WRF, our preliminary results suggest that glacier MB is highly sensitive to the timing, frequency, and amount of snowfall, which is influenced by the cloud microphysics parameterization. To this end, the Indus Basin is an ideal study site, as it has both westerly (winter) and monsoonal (summer) precipitation influences, is a data-sparse region (so models are critical), and still has lingering questions as to glacier importance for local and regional resources. WRF is run at a 4 km grid scale using two commonly used parameterizations: the Thompson scheme and the Goddard scheme. On average, these parameterizations result in minimal differences in annual precipitation. However, localized regions exhibit differences in precipitation of up to 3 m w.e. a-1. The different schemes also impact the radiative budgets over the glacierized areas. Our results show that glacier MB estimates can differ by up to 45% depending on the chosen cloud microphysics scheme. These findings highlight the need to better account for uncertainties in meteorological inputs into glacier energy and mass balance models.

Storm Water Management Model Climate Adjustment Tool (SWMM-CAT)

EPA Science Inventory

The US EPA’s newest tool, the Stormwater Management Model (SWMM) – Climate Adjustment Tool (CAT) is meant to help municipal stormwater utilities better address potential climate change impacts affecting their operations. SWMM, first released in 1971, models hydrology and hydrauli...

INVENTORY AND ASSESSMENT OF CLIMATE SENSITIVE DECISIONS

EPA Science Inventory

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

Modelling entomological-climatic interactions of Plasmodium falciparum malaria transmission in two Colombian endemic-regions: contributions to a National Malaria Early Warning System

PubMed Central

Ruiz, Daniel; Poveda, Germán; Vélez, Iván D; Quiñones, Martha L; Rúa, Guillermo L; Velásquez, Luz E; Zuluaga, Juan S

2006-01-01

Background Malaria has recently re-emerged as a public health burden in Colombia. Although the problem seems to be climate-driven, there remain significant gaps of knowledge in the understanding of the complexity of malaria transmission, which have motivated attempts to develop a comprehensive model. Methods The mathematical tool was applied to represent Plasmodium falciparum malaria transmission in two endemic-areas. Entomological exogenous variables were estimated through field campaigns and laboratory experiments. Availability of breeding places was included towards representing fluctuations in vector densities. Diverse scenarios, sensitivity analyses and instabilities cases were considered during experimentation-validation process. Results Correlation coefficients and mean square errors between observed and modelled incidences reached 0.897–0.668 (P > 0.95) and 0.0002–0.0005, respectively. Temperature became the most relevant climatic parameter driving the final incidence. Accordingly, malaria outbreaks are possible during the favourable epochs following the onset of El Niño warm events. Sporogonic and gonotrophic cycles showed to be the entomological key-variables controlling the transmission potential of mosquitoes' population. Simulation results also showed that seasonality of vector density becomes an important factor towards understanding disease transmission. Conclusion The model constitutes a promising tool to deepen the understanding of the multiple interactions related to malaria transmission conducive to outbreaks. In the foreseeable future it could be implemented as a tool to diagnose possible dynamical patterns of malaria incidence under several scenarios, as well as a decision-making tool for the early detection and control of outbreaks. The model will be also able to be merged with forecasts of El Niño events to provide a National Malaria Early Warning System. PMID:16882349

Modelling entomological-climatic interactions of Plasmodium falciparum malaria transmission in two Colombian endemic-regions: contributions to a National Malaria Early Warning System.

PubMed

Ruiz, Daniel; Poveda, Germán; Vélez, Iván D; Quiñones, Martha L; Rúa, Guillermo L; Velásquez, Luz E; Zuluaga, Juan S

2006-08-01

Malaria has recently re-emerged as a public health burden in Colombia. Although the problem seems to be climate-driven, there remain significant gaps of knowledge in the understanding of the complexity of malaria transmission, which have motivated attempts to develop a comprehensive model. The mathematical tool was applied to represent Plasmodium falciparum malaria transmission in two endemic-areas. Entomological exogenous variables were estimated through field campaigns and laboratory experiments. Availability of breeding places was included towards representing fluctuations in vector densities. Diverse scenarios, sensitivity analyses and instabilities cases were considered during experimentation-validation process. Correlation coefficients and mean square errors between observed and modelled incidences reached 0.897-0.668 (P > 0.95) and 0.0002-0.0005, respectively. Temperature became the most relevant climatic parameter driving the final incidence. Accordingly, malaria outbreaks are possible during the favourable epochs following the onset of El Niño warm events. Sporogonic and gonotrophic cycles showed to be the entomological key-variables controlling the transmission potential of mosquitoes' population. Simulation results also showed that seasonality of vector density becomes an important factor towards understanding disease transmission. The model constitutes a promising tool to deepen the understanding of the multiple interactions related to malaria transmission conducive to outbreaks. In the foreseeable future it could be implemented as a tool to diagnose possible dynamical patterns of malaria incidence under several scenarios, as well as a decision-making tool for the early detection and control of outbreaks. The model will be also able to be merged with forecasts of El Niño events to provide a National Malaria Early Warning System.

Multiclass Classification of Agro-Ecological Zones for Arabica Coffee: An Improved Understanding of the Impacts of Climate Change.

PubMed

Bunn, Christian; Läderach, Peter; Pérez Jimenez, Juan Guillermo; Montagnon, Christophe; Schilling, Timothy

2015-01-01

Cultivation of Coffea arabica is highly sensitive to and has been shown to be negatively impacted by progressive climatic changes. Previous research contributed little to support forward-looking adaptation. Agro-ecological zoning is a common tool to identify homologous environments and prioritize research. We demonstrate here a pragmatic approach to describe spatial changes in agro-climatic zones suitable for coffee under current and future climates. We defined agro-ecological zones suitable to produce arabica coffee by clustering geo-referenced coffee occurrence locations based on bio-climatic variables. We used random forest classification of climate data layers to model the spatial distribution of these agro-ecological zones. We used these zones to identify spatially explicit impact scenarios and to choose locations for the long-term evaluation of adaptation measures as climate changes. We found that in zones currently classified as hot and dry, climate change will impact arabica more than those that are better suited to it. Research in these zones should therefore focus on expanding arabica's environmental limits. Zones that currently have climates better suited for arabica will migrate upwards by about 500m in elevation. In these zones the up-slope migration will be gradual, but will likely have negative ecosystem impacts. Additionally, we identified locations that with high probability will not change their climatic characteristics and are suitable to evaluate C. arabica germplasm in the face of climate change. These locations should be used to investigate long term adaptation strategies to production systems.

An early warning system for high climate sensitivity? (Invited)

NASA Astrophysics Data System (ADS)

Pierrehumbert, R.

2010-12-01

The scientific case for the clear and present danger of global warming has been unassailable at least since the release of the Charney Report more than thirty years ago, if not longer. While prompt action to begin decarbonizing energy systems could still head off much of the potential warming, it is distinctly possible that emissions will continue unabated in the coming decades, leading to a doubling or more of pre-industrial carbon dioxide concentrations. At present, we are in the unenviable position of not even knowing how bad things will get if this scenario comes to pass, because of the uncertainty in climate sensitivity. If climate sensitivity is high, then the consequences will be dire, perhaps even catastrophic. As the world continues to warm in response to continued carbon dioxide emissions, will we at least be able to monitor the climate and provide an early warning that the planet is on a high-sensitivity track, if such turns out to be the case? At what point will we actually know the climate sensitivity? It has long been recognized that the prime contributor to uncertainty in climate sensitivity is uncertainty in cloud feedbacks. Study of paleoclimate and climate of the past century has not been able to resolve which models do cloud feedback most correctly, because of uncertainties in radiative forcing. In this talk, I will discuss monitoring requirements, and analysis techniques, that might have the potential to determine which climate models most faithfully represent climate feedbacks, and thus determine which models provide the best estimate of climate sensitivity. The endeavor is complicated by the distinction between transient climate response and equilibrium climate sensitivity. I will discuss the particular challenges posed by this issue, particularly in light of recent indications that the pattern of ocean heat storage may lead to different cloud feedbacks in the transient warming stage than apply once the system has reached equilibrium. Apart from this problem, the transient nature of climate response driven by increasing CO2 requires careful monitoring of ocean heat storage as well as top-of-atmosphere radiative budgets, if climate sensitivity is to be estimated. Water vapor feedback is not considered as uncertain as cloud feedback, but there is still a considerable potential for surprises. I will discuss microwave monitoring requirements for tracking water vapor feedback. At the other extreme, the longer term feedbacks that contribute to Earth System Sensitivity are even more uncertain than cloud feedbacks, particularly with regard to the terrestrial carbon cycle. Prospects for obtaining an early warning of a PETM-type organic carbon release seem bleak. Finally, I will discuss the particular challenge of obtaining an early warning of high climate sensitivity in the case that the climate system has a bifurcation.

Limits to global and Australian temperature change this century based on expert judgment of climate sensitivity

NASA Astrophysics Data System (ADS)

Grose, Michael R.; Colman, Robert; Bhend, Jonas; Moise, Aurel F.

2017-05-01

The projected warming of surface air temperature at the global and regional scale by the end of the century is directly related to emissions and Earth's climate sensitivity. Projections are typically produced using an ensemble of climate models such as CMIP5, however the range of climate sensitivity in models doesn't cover the entire range considered plausible by expert judgment. Of particular interest from a risk-management perspective is the lower impact outcome associated with low climate sensitivity and the low-probability, high-impact outcomes associated with the top of the range. Here we scale climate model output to the limits of expert judgment of climate sensitivity to explore these limits. This scaling indicates an expanded range of projected change for each emissions pathway, including a much higher upper bound for both the globe and Australia. We find the possibility of exceeding a warming of 2 °C since pre-industrial is projected under high emissions for every model even scaled to the lowest estimate of sensitivity, and is possible under low emissions under most estimates of sensitivity. Although these are not quantitative projections, the results may be useful to inform thinking about the limits to change until the sensitivity can be more reliably constrained, or this expanded range of possibilities can be explored in a more formal way. When viewing climate projections, accounting for these low-probability but high-impact outcomes in a risk management approach can complement the focus on the likely range of projections. They can also highlight the scale of the potential reduction in range of projections, should tight constraints on climate sensitivity be established by future research.

Regional Climate and Streamflow Projections in North America Under IPCC CMIP5 Scenarios

NASA Astrophysics Data System (ADS)

Chang, H. I.; Castro, C. L.; Troch, P. A. A.; Mukherjee, R.

2014-12-01

The Colorado River system is the predominant source of water supply for the Southwest U.S. and is already fully allocated, making the region's environmental and economic health particularly sensitive to annual and multi-year streamflow variability. Observed streamflow declines in the Colorado Basin in recent years are likely due to synergistic combination of anthropogenic global warming and natural climate variability, which are creating an overall warmer and more extreme climate. IPCC assessment reports have projected warmer and drier conditions in arid to semi-arid regions (e.g. Solomon et al. 2007). The NAM-related precipitation contributes to substantial Colorado streamflows. Recent climate change studies for the Southwest U.S. region project a dire future, with chronic drought, and substantially reduced Colorado River flows. These regional effects reflect the general observation that climate is being more extreme globally, with areas climatologically favored to be wet getting wetter and areas favored to be dry getting drier (Wang et al. 2012). Multi-scale downscaling modeling experiments are designed using recent IPCC AR5 global climate projections, which incorporate regional climate and hydrologic modeling components. The Weather Research and Forecasting model (WRF) has been selected as the main regional modeling tool; the Variable Infiltration Capacity model (VIC) will be used to generate streamflow projections for the Colorado River Basin. The WRF domain is set up to follow the CORDEX-North America guideline with 25km grid spacing, and VIC model is individually calibrated for upper and lower Colorado River basins in 1/8° resolution. The multi-scale climate and hydrology study aims to characterize how the combination of climate change and natural climate variability is changing cool and warm season precipitation. Further, to preserve the downscaled RCM sensitivity and maintain a reasonable climatology mean based on observed record, a new bias correction technique is applied when using the RCM climatology to the streamflow model. Of specific interest is how major droughts associated with La Niña-like conditions may worsen in the future, as these are the times when the Colorado River system is most critically stressed and would define the "worst case" scenario for water resource planning.

Agroclimate.Org: Tools and Information for a Climate Resilient Agriculture in the Southeast USA

NASA Astrophysics Data System (ADS)

Fraisse, C.

2014-12-01

AgroClimate (http://agroclimate.org) is a web-based system developed to help the agricultural industry in the southeastern USA reduce risks associated with climate variability and change. It includes climate related information and dynamic application tools that interact with a climate and crop database system. Information available includes climate monitoring and forecasts combined with information about crop management practices that help increase the resiliency of the agricultural industry in the region. Recently we have included smartphone apps in the AgroClimate suite of tools, including irrigation management and crop disease alert systems. Decision support tools available in AgroClimate include: (a) Climate risk: expected (probabilistic) and historical climate information and freeze risk; (b) Crop yield risk: expected yield based on soil type, planting date, and basic management practices for selected commodities and historical county yield databases; (c) Crop diseases: disease risk monitoring and forecasting for strawberry and citrus; (d) Crop development: monitoring and forecasting of growing degree-days and chill accumulation; (e) Drought: monitoring and forecasting of selected drought indices, (f) Footprints: Carbon and water footprint calculators. The system also provides background information about the main drivers of climate variability and basic information about climate change in the Southeast USA. AgroClimate has been widely used as an educational tool by the Cooperative Extension Services in the region and also by producers. It is now being replicated internationally with version implemented in Mozambique and Paraguay.

Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

NASA Astrophysics Data System (ADS)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling parameter for the aerosols. The estimation method is computationally fast and can be used with more complex models where climate sensitivity is diagnosed rather than prescribed. The parameter estimates can be used to create probabilistic climate projections using the UVic ESCM model in future studies.

Climate sensitivity of DSSAT under different agriculture practice scenarios in China

NASA Astrophysics Data System (ADS)

Xia, L.; Robock, A.

2014-12-01

Crop yields are sensitive to both agricultural practice and climate changes. Under different agricultural practice scenarios, crop yield may have different climate sensitivities. Since it is important to understand how future climate changes affect agriculture productivity and what the potential adaptation strategies would be to compensate for possible negative impacts on crop production, we performed experiments to study climate sensitivity under different agricultural practice scenarios for rice, maize and wheat in the top four production provinces in China using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model. The agricultural practice scenarios include four categories: different amounts of nitrogen fertilizer or no nitrogen stress; irrigation turned on or off, or no water stress; all possible seeds in the DSSAT cultivar data base; and different planting dates. For the climate sensitivity test, the control climate is from 1998 to 2007, and we individually modify four climate variables: daily maximum and minimum temperature by +2 °C and -2 °C, daily precipitation by +20% and -20%, and daily solar radiation by + 20% and -20%. With more nitrogen fertilizer applied, crops are more sensitive to temperature changes as well as precipitation changes because of their release from nitrogen limitation. With irrigation turned on, crop yield sensitivity to temperature decreases in most of the regions depending on the amount of the local precipitation, since more water is available and soil temperature varies less with higher soil moisture. Those results indicate that there could be possible agriculture adaptation strategies under certain future climate scenarios. For example, increasing nitrogen fertilizer usage by a certain amount might compensate for the negative impact on crop yield from climate changes. However, since crops are more sensitive to climate changes when there is more nitrogen fertilizer applied, if the climate changes are unfavorable to crop yields, increasing nitrogen fertilizer usage at certain levels might enhance the negative climate change impact. Enhanced nitrogen fertilizer use might have additional negative impacts on climate because of nitrogen emissions to the atmosphere, but those effects were not studied here.

Developing Climate Resilience Toolkit Decision Support Training Sectio

NASA Astrophysics Data System (ADS)

Livezey, M. M.; Herring, D.; Keck, J.; Meyers, J. C.

2014-12-01

The Climate Resilience Toolkit (CRT) is a Federal government effort to address the U.S. President's Climate Action Plan and Executive Order for Climate Preparedness. The toolkit will provide access to tools and products useful for climate-sensitive decision making. To optimize the user experience, the toolkit will also provide access to training materials. The National Oceanic and Atmospheric Administration (NOAA) has been building a climate training capability for 15 years. The target audience for the training has historically been mainly NOAA staff with some modified training programs for external users and stakeholders. NOAA is now using this climate training capacity for the CRT. To organize the CRT training section, we collaborated with the Association of Climate Change Officers to determine the best strategy and identified four additional complimentary skills needed for successful decision making: climate literacy, environmental literacy, risk assessment and management, and strategic execution and monitoring. Developing the climate literacy skills requires knowledge of climate variability and change, as well as an introduction to the suite of available products and services. For the development of an environmental literacy category, specific topics needed include knowledge of climate impacts on specific environmental systems. Climate risk assessment and management introduces a process for decision making and provides knowledge on communication of climate information and integration of climate information in planning processes. The strategic execution and monitoring category provides information on use of NOAA climate products, services, and partnership opportunities for decision making. In order to use the existing training modules, it was necessary to assess their level of complexity, catalog them, and develop guidance for users on a curriculum to take advantage of the training resources to enhance their learning experience. With the development of this CRT training section, NOAA has made significant progress in sharing resources with the external community.

Sensitivity of Regulated Flow Regimes to Climate Change in the Western United States

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

Zhou, Tian; Voisin, Nathalie; Leng, Guoyong

Water management activities or flow regulations modify water fluxes at the land surface and affect water resources in space and time. We hypothesize that flow regulations change the sensitivity of river flow to climate change with respect to unmanaged water resources. Quantifying these changes in sensitivity could help elucidate the impacts of water management at different spatiotemporal scales and inform climate adaptation decisions. In this study, we compared the emergence of significant changes in natural and regulated river flow regimes across the Western United States from simulations driven by multiple climate models and scenarios. We find that significant climate change-inducedmore » alterations in natural flow do not cascade linearly through water management activities. At the annual time scale, 50% of the Hydrologic Unit Code 4 (HUC4) sub-basins over the Western U.S. regions tend to have regulated flow regime more sensitive to the climate change than natural flow regime. Seasonality analyses show that the sensitivity varies remarkably across the seasons. We also find that the sensitivity is related to the level of water management. For 35% of the HUC4 sub-basins with the highest level of water management, the summer and winter flows tend to show a heightened sensitivity to climate change due to the complexity of joint reservoir operations. We further demonstrate that the impacts of considering water management in models are comparable to those that arises from uncertainties across climate models and emission scenarios. This prompts further climate adaptation studies research about nonlinearity effects of climate change through water management activities.« less

Implications for Climate Sensitivity from the Response to Individual Forcings

NASA Technical Reports Server (NTRS)

Marvel, Kate; Schmidt, Gavin A.; Miller, Ron L.; Nazarenko, Larissa

2015-01-01

Climate sensitivity to doubled CO2 is a widely-used metric of the large-scale response to external forcing. Climate models predict a wide range for two commonly used definitions: the transient climate response (TCR: the warming after 70 years of CO2 concentrations that riseat 1 per year), and the equilibrium climate sensitivity (ECS: the equilibrium temperature change following a doubling of CO2 concentrations). Many observational datasets have been used to constrain these values, including temperature trends over the recent past 16, inferences from paleo-climate and process-based constraints from the modern satellite eras. However, as the IPCC recently reported different classes of observational constraints produce somewhat incongruent ranges. Here we show that climate sensitivity estimates derived from recent observations must account for the efficacy of each forcing active during the historical period. When we use single forcing experiments to estimate these efficacies and calculate climate sensitivity from the observed twentieth-century warming, our estimates of both TCR and ECS are revised upward compared to previous studies, improving the consistency with independent constraints.

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system.

PubMed

Seinfeld, John H; Bretherton, Christopher; Carslaw, Kenneth S; Coe, Hugh; DeMott, Paul J; Dunlea, Edward J; Feingold, Graham; Ghan, Steven; Guenther, Alex B; Kahn, Ralph; Kraucunas, Ian; Kreidenweis, Sonia M; Molina, Mario J; Nenes, Athanasios; Penner, Joyce E; Prather, Kimberly A; Ramanathan, V; Ramaswamy, Venkatachalam; Rasch, Philip J; Ravishankara, A R; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System

NASA Technical Reports Server (NTRS)

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kahn, Ralph;

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system

DOE PAGES

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; ...

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from pre-industrial time. General Circulation Models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions but significant challengesmore » exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. Lastly, we suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.« less

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

PubMed Central

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kraucunas, Ian; Molina, Mario J.; Nenes, Athanasios; Penner, Joyce E.; Prather, Kimberly A.; Ramanathan, V.; Ramaswamy, Venkatachalam; Rasch, Philip J.; Ravishankara, A. R.; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-01-01

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty. PMID:27222566

BASINS Climate Assessment Tool Tutorials

EPA Pesticide Factsheets

The BASINS Climate Assessment Tool (CAT) provides a flexible set of capabilities for exploring the potential effects of climate change on streamflow and water quality using different watershed models in BASINS.

The Dependencies of Ecosystem Pattern, Structure, and Dynamics on Climate, Climate Variability, and Climate Change

NASA Astrophysics Data System (ADS)

Flanagan, S.; Hurtt, G. C.; Fisk, J. P.; Rourke, O.

2012-12-01

A robust understanding of the sensitivity of the pattern, structure, and dynamics of ecosystems to climate, climate variability, and climate change is needed to predict ecosystem responses to current and projected climate change. We present results of a study designed to first quantify the sensitivity of ecosystems to climate through the use of climate and ecosystem data, and then use the results to test the sensitivity of the climate data in a state-of the art ecosystem model. A database of available ecosystem characteristics such as mean canopy height, above ground biomass, and basal area was constructed from sources like the National Biomass and Carbon Dataset (NBCD). The ecosystem characteristics were then paired by latitude and longitude with the corresponding climate characteristics temperature, precipitation, photosynthetically active radiation (PAR) and dew point that were retrieved from the North American Regional Reanalysis (NARR). The average yearly and seasonal means of the climate data, and their associated maximum and minimum values, over the 1979-2010 time frame provided by NARR were constructed and paired with the ecosystem data. The compiled results provide natural patterns of vegetation structure and distribution with regard to climate data. An advanced ecosystem model, the Ecosystem Demography model (ED), was then modified to allow yearly alterations to its mechanistic climate lookup table and used to predict the sensitivities of ecosystem pattern, structure, and dynamics to climate data. The combined ecosystem structure and climate data results were compared to ED's output to check the validity of the model. After verification, climate change scenarios such as those used in the last IPCC were run and future forest structure changes due to climate sensitivities were identified. The results of this study can be used to both quantify and test key relationships for next generation models. The sensitivity of ecosystem characteristics to climate data shown in the database construction and by the model reinforces the need for high-resolution datasets and stresses the importance of understanding and incorporating climate change scenarios into earth system models.

Challenges and approaches to projecting changes in forest distributions in complex mountain landscape

NASA Astrophysics Data System (ADS)

Kueppers, L. M.; Molotch, N. P.; Meromy, L.; Moyes, A. B.; Conlisk, E.; Castanha, C.

2015-12-01

The extent and density of forest trees in mountain landscapes is a first order control on watershed function, affecting patterns of snow accumulation, timing of snowmelt, and amount and quality of run-off, through alterations of surface energy and water fluxes and wind. Climate change is increasingly affecting the density and distribution of mature forests through changes to disturbance regimes, increases in physiological stress and increases in mortality due to warmer temperatures. In addition, climate change is likely altering patterns of regeneration and driving establishment of trees in high elevation meadows and alpine tundra. Though hard to detect in current forestry datasets, changes in tree establishment are critical to the future of forests. Experimental approaches, such as our climate warming experiment in the Colorado Front Range, can provide valuable data regarding seedling sensitivity to climate variability and change across important landscape positions. We've found that warming enhances negative effects of water stress across forest, treeline and alpine sites, reducing recruitment in the absence of additional summer moisture. At the lowest elevation, reductions with warming have reduced Engelmann spruce recruitment to zero. Species differ in their responses to warming in the alpine, but together confirm the importance of seed dispersal to upward forest shifts. The presence of trees or other vegetation can facilitate tree establishment by modifying microclimates, especially at and above treeline. Ultimately, these ecological and demographic processes govern the timescales of tree and forest responses to climate variability and change. For the long-lived species that dominate high elevation watersheds, these processes can take decades or centuries to play out, meaning many tree populations are and will continue to be out of equilibrium with a rapidly changing climate. Projecting changes in tree distributions and abundances across mountain landscapes requires integration of changes in hydroclimatic conditions across diverse topoclimatic settings; the sensitivity of recruitment, growth and mortality to climate; and feedbacks between trees and microclimate into modeling tools that represent time-explicit ecological and demographic processes.

A Simple Climate Model Program for High School Education

NASA Astrophysics Data System (ADS)

Dommenget, D.

2012-04-01

The future climate change projections of the IPCC AR4 are based on GCM simulations, which give a distinct global warming pattern, with an arctic winter amplification, an equilibrium land sea contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the IPCC predictions, the conceptual understanding of these predicted structures of climate change are very difficult to reach if only based on these highly complex GCM simulations and they are not accessible for ordinary people. In this study presented here we will introduce a very simple gridded globally resolved energy balance model based on strongly simplified physical processes, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the 1-dimensional energy balance models and the fully coupled 4-dimensional complex GCMs. It runs on standard PC computers computing globally resolved climate simulation with 2yrs per second or 100,000yrs per day. The program can compute typical global warming scenarios in a few minutes on a standard PC. The computer code is only 730 line long with very simple formulations that high school students should be able to understand. The simple model's climate sensitivity and the spatial structure of the warming pattern is within the uncertainties of the IPCC AR4 models simulations. It is capable of simulating the arctic winter amplification, the equilibrium land sea contrast and the inter-hemispheric warming gradient with good agreement to the IPCC AR4 models in amplitude and structure. The program can be used to do sensitivity studies in which students can change something (e.g. reduce the solar radiation, take away the clouds or make snow black) and see how it effects the climate or the climate response to changes in greenhouse gases. This program is available for every one and could be the basis for high school education. Partners for a high school project are wanted!

Contrasting model complexity under a changing climate in a headwaters catchment.

NASA Astrophysics Data System (ADS)

Foster, L.; Williams, K. H.; Maxwell, R. M.

2017-12-01

Alpine, snowmelt-dominated catchments are the source of water for more than 1/6th of the world's population. These catchments are topographically complex, leading to steep weather gradients and nonlinear relationships between water and energy fluxes. Recent evidence suggests that alpine systems are more sensitive to climate warming, but these regions are vastly simplified in climate models and operational water management tools due to computational limitations. Simultaneously, point-scale observations are often extrapolated to larger regions where feedbacks can both exacerbate or mitigate locally observed changes. It is critical to determine whether projected climate impacts are robust to different methodologies, including model complexity. Using high performance computing and an integrated model of a representative headwater catchment we determined the hydrologic response from 30 projected climate changes to precipitation, temperature and vegetation for the Rocky Mountains. Simulations were run with 100m and 1km resolution, and with and without lateral subsurface flow in order to vary model complexity. We found that model complexity alters nonlinear relationships between water and energy fluxes. Higher-resolution models predicted larger changes per degree of temperature increase than lower resolution models, suggesting that reductions to snowpack, surface water, and groundwater due to warming may be underestimated in simple models. Increases in temperature were found to have a larger impact on water fluxes and stores than changes in precipitation, corroborating previous research showing that mountain systems are significantly more sensitive to temperature changes than to precipitation changes and that increases in winter precipitation are unlikely to compensate for increased evapotranspiration in a higher energy environment. These numerical experiments help to (1) bracket the range of uncertainty in published literature of climate change impacts on headwater hydrology; (2) characterize the role of precipitation and temperature changes on water supply for snowmelt-dominated downstream basins; and (3) identify which climate impacts depend on the scale of simulation.

A climate responsive urban design tool: a platform to improve energy efficiency in a dry hot climate

NASA Astrophysics Data System (ADS)

El Dallal, Norhan; Visser, Florentine

2017-09-01

In the Middle East and North Africa (MENA) region, new urban developments should address the climatic conditions to improve outdoor comfort and to reduce the energy consumption of buildings. This article describes a design tool that supports climate responsive design for a dry hot climate. The approach takes the climate as an initiator for the conceptual urban form with a more energy-efficient urban morphology. The methodology relates the different passive strategies suitable for major climate conditions in MENA region (dry-hot) to design parameters that create the urban form. This parametric design approach is the basis for a tool that generates conceptual climate responsive urban forms so as to assist the urban designer early in the design process. Various conceptual scenarios, generated by a computational model, are the results of the proposed platform. A practical application of the approach is conducted on a New Urban Community in Aswan (Egypt), showing the economic feasibility of the resulting urban form and morphology, and the proposed tool.

Sensitivity of an Integrated Mesoscale Atmosphere and Agriculture Land Modeling System (WRF/CMAQ-EPIC) to MODIS Vegetation and Lightning Assimilation

NASA Astrophysics Data System (ADS)

Ran, L.; Cooter, E. J.; Gilliam, R. C.; Foroutan, H.; Kang, D.; Appel, W.; Wong, D. C.; Pleim, J. E.; Benson, V.; Pouliot, G.

2017-12-01

The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteorology, climate, and chemical transport. The Environmental Policy Integrated Climate (EPIC) is a cropping model which has long been used in a range of applications related to soil erosion, crop productivity, climate change, and water quality around the world. We have integrated WRF/CMAQ with EPIC using the Fertilizer Emission Scenario Tool for CMAQ (FEST-C) to estimate daily soil N information with fertilization for CMAQ bi-directional ammonia flux modeling. Driven by the weather and N deposition from WRF/CMAQ, FEST-C EPIC simulations are conducted on 22 different agricultural production systems ranging from managed grass lands (e.g. hay and alfalfa) to crop lands (e.g. corn grain and soybean) with rainfed and irrigated information across any defined conterminous United States (U.S.) CMAQ domain and grid resolution. In recent years, this integrated system has been enhanced and applied in many different air quality and ecosystem assessment projects related to land-water-atmosphere interactions. These enhancements have advanced this system to become a valuable tool for integrated assessments of air, land and water quality in light of social drivers and human and ecological outcomes. This presentation will focus on evaluating the sensitivity of precipitation and N deposition in the integrated system to MODIS vegetation input and lightning assimilation and their impacts on agricultural production and fertilization. We will describe the integrated modeling system and evaluate simulated precipitation and N deposition along with other weather information (e.g. temperature, humidity) for 2011 over the conterminous U.S. at 12 km grids from a coupled WRF/CMAQ with MODIS and lightning assimilation. Simulated agricultural production and fertilization from FEST-C EPIC driven by the changed meteorology and N deposition from MODIS and lightning assimilations will be evaluated and analyzed.

Flow pathways and nutrient transport mechanisms drive hydrochemical sensitivity to climate change across catchments with different geology and topography

NASA Astrophysics Data System (ADS)

Crossman, J.; Futter, M. N.; Whitehead, P. G.; Stainsby, E.; Baulch, H. M.; Jin, L.; Oni, S. K.; Wilby, R. L.; Dillon, P. J.

2014-07-01

Hydrological processes determine the transport of nutrients and passage of diffuse pollution. Consequently, catchments are likely to exhibit individual hydrochemical responses (sensitivities) to climate change, which is expected to alter the timing and amount of runoff, and to impact in-stream water quality. In developing robust catchment management strategies and quantifying plausible future hydrochemical conditions it is therefore equally important to consider the potential for spatial variability in, and causal factors of, catchment sensitivity, as to explore future changes in climatic pressures. This study seeks to identify those factors which influence hydrochemical sensitivity to climate change. A perturbed physics ensemble (PPE), derived from a series of Global Climate Model (GCM) variants with specific climate sensitivities was used to project future climate change and uncertainty. Using the Integrated Catchment Model of Phosphorus Dynamics (INCA-P), we quantified potential hydrochemical responses in four neighbouring catchments (with similar land use but varying topographic and geological characteristics) in southern Ontario, Canada. Responses were assessed by comparing a 30 year baseline (1968-1997) to two future periods: 2020-2049 and 2060-2089. Although projected climate change and uncertainties were similar across these catchments, hydrochemical responses (sensitivity) were highly varied. Sensitivity was governed by soil type (influencing flow pathways) and nutrient transport mechanisms. Clay-rich catchments were most sensitive, with total phosphorus (TP) being rapidly transported to rivers via overland flow. In these catchments large annual reductions in TP loads were projected. Sensitivity in the other two catchments, dominated by sandy-loams, was lower due to a larger proportion of soil matrix flow, longer soil water residence times and seasonal variability in soil-P saturation. Here smaller changes in TP loads, predominantly increases, were projected. These results suggest that the clay content of soils could be a good indicator of the sensitivity of catchments to climatic input, and reinforces calls for catchment-specific management plans.

Flow pathways and nutrient transport mechanisms drive hydrochemical sensitivity to climate change across catchments with different geology and topography

NASA Astrophysics Data System (ADS)

Crossman, J.; Futter, M. N.; Whitehead, P. G.; Stainsby, E.; Baulch, H. M.; Jin, L.; Oni, S. K.; Wilby, R. L.; Dillon, P. J.

2014-12-01

Hydrological processes determine the transport of nutrients and passage of diffuse pollution. Consequently, catchments are likely to exhibit individual hydrochemical responses (sensitivities) to climate change, which are expected to alter the timing and amount of runoff, and to impact in-stream water quality. In developing robust catchment management strategies and quantifying plausible future hydrochemical conditions it is therefore equally important to consider the potential for spatial variability in, and causal factors of, catchment sensitivity, as it is to explore future changes in climatic pressures. This study seeks to identify those factors which influence hydrochemical sensitivity to climate change. A perturbed physics ensemble (PPE), derived from a series of global climate model (GCM) variants with specific climate sensitivities was used to project future climate change and uncertainty. Using the INtegrated CAtchment model of Phosphorus dynamics (INCA-P), we quantified potential hydrochemical responses in four neighbouring catchments (with similar land use but varying topographic and geological characteristics) in southern Ontario, Canada. Responses were assessed by comparing a 30 year baseline (1968-1997) to two future periods: 2020-2049 and 2060-2089. Although projected climate change and uncertainties were similar across these catchments, hydrochemical responses (sensitivities) were highly varied. Sensitivity was governed by quaternary geology (influencing flow pathways) and nutrient transport mechanisms. Clay-rich catchments were most sensitive, with total phosphorus (TP) being rapidly transported to rivers via overland flow. In these catchments large annual reductions in TP loads were projected. Sensitivity in the other two catchments, dominated by sandy loams, was lower due to a larger proportion of soil matrix flow, longer soil water residence times and seasonal variability in soil-P saturation. Here smaller changes in TP loads, predominantly increases, were projected. These results suggest that the clay content of soils could be a good indicator of the sensitivity of catchments to climatic input, and reinforces calls for catchment-specific management plans.

Plio-Pleistocene climate sensitivity evaluated using high-resolution CO2 records

NASA Astrophysics Data System (ADS)

Martínez-Botí, M. A.; Foster, G. L.; Chalk, T. B.; Rohling, E. J.; Sexton, P. F.; Lunt, D. J.; Pancost, R. D.; Badger, M. P. S.; Schmidt, D. N.

2015-02-01

Theory and climate modelling suggest that the sensitivity of Earth's climate to changes in radiative forcing could depend on the background climate. However, palaeoclimate data have thus far been insufficient to provide a conclusive test of this prediction. Here we present atmospheric carbon dioxide (CO2) reconstructions based on multi-site boron-isotope records from the late Pliocene epoch (3.3 to 2.3 million years ago). We find that Earth's climate sensitivity to CO2-based radiative forcing (Earth system sensitivity) was half as strong during the warm Pliocene as during the cold late Pleistocene epoch (0.8 to 0.01 million years ago). We attribute this difference to the radiative impacts of continental ice-volume changes (the ice-albedo feedback) during the late Pleistocene, because equilibrium climate sensitivity is identical for the two intervals when we account for such impacts using sea-level reconstructions. We conclude that, on a global scale, no unexpected climate feedbacks operated during the warm Pliocene, and that predictions of equilibrium climate sensitivity (excluding long-term ice-albedo feedbacks) for our Pliocene-like future (with CO2 levels up to maximum Pliocene levels of 450 parts per million) are well described by the currently accepted range of an increase of 1.5 K to 4.5 K per doubling of CO2.

Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA

USGS Publications Warehouse

West, Amanda; Kumar, Sunil; Jarnevich, Catherine S.

2016-01-01

Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

Enhancing seasonal climate prediction capacity for the Pacific countries

NASA Astrophysics Data System (ADS)

Kuleshov, Y.; Jones, D.; Hendon, H.; Charles, A.; Cottrill, A.; Lim, E.-P.; Langford, S.; de Wit, R.; Shelton, K.

2012-04-01

Seasonal and inter-annual climate variability is a major factor in determining the vulnerability of many Pacific Island Countries to climate change and there is need to improve weekly to seasonal range climate prediction capabilities beyond what is currently available from statistical models. In the seasonal climate prediction project under the Australian Government's Pacific Adaptation Strategy Assistance Program (PASAP), we describe a comprehensive project to strengthen the climate prediction capacities in National Meteorological Services in 14 Pacific Island Countries and East Timor. The intent is particularly to reduce the vulnerability of current services to a changing climate, and improve the overall level of information available assist with managing climate variability. Statistical models cannot account for aspects of climate variability and change that are not represented in the historical record. In contrast, dynamical physics-based models implicitly include the effects of a changing climate whatever its character or cause and can predict outcomes not seen previously. The transition from a statistical to a dynamical prediction system provides more valuable and applicable climate information to a wide range of climate sensitive sectors throughout the countries of the Pacific region. In this project, we have developed seasonal climate outlooks which are based upon the current dynamical model POAMA (Predictive Ocean-Atmosphere Model for Australia) seasonal forecast system. At present, meteorological services of the Pacific Island Countries largely employ statistical models for seasonal outlooks. Outcomes of the PASAP project enhanced capabilities of the Pacific Island Countries in seasonal prediction providing National Meteorological Services with an additional tool to analyse meteorological variables such as sea surface temperatures, air temperature, pressure and rainfall using POAMA outputs and prepare more accurate seasonal climate outlooks.

Informing climate change adaptation with insights from famine early warning (Invited)

NASA Astrophysics Data System (ADS)

Funk, C. C.; Verdin, J. P.

2010-12-01

Famine early warning systems provide a unique viewpoint for understanding the implications of climate change on food security, identifying the locations and seasons where millions of food insecure people are dependent upon climate-sensitive agricultural systems. The Famine Early Warning Systems Network (FEWS NET) is a decision support system sponsored by the Office of Food for Peace of the U.S. Agency for International Development (USAID), which distributes over two billion dollars of food aid to more than 40 countries each year. FEWS NET identifies the times and places where food aid is required by the most climatically sensitive and consequently food insecure populations of the developing world. As result, FEWS NET has developed its own "climate service", implemented by USGS, NOAA, and NASA, to support its decision making processes. The foundation of this climate service is the monitoring of current growing conditions for early identification of agricultural drought that might impact food security. Since station networks are sparse in the countries monitored, FEWS NET has a tradition (dating back to 1985) of reliance on satellite remote sensing of vegetation and rainfall. In the last ten years, climate forecasts have become an additional tool for food security assessment, extending the early warning perspective to include expected agricultural outcomes for the season ahead. More recently, research has expanded to include detailed analyses of recent observed climate trends, combined with diagnostic ocean-atmosphere studies. These studies are then used to develop interpretations of GCM scenarios and their implications for future patterns of precipitation and temperature, revealing trends towards warmer/drier climate conditions and increases in the relative frequency of drought. In some regions, like Eastern Africa, such changes seem to be already occurring, with an associated increase in food insecurity. Sub-national analyses for Kenya, for example, point to the need for adaptation through improved agricultural practices, so that increased yields can offset the impacts of rising temperatures and declining rainfall. Future work will focus on assessing temperature-PET linkages, and evaluating pathways for agricultural development.

Thinning increases climatic resilience of red pine

USGS Publications Warehouse

Magruder, Matthew; Chhin, Sophan; Palik, Brian; Bradford, John B.

2013-01-01

Forest management techniques such as intermediate stand-tending practices (e.g., thinning) can promote climatic resiliency in forest stands by moderating tree competition. Residual trees gain increased access to environmental resources (i.e., soil moisture, light), which in turn has the potential to buffer trees from stressful climatic conditions. The influences of climate (temperature and precipitation) and forest management (thinning method and intensity) on the productivity of red pine (Pinus resinosa Ait.) in Michigan were examined to assess whether repeated thinning treatments were able to increase climatic resiliency (i.e., maintaining productivity and reduced sensitivity to climatic stress). The cumulative productivity of each thinning treatment was determined, and it was found that thinning from below to a residual basal area of 14 m2·ha−1 produced the largest average tree size but also the second lowest overall biomass per acre. On the other hand, the uncut control and the thinning from above to a residual basal area of 28 m2·ha−1 produced the smallest average tree size but also the greatest overall biomass per acre. Dendrochronological methods were used to quantify sensitivity of annual radial growth to monthly and seasonal climatic factors for each thinning treatment type. Climatic sensitivity was influenced by thinning method (i.e., thinning from below decreased sensitivity to climatic stress more than thinning from above) and by thinning intensity (i.e., more intense thinning led to a lower climatic sensitivity). Overall, thinning from below to a residual basal area of 21 m2·ha−1 represented a potentially beneficial compromise to maximize tree size, biomass per acre, and reduced sensitivity to climatic stress, and, thus, the highest level of climatic resilience.

Multiclass Classification of Agro-Ecological Zones for Arabica Coffee: An Improved Understanding of the Impacts of Climate Change

PubMed Central

Bunn, Christian; Läderach, Peter; Pérez Jimenez, Juan Guillermo; Montagnon, Christophe; Schilling, Timothy

2015-01-01

Cultivation of Coffea arabica is highly sensitive to and has been shown to be negatively impacted by progressive climatic changes. Previous research contributed little to support forward-looking adaptation. Agro-ecological zoning is a common tool to identify homologous environments and prioritize research. We demonstrate here a pragmatic approach to describe spatial changes in agro-climatic zones suitable for coffee under current and future climates. We defined agro-ecological zones suitable to produce arabica coffee by clustering geo-referenced coffee occurrence locations based on bio-climatic variables. We used random forest classification of climate data layers to model the spatial distribution of these agro-ecological zones. We used these zones to identify spatially explicit impact scenarios and to choose locations for the long-term evaluation of adaptation measures as climate changes. We found that in zones currently classified as hot and dry, climate change will impact arabica more than those that are better suited to it. Research in these zones should therefore focus on expanding arabica's environmental limits. Zones that currently have climates better suited for arabica will migrate upwards by about 500m in elevation. In these zones the up-slope migration will be gradual, but will likely have negative ecosystem impacts. Additionally, we identified locations that with high probability will not change their climatic characteristics and are suitable to evaluate C. arabica germplasm in the face of climate change. These locations should be used to investigate long term adaptation strategies to production systems. PMID:26505637

The Effect of an Increased Convective Entrainment Rate on Indian Monsoon Biases in the Met Office Unified Model

NASA Astrophysics Data System (ADS)

Bush, Stephanie; Turner, Andrew; Woolnough, Steve; Martin, Gill

2013-04-01

Global circulation models (GCMs) are a key tool for understanding and predicting monsoon rainfall, now and under future climate change. However, many GCMs show significant, systematic biases in their simulation of monsoon rainfall and dynamics that spin up over very short time scales and persist in the climate mean state. We describe several of these biases as simulated in the Met Office Unified Model and show they are sensitive to changes in the convective parameterization's entrainment rate. To improve our understanding of the biases and inform efforts to improve convective parameterizations, we explore the reasons for this sensitivity. We show the results of experiments where we increase the entrainment rate in regions of especially large bias: the western equatorial Indian Ocean, western north Pacific and India itself. We use the results to determine whether improvements in biases are due to the local increase in entrainment or are the remote response of the entrainment increase elsewhere in the GCM. We find that feedbacks usually strengthen the local response, but the local response leads to a different mean state change in different regions. We also show results from experiments which demonstrate the spin-up of the local response, which we use to further understand the response in complex regions such as the Western North Pacific. Our work demonstrates that local application of parameterization changes is a powerful tool for understanding their global impact.

Climate change and marine fisheries: Least developed countries top global index of vulnerability

PubMed Central

Blasiak, Robert; Spijkers, Jessica; Tokunaga, Kanae; Pittman, Jeremy; Yagi, Nobuyuki; Österblom, Henrik

2017-01-01

Future impacts of climate change on marine fisheries have the potential to negatively influence a wide range of socio-economic factors, including food security, livelihoods and public health, and even to reshape development trajectories and spark transboundary conflict. Yet there is considerable variability in the vulnerability of countries around the world to these effects. We calculate a vulnerability index of 147 countries by drawing on the most recent data related to the impacts of climate change on marine fisheries. Building on the Intergovernmental Panel on Climate Change framework for vulnerability, we first construct aggregate indices for exposure, sensitivity and adaptive capacity using 12 primary variables. Seven out of the ten most vulnerable countries on the resulting index are Small Island Developing States, and the top quartile of the index includes countries located in Africa (17), Asia (7), North America and the Caribbean (4) and Oceania (8). More than 87% of least developed countries are found within the top half of the vulnerability index, while the bottom half includes all but one of the Organization for Economic Co-operation and Development member states. This is primarily due to the tremendous variation in countries’ adaptive capacity, as no such trends are evident from the exposure or sensitivity indices. A negative correlation exists between vulnerability and per capita carbon emissions, and the clustering of states at different levels of development across the vulnerability index suggests growing barriers to meeting global commitments to reducing inequality, promoting human well-being and ensuring sustainable cities and communities. The index provides a useful tool for prioritizing the allocation of climate finance, as well as activities aimed at capacity building and the transfer of marine technology. PMID:28632781

Climate change and children.

PubMed

Ebi, Kristie L; Paulson, Jerome A

2007-04-01

Climate change is increasing the burden of climate-sensitive health determinants and outcomes worldwide. Acting through increasing temperature, changes in the hydrologic cycle, and sea level rise, climate change is projected to increase the frequency and intensity of heat events and extreme events (floods and droughts), change the geographic range and incidence of climate-sensitive vector-, food-, and waterborne diseases, and increase diseases associated with air pollution and aeroallergens. Children are particularly vulnerable to these health outcomes because of their potentially greater exposures, greater sensitivity to certain exposures, and their dependence on caregivers.

Farm Simulation: a tool for evaluating the mitigation of greenhouse gas emissions and the adaptation of dairy production to climate change

USDA-ARS?s Scientific Manuscript database

Farms both produce greenhouse gas emissions that drive human-induced climate change and are impacted by that climate change. Whole farm and global climate models provide useful tools for studying the benefits and costs of greenhouse gas mitigation and the adaptation of farms to changing climate. The...

Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT

NASA Technical Reports Server (NTRS)

Maxwell, Thomas

2012-01-01

Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets.

Higher climatological temperature sensitivity of soil carbon in cold than warm climates

NASA Astrophysics Data System (ADS)

Koven, Charles D.; Hugelius, Gustaf; Lawrence, David M.; Wieder, William R.

2017-11-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). To assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. Here, we show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.

Solomon M. Hsiang Receives 2013 Science for Solutions Award: Citation

NASA Astrophysics Data System (ADS)

Oppenheimer, Michael

2014-01-01

Solomon Hsiang is representative of a new generation in the geosciences community, whose work spans several disciplines, drawing on methods and concepts from far outside the traditional physical science domain in order to make progress on difficult questions at the intersection of natural science, social science, and public policy. Broadly speaking, by examining how humanity has responded to climate variability and change in the distant and recent past, Sol's research elucidates the question of how humanity may respond to a changing climate in the future. Combining large, independent sets of social science, meteorological, and climatological data and analyzing them with tools more common in microeconomics than natural science, Sol, still at an early stage of his career, has made critical contributions to an incipient revolution in our understanding of the sensitivity and adaptability of humans and their social arrangements to climate variability and change. Such insights will greatly improve the information base from which effective public policy is developed.

Climate Change Resilience Planning at the Department of Energy's Savannah River Site

NASA Astrophysics Data System (ADS)

Werth, D. W.; Johnson, A.

2015-12-01

The Savannah River National Laboratory (SRNL) is developing a site sustainability plan for the Department of Energy's Savannah River Site (SRS) in South Carolina in accordance with Executive Order 13693, which charges each DOE agency with "identifying and addressing projected impacts of climate change" and "calculating the potential cost and risk to mission associated with agency operations". The plan will comprise i) projections of climate change, ii) surveys of site managers to estimate the effects of climate change on site operations, and iii) a determination of adaptive actions. Climate change projections for SRS are obtained from multiple sources, including an online repository of downscaled global climate model (GCM) simulations of future climate and downscaled GCM simulations produced at SRNL. Taken together, we have projected data for temperature, precipitation, humidity, and wind - all variables with a strong influence on site operations. SRNL is working to engage site facility managers and facilitate a "bottom up" approach to climate change resilience planning, where the needs and priorities of stakeholders are addressed throughout the process. We make use of the Vulnerability Assessment Scoring Tool, an Excel-based program designed to accept as input various climate scenarios ('exposure'), the susceptibility of assets to climate change ('sensitivity'), and the ability of these assets to cope with climate change ('adaptive capacity'). These are combined to produce a series of scores that highlight vulnerabilities. Working with site managers, we have selected the most important assets, estimated their expected response to climate change, and prepared a report highlighting the most endangered facilities. Primary risks include increased energy consumption, decreased water availability, increased forest fire danger, natural resource degradation, and compromised outdoor worker safety in a warmer and more humid climate. Results of this study will aid in driving future management decisions and promoting sustainable practices at SRS.

The sensitivity of current and future forest managers to climate-induced changes in ecological processes.

PubMed

Seidl, Rupert; Aggestam, Filip; Rammer, Werner; Blennow, Kristina; Wolfslehner, Bernhard

2016-05-01

Climate vulnerability of managed forest ecosystems is not only determined by ecological processes but also influenced by the adaptive capacity of forest managers. To better understand adaptive behaviour, we conducted a questionnaire study among current and future forest managers (i.e. active managers and forestry students) in Austria. We found widespread belief in climate change (94.7 % of respondents), and no significant difference between current and future managers. Based on intended responses to climate-induced ecosystem changes, we distinguished four groups: highly sensitive managers (27.7 %), those mainly sensitive to changes in growth and regeneration processes (46.7 %), managers primarily sensitive to regeneration changes (11.2 %), and insensitive managers (14.4 %). Experiences and beliefs with regard to disturbance-related tree mortality were found to particularly influence a manager's sensitivity to climate change. Our findings underline the importance of the social dimension of climate change adaptation, and suggest potentially strong adaptive feedbacks between ecosystems and their managers.

HydroClimATe: hydrologic and climatic analysis toolkit

USGS Publications Warehouse

Dickinson, Jesse; Hanson, Randall T.; Predmore, Steven K.

2014-01-01

The potential consequences of climate variability and climate change have been identified as major issues for the sustainability and availability of the worldwide water resources. Unlike global climate change, climate variability represents deviations from the long-term state of the climate over periods of a few years to several decades. Currently, rich hydrologic time-series data are available, but the combination of data preparation and statistical methods developed by the U.S. Geological Survey as part of the Groundwater Resources Program is relatively unavailable to hydrologists and engineers who could benefit from estimates of climate variability and its effects on periodic recharge and water-resource availability. This report documents HydroClimATe, a computer program for assessing the relations between variable climatic and hydrologic time-series data. HydroClimATe was developed for a Windows operating system. The software includes statistical tools for (1) time-series preprocessing, (2) spectral analysis, (3) spatial and temporal analysis, (4) correlation analysis, and (5) projections. The time-series preprocessing tools include spline fitting, standardization using a normal or gamma distribution, and transformation by a cumulative departure. The spectral analysis tools include discrete Fourier transform, maximum entropy method, and singular spectrum analysis. The spatial and temporal analysis tool is empirical orthogonal function analysis. The correlation analysis tools are linear regression and lag correlation. The projection tools include autoregressive time-series modeling and generation of many realizations. These tools are demonstrated in four examples that use stream-flow discharge data, groundwater-level records, gridded time series of precipitation data, and the Multivariate ENSO Index.

Collaboration pathway(s) using new tools for optimizing operational climate monitoring from space

NASA Astrophysics Data System (ADS)

Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.

2014-10-01

Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the needs of decision makers, scientific investigators and global users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent (2014) rulebased decision engine modeling runs that targeted optimizing the intended NPOESS architecture, becomes a surrogate for global operational climate monitoring architecture(s). This rule-based systems tools provide valuable insight for Global climate architectures, through the comparison and evaluation of alternatives considered and the exhaustive range of trade space explored. A representative optimization of Global ECV's (essential climate variables) climate monitoring architecture(s) is explored and described in some detail with thoughts on appropriate rule-based valuations. The optimization tools(s) suggest and support global collaboration pathways and hopefully elicit responses from the audience and climate science shareholders.

Sensitivity of Alpine Snow and Streamflow Regimes to Climate Changes

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Marks, D. G.; Bernhardt, M.

2014-12-01

Understanding the sensitivity of hydrological processes to climate change in alpine areas with snow dominated regimes is of paramount importance as alpine basins show both high runoff efficiency associated with the melt of the seasonal snowpack and great sensitivity of snow processes to temperature change. In this study, meteorological data measured in a selection of alpine headwaters basins including Reynolds Mountain East, Idaho, USA, Wolf Creek, Yukon in Canada, and Zugspitze Mountain, Germany with climates ranging from arctic to continental temperate were used to study the snow and streamflow sensitivity to climate change. All research sites have detailed multi-decadal meteorological and snow measurements. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a model representing a typical alpine headwater basin discretized into hydrological response units with physically based representations of snow redistribution by wind, complex terrain snowmelt energetics and runoff processes in alpine tundra. The sensitivity of snow hydrology to climate change was investigated by changing air temperature and precipitation using weather generating methods based on the change factors obtained from different climate model projections for future and current periods. The basin mean and spatial variability of peak snow water equivalent, sublimation loss, duration of snow season, snowmelt rates, streamflow peak, and basin discharge were assessed under varying climate scenarios and the most sensitive hydrological mechanisms to the changes in the different alpine climates were detected. The results show that snow hydrology in colder alpine climates is more resilient to warming than that in warmer climates, but that compensatory factors to warming such as reduced blowing snow sublimation loss and reduced melt rate should also be assessed when considering climate change impacts on alpine hydrology.

Plio-Pleistocene climate sensitivity evaluated using high-resolution CO2 records.

PubMed

Martínez-Botí, M A; Foster, G L; Chalk, T B; Rohling, E J; Sexton, P F; Lunt, D J; Pancost, R D; Badger, M P S; Schmidt, D N

2015-02-05

Theory and climate modelling suggest that the sensitivity of Earth's climate to changes in radiative forcing could depend on the background climate. However, palaeoclimate data have thus far been insufficient to provide a conclusive test of this prediction. Here we present atmospheric carbon dioxide (CO2) reconstructions based on multi-site boron-isotope records from the late Pliocene epoch (3.3 to 2.3 million years ago). We find that Earth's climate sensitivity to CO2-based radiative forcing (Earth system sensitivity) was half as strong during the warm Pliocene as during the cold late Pleistocene epoch (0.8 to 0.01 million years ago). We attribute this difference to the radiative impacts of continental ice-volume changes (the ice-albedo feedback) during the late Pleistocene, because equilibrium climate sensitivity is identical for the two intervals when we account for such impacts using sea-level reconstructions. We conclude that, on a global scale, no unexpected climate feedbacks operated during the warm Pliocene, and that predictions of equilibrium climate sensitivity (excluding long-term ice-albedo feedbacks) for our Pliocene-like future (with CO2 levels up to maximum Pliocene levels of 450 parts per million) are well described by the currently accepted range of an increase of 1.5 K to 4.5 K per doubling of CO2.

Linking climate change and fish conservation efforts using spatially explicit decision support tools

Treesearch

Douglas P. Peterson; Seth J. Wenger; Bruce E. Rieman; Daniel J. Isaak

2013-01-01

Fisheries professionals are increasingly tasked with incorporating climate change projections into their decisions. Here we demonstrate how a structured decision framework, coupled with analytical tools and spatial data sets, can help integrate climate and biological information to evaluate management alternatives. We present examples that link downscaled climate...

Equilibrium and Effective Climate Sensitivity

NASA Astrophysics Data System (ADS)

Rugenstein, M.; Bloch-Johnson, J.

2016-12-01

Atmosphere-ocean general circulation models, as well as the real world, take thousands of years to equilibrate to CO2 induced radiative perturbations. Equilibrium climate sensitivity - a fully equilibrated 2xCO2 perturbation - has been used for decades as a benchmark in model intercomparisons, as a test of our understanding of the climate system and paleo proxies, and to predict or project future climate change. Computational costs and limited time lead to the widespread practice of extrapolating equilibrium conditions from just a few decades of coupled simulations. The most common workaround is the "effective climate sensitivity" - defined through an extrapolation of a 150 year abrupt2xCO2 simulation, including the assumption of linear climate feedbacks. The definitions of effective and equilibrium climate sensitivity are often mixed up and used equivalently, and it is argued that "transient climate sensitivity" is the more relevant measure for predicting the next decades. We present an ongoing model intercomparison, the "LongRunMIP", to study century and millennia time scales of AOGCM equilibration and the linearity assumptions around feedback analysis. As a true ensemble of opportunity, there is no protocol and the only condition to participate is a coupled model simulation of any stabilizing scenario simulating more than 1000 years. Many of the submitted simulations took several years to conduct. As of July 2016 the contribution comprises 27 scenario simulations of 13 different models originating from 7 modeling centers, each between 1000 and 6000 years. To contribute, please contact the authors as soon as possible We present preliminary results, discussing differences between effective and equilibrium climate sensitivity, the usefulness of transient climate sensitivity, extrapolation methods, and the state of the coupled climate system close to equilibrium. Caption for the Figure below: Evolution of temperature anomaly and radiative imbalance of 22 simulations with 12 models (color indicates the model). 20 year moving average.

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

NASA Astrophysics Data System (ADS)

Ford, James D.; Pearce, Tristan

2010-01-01

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

Sensitivity of ground - water recharge estimates to climate variability and change, Columbia Plateau, Washington

USGS Publications Warehouse

Vaccaro, John J.

1992-01-01

The sensitivity of groundwater recharge estimates was investigated for the semiarid Ellensburg basin, located on the Columbia Plateau, Washington, to historic and projected climatic regimes. Recharge was estimated for predevelopment and current (1980s) land use conditions using a daily energy-soil-water balance model. A synthetic daily weather generator was used to simulate lengthy sequences with parameters estimated from subsets of the historical record that were unusually wet and unusually dry. Comparison of recharge estimates corresponding to relatively wet and dry periods showed that recharge for predevelopment land use varies considerably within the range of climatic conditions observed in the 87-year historical observation period. Recharge variations for present land use conditions were less sensitive to the same range of historical climatic conditions because of irrigation. The estimated recharge based on the 87-year historical climatology was compared with adjustments to the historical precipitation and temperature records for the same record to reflect CO2-doubling climates as projected by general circulation models (GCMs). Two GCM scenarios were considered: an average of conditions for three different GCMs with CO2 doubling, and a most severe “maximum” case. For the average GCM scenario, predevelopment recharge increased, and current recharge decreased. Also considered was the sensitivity of recharge to the variability of climate within the historical and adjusted historical records. Predevelopment and current recharge were less and more sensitive, respectively, to the climate variability for the average GCM scenario as compared to the variability within the historical record. For the maximum GCM scenario, recharge for both predevelopment and current land use decreased, and the sensitivity to the CO2-related climate change was larger than sensitivity to the variability in the historical and adjusted historical climate records.

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

PubMed

Alsalem, Gheed; Bowie, Paul; Morrison, Jillian

2018-05-10

The perceived importance of safety culture in improving patient safety and its impact on patient outcomes has led to a growing interest in the assessment of safety climate in healthcare organizations; however, the rigour with which safety climate tools were developed and psychometrically tested was shown to be variable. This paper aims to identify and review questionnaire studies designed to measure safety climate in acute hospital settings, in order to assess the adequacy of reported psychometric properties of identified tools. A systematic review of published empirical literature was undertaken to examine sample characteristics and instrument details including safety climate dimensions, origin and theoretical basis, and extent of psychometric evaluation (content validity, criterion validity, construct validity and internal reliability). Five questionnaire tools, designed for general evaluation of safety climate in acute hospital settings, were included. Detailed inspection revealed ambiguity around concepts of safety culture and climate, safety climate dimensions and the methodological rigour associated with the design of these measures. Standard reporting of the psychometric properties of developed questionnaires was variable, although evidence of an improving trend in the quality of the reported psychometric properties of studies was noted. Evidence of the theoretical underpinnings of climate tools was limited, while a lack of clarity in the relationship between safety culture and patient outcome measures still exists. Evidence of the adequacy of the psychometric development of safety climate questionnaire tools is still limited. Research is necessary to resolve the controversies in the definitions and dimensions of safety culture and climate in healthcare and identify related inconsistencies. More importance should be given to the appropriate validation of safety climate questionnaires before extending their usage in healthcare contexts different from those in which they were originally developed. Mixed methods research to understand why psychometric assessment and measurement reporting practices can be inadequate and lacking in a theoretical basis is also necessary.

Use of remote sensing and GIS in mapping the environmental sensitivity areas for desertification of Egyptian territory

NASA Astrophysics Data System (ADS)

Gad, A.; Lotfy, I.

2008-06-01

Desertification is defined in the first art of the convention to combat desertification as "land degradation in arid, semiarid and dry sub-humid areas resulting from climatic variations and human activities". Its consequence include a set of important processes which are active in arid and semi arid environment, where water is the main limiting factor of land use performance in such ecosystem . Desertification indicators or the groups of associated indicators should be focused on a single process. They should be based on available reliable information sources, including remotely sensed images, topographic data (maps or DEM'S), climate, soils and geological data. The current work aims to map the Environmental Sensitivity Areas (ESA's) to desertification in whole territory of Egypt at a scale of 1:1 000 000. ETM satellite images, geologic and soil maps were used as main sources for calculating the index of Environmental Sensitivity Areas (ESAI) for desertification. The algorism is adopted from MEDALLUS methodology as follows; ESAI = (SQI * CQI * VQI)1/3 Where SQI is the soil quality index, CQI is the climate quality index and VQI is the vegetation quality index. The SQI is based on rating the parent material, slope, soil texture, and soil depth. The VQI is computed on bases of rating three categories (i.e. erosion protection, drought resistance and plant cover). The CQI is based on the aridity index, derived from values of annual rainfall and potential evapotranspiration. Arc-GIS 9 software was used for the computation and sensitivity maps production. The results show that the soil of the Nile Valley are characterized by a moderate SQI, however the those in the interference zone are low soil quality indexed. The dense vegetation of the valley has raised its VQI to be good, however coastal areas are average and interference zones are low. The maps of ESA's for desertification show that 86.1% of Egyptian territory is classified as very sensitive areas, while 4.3% as Moderately sensitive, and 9.6% as sensitive. It can be concluded that implementing the maps of sensitivity to desertification is rather useful in the arid and semi arid areas as they give more likely quantitative trend for frequency of sensitive areas. The integration of different factors contributing to desertification sensitivity may lead to plan a successful combating. The usage of space data and GIS proved to be suitable tools to rely estimation and to fulfill the needed large computational requirements. They are also useful in visualizing the sensitivity situation of different desertification parameters.

Drought sensitivity changes over the last century at the North American savanna-forest boundary

NASA Astrophysics Data System (ADS)

Heilman, K.; McLachlan, J. S.

2017-12-01

Future environmental changes can affect the sensitivity of tree growth to climate. Theses changes are of particular concern at biome boundaries where tree distribution could shift as a result of changes in both drought and drought sensitivity. One such region is the North American savanna-forest boundary, where increased CO2 and droughts could alter savanna and forest ecosystem distributions in two contrasting ways: 1). More severe droughts may increase drought sensitivity, favoring open savanna ecosystems or, 2). Increases in water use efficiency resulting from higher atmospheric CO2 may decrease drought sensitivity, promoting forest expansion. This study sought to understand whether the past 100 years of climate and CO2 changes have impacted regional tree growth-climate sensitivity. To test for these climate sensitivity changes, we measured the sensitivity of Quercus spp. radial growth to Palmer Drought Severity Index (PDSI). Tree growth sensitivity to climate can vary according to many factors, including: stand structure, available moisture, and tree age. To control for these factors, we sampled tree growth-climate responses at sites in both open and closed forests, and at both low and high annual precipitation. Within each site, we compared growth responses to climate between trees established under high CO2 conditions after 1950 (high CO2 young), and tree established before 1950 under low CO2 levels (low CO2 young). At most sites, low CO2 young have a higher drought sensitivity than higher CO2 young. These changes in the sensitivity to drought are consistent with CO2 enhancement of water use efficiency. Furthermore, these differences in drought sensitivity are higher at sites with high temperature and low precipitation, suggesting that the alleviation of drought is more likely in hot and dry regions. Thus, if CO2 enhancement is indeed occurring in these systems, lower growth sensitivity to drought in hot and dry regions could favor increased forest growth. If changes in drought sensitivity scale to ecosystem level, decreased drought sensitivity may have helped promote regional forest expansion.

How to Assess Vulnerabilities of Water Policies to Global Change?

NASA Astrophysics Data System (ADS)

Kumar, A.; Haasnoot, M.; Weijs, S.

2017-12-01

Water managers are confronted with uncertainties arising from hydrological, societal, economical and political drivers. To manage these uncertainties two paradigms have been identified: top-down and bottom-up approaches. Top-down or prediction-based approaches use socio-economic scenarios together with a discrete set of GCM projections (often downscaled) to assess the expected impact of drivers and policies on water resource system through various hydrological and social systems models. Adaptation strategies to alleviate these impacts are then identified and tested against the scenarios. To address GCM and downscaling uncertainties, these approaches put more focus on climate predictions, rather than the decision problem itself. Triggered by the wish to have a more scenario-neutral approach and address downscaling uncertainties, recent analyses have been shifted towards vulnerability-based (bottom-up or decision-centric) approaches. They begin at the local scale by addressing socio-economic responses to climate, often involving stakeholder's input; identify vulnerabilities under a larger sample of plausible futures and evaluate sensitivity and robustness of possible adaptation options. Several bottom-up approaches have emerged so far and are increasingly recommended. Fundamentally they share several core ideas, however, subtle differences exist in vulnerability assessment, visualization tools for exploring vulnerabilities and computational methods used for identifying robust water policies. Through this study, we try to identify how these approaches are progressing, how the climate and non-climate uncertainties are being confronted and how to integrate existing and new tools. We find that choice of a method may depend on the number of vulnerability drivers identified and type of threshold levels (environmental conditions or policy objectives) defined. Certain approaches are suited well for assessing adaptive capacities, tipping points and sequencing of decisions. However, visualization of the vulnerability domain is still challenging if multiple drivers are present. New emerging tools are focused on generating synthetic scenarios, addressing multiple objectives, linking decision-making frameworks to adaptation pathways and communicating risks to the stakeholders.

Potential New Lidar Observations for Cloud Studies

NASA Technical Reports Server (NTRS)

Winker, Dave; Hu, Yong; Narir, Amin; Cai, Xia

2015-01-01

The response of clouds to global warming represents a major uncertainty in estimating climate sensitivity. These uncertainties have been tracked to shallow marine clouds in the tropics and subtropics. CALIOP observations have already been used extensively to evaluate model predictions of shallow cloud fraction and top height (Leahy et al. 2013; Nam et al 2012). Tools are needed to probe the lowest levels of the troposphere. The large footprint of satellite lidars gives large multiple scattering from clouds which presents new possibilities for cloud retrievals to constrain model predictions.

Sensitivity of Ocean Chemistry and Oxygen Change to the Uncertainty in Climate Change

NASA Astrophysics Data System (ADS)

Cao, L.; Wang, S.; Zheng, M.; Zhang, H.

2014-12-01

With increasing atmospheric CO2 and climate change, global ocean is undergoing substantial physical and biogeochemical changes. In particular, changes in ocean oxygen and carbonate chemistry have great implication for marine biota. There is considerable uncertainty in the projections of future climate change, and it is unclear how the uncertainty in climate change would affect the projection of ocean oxygen and carbonate chemistry. To examine the effect of climate change on ocean oxygen and carbonate chemistry, we used an Earth system model of intermediate complexity to perform simulations that are driven by atmospheric CO2 concentration pathway of RCP 8.5 with climate sensitivity varying from 0.0°C to 4.5 °C. Climate change affects carbonate chemistry and oxygen mainly through its impact on ocean temperature, ocean ventilation, and concentration of dissolved inorganic carbon and alkalinity. Our simulations show that climate change mitigates the decrease of carbonate ions at the ocean surface but has negligible effect on surface ocean pH. Averaged over the whole ocean, climate change acts to decrease oxygen concentration but mitigates the CO2-induced reduction of carbonate ion and pH. In our simulations, by year 2500, every degree increase of climate sensitivity warms the ocean by 0.8 °C and reduces ocean-mean dissolved oxygen concentration by 5.0%. Meanwhile, every degree increase of climate sensitivity buffers CO2-induced reduction in ocean-mean carbonate ion concentration and pH by 3.4% and 0.02 units, respectively. Our study demonstrates different sensitivities of ocean temperature, carbonate chemistry, and oxygen, in terms of both the sign and magnitude, to the amount of climate change, which have great implications for understanding the response of ocean biota to climate change.

Vulnerability of the global terrestrial ecosystems to climate change.

PubMed

Li, Delong; Wu, Shuyao; Liu, Laibao; Zhang, Yatong; Li, Shuangcheng

2018-05-27

Climate change has far-reaching impacts on ecosystems. Recent attempts to quantify such impacts focus on measuring exposure to climate change but largely ignore ecosystem resistance and resilience, which may also affect the vulnerability outcomes. In this study, the relative vulnerability of global terrestrial ecosystems to short-term climate variability was assessed by simultaneously integrating exposure, sensitivity, and resilience at a high spatial resolution (0.05°). The results show that vulnerable areas are currently distributed primarily in plains. Responses to climate change vary among ecosystems and deserts and xeric shrublands are the most vulnerable biomes. Global vulnerability patterns are determined largely by exposure, while ecosystem sensitivity and resilience may exacerbate or alleviate external climate pressures at local scales; there is a highly significant negative correlation between exposure and sensitivity. Globally, 61.31% of the terrestrial vegetated area is capable of mitigating climate change impacts and those areas are concentrated in polar regions, boreal forests, tropical rainforests, and intact forests. Under current sensitivity and resilience conditions, vulnerable areas are projected to develop in high Northern Hemisphere latitudes in the future. The results suggest that integrating all three aspects of vulnerability (exposure, sensitivity, and resilience) may offer more comprehensive and spatially explicit adaptation strategies to reduce the impacts of climate change on terrestrial ecosystems. © 2018 John Wiley & Sons Ltd.

BASINS and WEPP Climate Assessment Tools (CAT): Case Study Guide to Potential Applications (External Review Draft)

EPA Science Inventory

This draft report supports application of two recently developed water modeling tools, the BASINS and WEPP climate assessment tools. The report presents a series of short case studies designed to illustrate the capabilities of these tools for conducting scenario based assessments...

Tropical forest soil microbes and climate warming: An Andean-Amazon gradient and `SWELTR'

NASA Astrophysics Data System (ADS)

Nottingham, A.; Turner, B. L.; Fierer, N.; Whitaker, J.; Ostle, N. J.; McNamara, N. P.; Bardgett, R.; Silman, M.; Bååth, E.; Salinas, N.; Meir, P.

2017-12-01

Climate warming predicted for the tropics in the coming century will result in average temperatures under which no closed canopy forest exists today. There is, therefore, great uncertainty associated with the direction and magnitude of feedbacks between tropical forests and our future climate - especially relating to the response of soil microbes and the third of global soil carbon contained in tropical forests. While warming experiments are yet to be performed in tropical forests, natural temperature gradients are powerful tools to investigate temperature effects on soil microbes. Here we draw on studies from a 3.5 km elevation gradient - and 20oC mean annual temperature gradient - in Peruvian tropical forest, to investigate how temperature affects the structure of microbial communities, microbial metabolism, enzymatic activity and soil organic matter cycling. With decreased elevation, soil microbial diversity increased and community composition shifted, from taxa associated with oligotrophic towards copiotrophic traits. A key role for temperature in shaping these patterns was demonstrated by a soil translocation experiment, where temperature-manipulation altered the relative abundance of specific taxa. Functional implications of these community composition shifts were indicated by changes in enzyme activities, the temperature sensitivity of bacterial and fungal growth rates, and the presence of temperature-adapted iso-enzymes at different elevations. Studies from a Peruvian elevation transect indicated that soil microbial communities are adapted to long-term (differences with elevation) and short-term (translocation responses) temperature changes. These findings indicate the potential for adaptation of soil microbes in tropical soils to future climate warming. However, in order to evaluate the sensitivity of these processes to climate warming in lowland forests, in situ experimentation is required. Finally, we describe SWELTR (Soil Warming Experiment in Lowland Tropical Rainforest), a new soil warming experiment being undertaken on Barro Colorado Island, Panama, designed to improve our understanding of biogeochemical feedbacks to climate warming in lowland tropical forests.

Different parts, different stories: climate sensitivity of growth is stronger in root collars vs. stems in tundra shrubs.

PubMed

Ropars, Pascale; Angers-Blondin, Sandra; Gagnon, Marianne; Myers-Smith, Isla H; Lévesque, Esther; Boudreau, Stéphane

2017-08-01

Shrub densification has been widely reported across the circumpolar arctic and subarctic biomes in recent years. Long-term analyses based on dendrochronological techniques applied to shrubs have linked this phenomenon to climate change. However, the multi-stemmed structure of shrubs makes them difficult to sample and therefore leads to non-uniform sampling protocols among shrub ecologists, who will favor either root collars or stems to conduct dendrochronological analyses. Through a comparative study of the use of root collars and stems of Betula glandulosa, a common North American shrub species, we evaluated the relative sensitivity of each plant part to climate variables and assessed whether this sensitivity is consistent across three different types of environments in northwestern Québec, Canada (terrace, hilltop and snowbed). We found that root collars had greater sensitivity to climate than stems and that these differences were maintained across the three types of environments. Growth at the root collar was best explained by spring precipitation and summer temperature, whereas stem growth showed weak and inconsistent responses to climate variables. Moreover, sensitivity to climate was not consistent among plant parts, as individuals having climate-sensitive root collars did not tend to have climate-sensitive stems. These differences in sensitivity of shrub parts to climate highlight the complexity of resource allocation in multi-stemmed plants. Whereas stem initiation and growth are driven by microenvironmental variables such as light availability and competition, root collars integrate the growth of all plant parts instead, rendering them less affected by mechanisms such as competition and more responsive to signals of global change. Although further investigations are required to determine the degree to which these findings are generalizable across the tundra biome, our results indicate that consistency and caution in the choice of plant parts are a key consideration for the success of future dendroclimatological studies on shrubs. © 2017 John Wiley & Sons Ltd.

Sensitivity of water resources in the Delaware River basin to climate variability and change

USGS Publications Warehouse

Ayers, Mark A.; Wolock, David M.; McCabe, Gregory J.; Hay, Lauren E.; Tasker, Gary D.

1994-01-01

Because of the greenhouse effect, projected increases in atmospheric carbon dioxide levels might cause global warming, which in turn could result in changes in precipitation patterns and evapotranspiration and in increases in sea level. This report describes the greenhouse effect; discusses the problems and uncertainties associated with the detection, prediction, and effects of climate change; and presents the results of sensitivity analyses of how climate change might affect water resources in the Delaware River basin. Sensitivity analyses suggest that potentially serious shortfalls of certain water resources in the basin could result if some scenarios for climate change come true . The results of model simulations of the basin streamflow demonstrate the difficulty in distinguishing the effects that climate change versus natural climate variability have on streamflow and water supply . The future direction of basin changes in most water resources, furthermore, cannot be precisely determined because of uncertainty in current projections of regional temperature and precipitation . This large uncertainty indicates that, for resource planning, information defining the sensitivities of water resources to a range of climate change is most relevant . The sensitivity analyses could be useful in developing contingency plans for evaluating and responding to changes, should they occur.

Enabling Research Tools for Sustained Climate Assessment

NASA Technical Reports Server (NTRS)

Leidner, Allison K.; Bosilovich, Michael G.; Jasinski, Michael F.; Nemani, Ramakrishna R.; Waliser, Duane Edward; Lee, Tsengdar J.

2016-01-01

The U.S. Global Change Research Program Sustained Assessment process benefits from long-term investments in Earth science research that enable the scientific community to conduct assessment-relevant science. To this end, NASA initiated several research programs over the past five years to support the Earth observation community in developing indicators, datasets, research products, and tools to support ongoing and future National Climate Assessments. These activities complement NASA's ongoing Earth science research programs. One aspect of the assessment portfolio funds four "enabling tools" projects at NASA research centers. Each tool leverages existing capacity within the center, but has developed tailored applications and products for National Climate Assessments. The four projects build on the capabilities of a global atmospheric reanalysis (MERRA-2), a continental U.S. land surface reanalysis (NCA-LDAS), the NASA Earth Exchange (NEX), and a Regional Climate Model Evaluation System (RCMES). Here, we provide a brief overview of each enabling tool, highlighting the ways in which it has advanced assessment science to date. We also discuss how the assessment community can access and utilize these tools for National Climate Assessments and other sustained assessment activities.

Palaeoclimatic insights into future climate challenges.

PubMed

Alley, Richard B

2003-09-15

Palaeoclimatic data document a sensitive climate system subject to large and perhaps difficult-to-predict abrupt changes. These data suggest that neither the sensitivity nor the variability of the climate are fully captured in some climate-change projections, such as the Intergovernmental Panel on Climate Change (IPCC) Summary for Policymakers. Because larger, faster and less-expected climate changes can cause more problems for economies and ecosystems, the palaeoclimatic data suggest the hypothesis that the future may be more challenging than anticipated in ongoing policy making. Large changes have occurred repeatedly with little net forcing. Increasing carbon dioxide concentration appears to have globalized deglacial warming, with climate sensitivity near the upper end of values from general circulation models (GCMs) used to project human-enhanced greenhouse warming; data from the warm Cretaceous period suggest a similarly high climate sensitivity to CO(2). Abrupt climate changes of the most recent glacial-interglacial cycle occurred during warm as well as cold times, linked especially to changing North Atlantic freshwater fluxes. GCMs typically project greenhouse-gas-induced North Atlantic freshening and circulation changes with notable but not extreme consequences; however, such models often underestimate the magnitude, speed or extent of past changes. Targeted research to assess model uncertainties would help to test these hypotheses.

Logit-normal mixed model for Indian monsoon precipitation

NASA Astrophysics Data System (ADS)

Dietz, L. R.; Chatterjee, S.

2014-09-01

Describing the nature and variability of Indian monsoon precipitation is a topic of much debate in the current literature. We suggest the use of a generalized linear mixed model (GLMM), specifically, the logit-normal mixed model, to describe the underlying structure of this complex climatic event. Four GLMM algorithms are described and simulations are performed to vet these algorithms before applying them to the Indian precipitation data. The logit-normal model was applied to light, moderate, and extreme rainfall. Findings indicated that physical constructs were preserved by the models, and random effects were significant in many cases. We also found GLMM estimation methods were sensitive to tuning parameters and assumptions and therefore, recommend use of multiple methods in applications. This work provides a novel use of GLMM and promotes its addition to the gamut of tools for analysis in studying climate phenomena.

Meeting the Next Generation Science Standards Through "Rediscovered" Climate Model Experiments

NASA Astrophysics Data System (ADS)

Sohl, L. E.; Chandler, M. A.; Zhou, J.

2013-12-01

Since the Educational Global Climate Model (EdGCM) Project made its debut in January 2005, over 150 institutions have employed EdGCM software for a variety of uses ranging from short lab exercises to semester-long and year-long thesis projects. The vast majority of these EdGCM adoptees have been at the undergraduate and graduate levels, with few users at the K-12 level. The K-12 instructors who have worked with EdGCM in professional development settings have commented that, although EdGCM can be used to illustrate a number of the Disciplinary Core Ideas and connects to many of the Common Core State Standards across subjects and grade levels, significant hurdles preclude easy integration of EdGCM into their curricula. Time constraints, a scarcity of curriculum materials, and classroom technology are often mentioned as obstacles in providing experiences to younger grade levels in realistic climate modeling research. Given that the NGSS incorporates student performance expectations relating to Earth System Science, and to climate science and the human dimension in particular, we feel that a streamlined version of EdGCM -- one that eliminates the need to run the climate model on limited computing resources, and provides a more guided climate modeling experience -- would be highly beneficial for the K-12 community. This new tool currently under development, called EzGCM, functions through a browser interface, and presents "rediscovery experiments" that allow students to do their own exploration of model output from published climate experiments, or from sensitivity experiments designed to illustrate how climate models as well as the climate system work. The experiments include background information and sample questions, with more extensive notes for instructors so that the instructors can design their own reflection questions or follow-on activities relating to physical or human impacts, as they choose. An added benefit of the EzGCM tool is that, like EdGCM, it helps illustrate the process of doing research on a complex topic, in a way that builds upon earlier experiences in inquiry-based learning. By having students work through a multi-stage process that requires them to plan several steps ahead, through data processing, analysis and interpretation, they learn how to do research in addition to improving their understanding of climate change.

Simulating the Response of Urban Water Quality to Climate and Land Use Change in Partially Urbanized Basins

NASA Astrophysics Data System (ADS)

Sun, N.; Yearsley, J. R.; Nijssen, B.; Lettenmaier, D. P.

2014-12-01

Urban stream quality is particularly susceptible to extreme precipitation events and land use change. Although the projected effects of extreme events and land use change on hydrology have been resonably well studied, the impacts on urban water quality have not been widely examined due in part to the scale mismatch between global climate models and the spatial scales required to represent urban hydrology and water quality signals. Here we describe a grid-based modeling system that integrates the Distributed Hydrology Soil Vegetation Model (DHSVM) and urban water quality module adpated from EPA's Storm Water Management Model (SWMM) and Soil and water assessment tool (SWAT). Using the model system, we evaluate, for four partially urbanized catchments within the Puget Sound basin, urban water quality under current climate conditions, and projected potential changes in urban water quality associated with future changes in climate and land use. We examine in particular total suspended solids, toal nitrogen, total phosphorous, and coliform bacteria, with catchment representations at the 150-meter spatial resolution and the sub-daily timestep. We report long-term streamflow and water quality predictions in response to extreme precipitation events of varying magnitudes in the four partially urbanized catchments. Our simulations show that urban water quality is highly sensitive to both climatic and land use change.

Climate change impact assessment on hydrology of a small watershed using semi-distributed model

NASA Astrophysics Data System (ADS)

Pandey, Brij Kishor; Gosain, A. K.; Paul, George; Khare, Deepak

2017-07-01

This study is an attempt to quantify the impact of climate change on the hydrology of Armur watershed in Godavari river basin, India. A GIS-based semi-distributed hydrological model, soil and water assessment tool (SWAT) has been employed to estimate the water balance components on the basis of unique combinations of slope, soil and land cover classes for the base line (1961-1990) and future climate scenarios (2071-2100). Sensitivity analysis of the model has been performed to identify the most critical parameters of the watershed. Average monthly calibration (1987-1994) and validation (1995-2000) have been performed using the observed discharge data. Coefficient of determination (R2), Nash-Sutcliffe efficiency (ENS) and root mean square error (RMSE) were used to evaluate the model performance. Calibrated SWAT setup has been used to evaluate the changes in water balance components of future projection over the study area. HadRM3, a regional climatic data, have been used as input of the hydrological model for climate change impact studies. In results, it was found that changes in average annual temperature (+3.25 °C), average annual rainfall (+28 %), evapotranspiration (28 %) and water yield (49 %) increased for GHG scenarios with respect to the base line scenario.

Advances of NOAA Training Program in Climate Services

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.

2012-12-01

Since 2002, NOAA's National Weather Service (NWS) Climate Services Division (CSD) has offered numerous training opportunities to NWS staff. After eight-years of development, the training program offers three instructor-led courses and roughly 25 online (distance learning) modules covering various climate topics, such as: climate data and observations, climate variability and change, and NWS national / local climate products (tools, skill, and interpretation). Leveraging climate information and expertise available at all NOAA line offices and partners allows for the delivery of the most advanced knowledge and is a very critical aspect of the training program. The emerging NOAA Climate Service (NCS) requires a well-trained, climate-literate workforce at the local level capable of delivering NOAA's climate products and services as well as providing climate-sensitive decision support. NWS Weather Forecast Offices and River Forecast Centers presently serve as local outlets for the NCS climate services. Trained NWS climate service personnel use proactive and reactive approaches and professional education methods in communicating climate variability and change information to local users. Both scientifically-sound messages and amiable communication techniques are important in developing an engaged dialog between the climate service providers and users. Several pilot projects have been conducted by the NWS CSD this past year that apply the program's training lessons and expertise to specialized external user group training. The technical user groups included natural resources managers, engineers, hydrologists, and planners for transportation infrastructure. Training of professional user groups required tailoring instructions to the potential applications for each group of users. Training technical users identified the following critical issues: (1) knowledge of target audience expectations, initial knowledge status, and potential use of climate information; (2) leveraging partnership with climate services providers; and, (3) applying 3H training approach, where the first H stands for Head (trusted science), the second H stands for Heart (make it easy), and the third H for Hand (support with applications).

Training NOAA Staff on Effective Communication Methods with Local Climate Users

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Mayes, B.

2011-12-01

Since 2002 NOAA National Weather Service (NWS) Climate Services Division (CSD) offered training opportunities to NWS staff. As a result of eight-year-long development of the training program, NWS offers three training courses and about 25 online distance learning modules covering various climate topics: climate data and observations, climate variability and change, NWS national and local climate products, their tools, skill, and interpretation. Leveraging climate information and expertise available at all NOAA line offices and partners allows delivery of the most advanced knowledge and is a very critical aspect of the training program. NWS challenges in providing local climate services includes effective communication techniques on provide highly technical scientific information to local users. Addressing this challenge requires well trained, climate-literate workforce at local level capable of communicating the NOAA climate products and services as well as provide climate-sensitive decision support. Trained NWS climate service personnel use proactive and reactive approaches and professional education methods in communicating climate variability and change information to local users. Both scientifically-unimpaired messages and amiable communication techniques such as story telling approach are important in developing an engaged dialog between the climate service providers and users. Several pilot projects NWS CSD conducted in the past year applied the NWS climate services training program to training events for NOAA technical user groups. The technical user groups included natural resources managers, engineers, hydrologists, and planners for transportation infrastructure. Training of professional user groups required tailoring the instructions to the potential applications of each group of users. Training technical user identified the following critical issues: (1) Knowledge of target audience expectations, initial knowledge status, and potential use of climate information; (2) Leveraging partnership with climate services providers; and, (3) Applying 3H training approach, where the first H stands for Head (trusted science), the second H stands for Heart (make it easy), and the third H for Hand (support with applications).

Hydrologic and water quality sensitivity to climate and land ...

EPA Pesticide Factsheets

This page describes a current EPA ORD project. No project report or other download is available at this time. Please see the section Next Steps below for a timeline of anticipated products of this work. Background: Projected changes in climate during the next century could cause or contribute to increased flooding, drought, water quality degradation, and ecosystem impairment. The effects of climate change in different watersheds will vary due to regional differences in climate change, physiographic setting, and interaction with land-use, pollutant sources, and water management in different locations. EPA is conducting watershed modeling to develop hydrologic and water quality change scenarios for 20 relatively large U.S. watersheds. Watershed modeling will be conducted using the Hydrologic Simulation Program-FORTRAN (HSPF) and Soil Water Assessment Tool (SWAT) watershed models. Study areas range from about 10,000-15,000 square miles in size, and will cover nearly every ecoregion in the United States and a range of hydro-climatic conditions. A range of hydrologic and water quality endpoints will be determined for each watershed simulation. Endpoints will be selected to inform upon a range of stream flow, water quality, aquatic ecosystem, and EPA program management goals and targets. Model simulations will be conducted to evaluate a range of projected future (2040-2070) changes in climate and land-use. Simulations will include baseline conditions,

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-10-20

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

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

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

End-member modelling as a tool for climate reconstruction-An Eastern Mediterranean case study.

PubMed

Beuscher, Sarah; Krüger, Stefan; Ehrmann, Werner; Schmiedl, Gerhard; Milker, Yvonne; Arz, Helge; Schulz, Hartmut

2017-01-01

The Eastern Mediterranean Sea is a sink for terrigenous sediments from North Africa, Europe and Asia Minor. Its sediments therefore provide valuable information on the climate dynamics in the source areas and the associated transport processes. We present a high-resolution dataset of sediment core M40/4_SL71, which was collected SW of Crete and spans the last ca. 180 kyr. We analysed the clay mineral composition, the grain size distribution within the silt fraction, and the abundance of major and trace elements. We tested the potential of end-member modelling on these sedimentological datasets as a tool for reconstructing the climate variability in the source regions and the associated detrital input. For each dataset, we modelled three end members. All end members were assigned to a specific provenance and sedimentary process. In total, three end members were related to the Saharan dust input, and five were related to the fluvial sediment input. One end member was strongly associated with the sapropel layers. The Saharan dust end members of the grain size and clay mineral datasets generally suggest enhanced dust export into the Eastern Mediterranean Sea during the dry phases with short-term increases during Heinrich events. During the African Humid Periods, dust export was reduced but may not have completely ceased. The loading patterns of two fluvial end members show a strong relationship with the Northern Hemisphere insolation, and all fluvial end members document enhanced input during the African Humid Periods. The sapropel end member most likely reflects the fixation of redox-sensitive elements within the anoxic sapropel layers. Our results exemplify that end-member modelling is a valuable tool for interpreting extensive and multidisciplinary datasets.

End-member modelling as a tool for climate reconstruction—An Eastern Mediterranean case study

PubMed Central

Krüger, Stefan; Ehrmann, Werner; Schmiedl, Gerhard; Milker, Yvonne; Arz, Helge; Schulz, Hartmut

2017-01-01

The Eastern Mediterranean Sea is a sink for terrigenous sediments from North Africa, Europe and Asia Minor. Its sediments therefore provide valuable information on the climate dynamics in the source areas and the associated transport processes. We present a high-resolution dataset of sediment core M40/4_SL71, which was collected SW of Crete and spans the last ca. 180 kyr. We analysed the clay mineral composition, the grain size distribution within the silt fraction, and the abundance of major and trace elements. We tested the potential of end-member modelling on these sedimentological datasets as a tool for reconstructing the climate variability in the source regions and the associated detrital input. For each dataset, we modelled three end members. All end members were assigned to a specific provenance and sedimentary process. In total, three end members were related to the Saharan dust input, and five were related to the fluvial sediment input. One end member was strongly associated with the sapropel layers. The Saharan dust end members of the grain size and clay mineral datasets generally suggest enhanced dust export into the Eastern Mediterranean Sea during the dry phases with short-term increases during Heinrich events. During the African Humid Periods, dust export was reduced but may not have completely ceased. The loading patterns of two fluvial end members show a strong relationship with the Northern Hemisphere insolation, and all fluvial end members document enhanced input during the African Humid Periods. The sapropel end member most likely reflects the fixation of redox-sensitive elements within the anoxic sapropel layers. Our results exemplify that end-member modelling is a valuable tool for interpreting extensive and multidisciplinary datasets. PMID:28934332

A De Novo Tool to Measure the Preclinical Learning Climate of Medical Faculties in Turkey

ERIC Educational Resources Information Center

Yilmaz, Nilufer Demiral; Velipasaoglu, Serpil; Sahin, Hatice; Basusta, Bilge Uzun; Midik, Ozlem; Coskun, Ozlem; Budakoglu, Isil Irem; Mamakli, Sumer; Tengiz, Funda Ifakat; Durak, Halil Ibrahim; Ozan, Sema

2015-01-01

Although several scales are used to measure general and clinical learning climates, there are no scales that assess the preclinical learning climate. Therefore, the purpose of this study was to develop an effective measurement tool in order to assess the preclinical learning climate. In this cross-sectional study, data were collected from 3,540…

Sensitivity and rapidity of vegetational response to abrupt climate change

NASA Technical Reports Server (NTRS)

Peteet, D.

2000-01-01

Rapid climate change characterizes numerous terrestrial sediment records during and since the last glaciation. Vegetational response is best expressed in terrestrial records near ecotones, where sensitivity to climate change is greatest, and response times are as short as decades.

National Forest management options in response to climate change

Treesearch

Forest Service U.S. Department of Agriculture

2009-01-01

The effect of climate change on ecosystem structure, function, and services will depend on the ecosystem's degree of sensitivity to climate change, the natural ability of plants and animals to adapt, and the availability of effective management options. Sensitivity to climate change is a function of ecosystem health and environmental stresses such as air pollution...

Lichen communities and species indicate climate thresholds in southeast and south-central Alaska, USA

Treesearch

Heather T. Root; Bruce McCune; Sarah Jovan

2014-01-01

Because of their unique physiology, lichen communities are highly sensitive to climatic conditions,making them ideal bioindicators for climate change. Southeast and south-central Alaska host diverse and abundant lichen communities and are faced with a more rapidly changing climate than many more southerly latitudes. We develop sensitive lichen-based indicators for...

Climate-Smart Seedlot Selection Tool: Reforestation and Restoration for the 21st Century

NASA Astrophysics Data System (ADS)

Stevenson-Molnar, N.; Howe, G.; St Clair, B.; Bachelet, D. M.; Ward, B. C.

2017-12-01

Local populations of trees are generally adapted to their local climates. Historically, this has meant that local seed zones based on geography and elevation have been used to guide restoration and reforestation. In the face of climate change, seeds from local sources will likely be subjected to climates significantly different from those to which they are currently adapted. The Seedlot Selection Tool (SST) offers a new approach for matching seed sources with planting sites based on future climate scenarios. The SST is a mapping program designed for forest managers and researchers. Users can use the tool to to find seedlots for a given planting site, or to find potential planting sites for a given seedlot. Users select a location (seedlot or planting site), climate scenarios (a climate to which seeds are adapted, and a current or future climate scenario), climate variables, and transfer limits (the maximum climatic distance that is considered a suitable match). Transfer limits are provided by the user, or derived from the range of values within a geographically defined seed zone. The tool calculates scores across the landscape based on an area's similarity, in a multivariate climate space, to the input. Users can explore results on an interactive map, and export PDF and PowerPoint reports, including a map of the results along with the inputs used. Planned future improvements include support for non-forest use cases and ability to download results as GeoTIFF data. The Seedlot Selection Tool and its source code are available online at https://seedlotselectiontool.org. It is co-developed by the United States Forest Service, Oregon State University, and the Conservation Biology Institute.

NPOESS, Essential Climates Variables and Climate Change

NASA Astrophysics Data System (ADS)

Forsythe-Newell, S. P.; Bates, J. J.; Barkstrom, B. R.; Privette, J. L.; Kearns, E. J.

2008-12-01

Advancement in understanding, predicting and mitigating against climate change implies collaboration, close monitoring of Essential Climate Variable (ECV)s through development of Climate Data Record (CDR)s and effective action with specific thematic focus on human and environmental impacts. Towards this end, NCDC's Scientific Data Stewardship (SDS) Program Office developed Climate Long-term Information and Observation system (CLIO) for satellite data identification, characterization and use interrogation. This "proof-of-concept" online tool provides the ability to visualize global CDR information gaps and overlaps with options to temporally zoom-in from satellite instruments to climate products, data sets, data set versions and files. CLIO provides an intuitive one-stop web site that displays past, current and planned launches of environmental satellites in conjunction with associated imagery and detailed information. This tool is also capable of accepting and displaying Web-based input from Subject Matter Expert (SME)s providing a global to sub-regional scale perspective of all ECV's and their impacts upon climate studies. SME's can access and interact with temporal data from the past and present, or for future planning of products, datasets/dataset versions, instruments, platforms and networks. CLIO offers quantifiable prioritization of ECV/CDR impacts that effectively deal with climate change issues, their associated impacts upon climate, and this offers an intuitively objective collaboration and consensus building tool. NCDC's latest tool empowers decision makers and the scientific community to rapidly identify weaknesses and strengths in climate change monitoring strategies and significantly enhances climate change collaboration and awareness.

Extra-Tropical Cyclones at Climate Scales: Comparing Models to Observations

NASA Astrophysics Data System (ADS)

Tselioudis, G.; Bauer, M.; Rossow, W.

2009-04-01

Climate is often defined as the accumulation of weather, and weather is not the concern of climate models. Justification for this latter sentiment has long been hidden behind coarse model resolutions and blunt validation tools based on climatological maps. The spatial-temporal resolutions of today's climate models and observations are converging onto meteorological scales, however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough that its accumulation results in a robust climate simulation. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from observations and climate model output. These include the usual cyclone characteristics (centers, tracks), but also adaptive cyclone-centric composites. We have created a novel dataset, the MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid-latitude cyclones, using a search algorithm that delimits the boundaries of each system from the outer-most closed SLP contour. Using this we then extract composites of cloud, radiation, and precipitation properties from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools in process-based climate model evaluation studies will be shown.

Integrating Climate and Ocean Change Vulnerability into Conservation Planning

NASA Astrophysics Data System (ADS)

Mcleod, E.; Green, A.; Game, E.; Anthony, K.; Cinner, J.; Heron, S. F.; Kleypas, J. A.; Lovelock, C.; Pandolfi, J.; Pressey, B.; Salm, R.; Schill, S.; Woodroffe, C. D.

2013-05-01

Tropical coastal and marine ecosystems are particularly vulnerable to ocean warming, ocean acidification, and sea-level rise. Yet these projected climate and ocean change impacts are rarely considered in conservation planning due to the lack of guidance on how existing climate and ocean change models, tools, and data can be applied. We address this gap by describing how conservation planning can use available tools and data for assessing the vulnerability of tropical marine ecosystems to key climate threats. Additionally, we identify limitations of existing tools and provide recommendations for future research to improve integration of climate and ocean change information and conservation planning. Such information is critical for developing a conservation response that adequately protects these ecosystems and dependent coastal communities in the face of climate and ocean change.

Collaboration pathway(s) using new tools for optimizing `operational' climate monitoring from space

NASA Astrophysics Data System (ADS)

Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.

2015-09-01

Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a long term solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the collective needs of policy makers, scientific communities and global academic users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent rule-based expert system (RBES) optimization modeling of the intended NPOESS architecture becomes a surrogate for global operational climate monitoring architecture(s). These rulebased systems tools provide valuable insight for global climate architectures, by comparison/evaluation of alternatives and the sheer range of trade space explored. Optimization of climate monitoring architecture(s) for a partial list of ECV (essential climate variables) is explored and described in detail with dialogue on appropriate rule-based valuations. These optimization tool(s) suggest global collaboration advantages and elicit responses from the audience and climate science community. This paper will focus on recent research exploring joint requirement implications of the high profile NPOESS architecture and extends the research and tools to optimization for a climate centric case study. This reflects work from SPIE RS Conferences 2013 and 2014, abridged for simplification30, 32. First, the heavily securitized NPOESS architecture; inspired the recent research question - was Complexity (as a cost/risk factor) overlooked when considering the benefits of aggregating different missions into a single platform. Now years later a complete reversal; should agencies considering Disaggregation as the answer. We'll discuss what some academic research suggests. Second, using the GCOS requirements of earth climate observations via ECV (essential climate variables) many collected from space-based sensors; and accepting their definitions of global coverages intended to ensure the needs of major global and international organizations (UNFCCC and IPCC) are met as a core objective. Consider how new optimization tools like rule-based engines (RBES) offer alternative methods of evaluating collaborative architectures and constellations? What would the trade space of optimized operational climate monitoring architectures of ECV look like? Third, using the RBES tool kit (2014) demonstrate with application to a climate centric rule-based decision engine - optimizing architectural trades of earth observation satellite systems, allowing comparison(s) to existing architectures and gaining insights for global collaborative architectures. How difficult is it to pull together an optimized climate case study - utilizing for example 12 climate based instruments on multiple existing platforms and nominal handful of orbits; for best cost and performance benefits against the collection requirements of representative set of ECV. How much effort and resources would an organization expect to invest to realize these analysis and utility benefits?

Making Sense of Palaeoclimate Sensitivity

NASA Technical Reports Server (NTRS)

Rohling, E. J.; Sluijs, A.; DeConto, R.; Drijfhout, S. S.; Fedorov, A.; Foster, G. L.; Ganopolski, A.; Hansen, J.; Honisch, B.; Hooghiemstra, H.;

Molecules in the mud: Combining ancient DNA and lipid biomarkers to reconstruct vegetation response to climate variability during the Last Interglacial and the Holocene on Baffin Island, Arctic Canada

NASA Astrophysics Data System (ADS)

Crump, S. E.; Sepúlveda, J.; Bunce, M.; Miller, G. H.

2017-12-01

Modern ecological studies are revealing that the "greening" of the Arctic, resulting from a poleward shift in woody vegetation ranges, is already underway. The increasing abundance of shrubs in tundra ecosystems plays an important role in the global climate system through multiple positive feedbacks, yet uncertainty in future predictions of terrestrial vegetation means that climate models are likely not capturing these feedbacks accurately. Recently developed molecular techniques for reconstructing past vegetation and climate allow for a closer look at the paleo-record in order to improve our understanding of tundra community responses to climate variability; our current research focus is to apply these tools to both Last Interglacial and Holocene warm times. Here we present initial results from a small lake on southern Baffin Island spanning the last 7.2 ka. We reconstruct climate with both bulk geochemical and biomarker proxies, primarily using biogenic silica and branched glycerol dialkyl glycerol tetraethers (brGDGTs) as temperature indicators. We assess shifts in plant community using multivariate analysis of sedimentary ancient DNA (sedaDNA) metabarcoding data. This combination of approaches reveals that the vegetation community has responded sensitively to early Holocene warmth, Neoglacial cooling, and possibly modern anthropogenic warming. To our knowledge, this represents the first combination of a quantitative, biomarker-based climate reconstruction with a sedaDNA-based paleoecological reconstruction, and offers a glimpse at the potential of these molecular techniques used in tandem.

Impacts of climate change under CMIP5 RCP scenarios on the streamflow in the Dinder River and ecosystem habitats in Dinder National Park, Sudan

NASA Astrophysics Data System (ADS)

Basheer, Amir K.; Lu, Haishen; Omer, Abubaker; Ali, Abubaker B.; Abdelgader, Abdeldime M. S.

2016-04-01

The fate of seasonal river ecosystem habitats under climate change essentially depends on the changes in annual recharge of the river, which are related to alterations in precipitation and evaporation over the river basin. Therefore, the change in climate conditions is expected to significantly affect hydrological and ecological components, particularly in fragmented ecosystems. This study aims to assess the impacts of climate change on the streamflow in the Dinder River basin (DRB) and to infer its relative possible effects on the Dinder National Park (DNP) ecosystem habitats in Sudan. Four global circulation models (GCMs) from Coupled Model Intercomparison Project Phase 5 and two statistical downscaling approaches combined with a hydrological model (SWAT - the Soil and Water Assessment Tool) were used to project the climate change conditions over the study periods 2020s, 2050s, and 2080s. The results indicated that the climate over the DRB will become warmer and wetter under most scenarios. The projected precipitation variability mainly depends on the selected GCM and downscaling approach. Moreover, the projected streamflow is quite sensitive to rainfall and temperature variation, and will likely increase in this century. In contrast to drought periods during the 1960s, 1970s, and 1980s, the predicted climate change is likely to affect ecosystems in DNP positively and promote the ecological restoration for the habitats of flora and fauna.

Climate change in the Pacific - is it real or not?

NASA Astrophysics Data System (ADS)

Kuleshov, Yuriy

2013-04-01

In this presentation, novel approaches and new ideas for students and young researchers to appreciate the importance of climate science are discussed. These approaches have been applied through conducting a number of training workshops in the Pacific Island Countries and teaching a course on climate change international law and climate change science at the University of the South Pacific (USP) - the first course on this type in the Pacific. Particular focus of this presentation is on broadening students' experience with application of web-based information tools for analysis of climatic extremes and natural hazards such as tropical cyclones. Over the past few years, significant efforts of Australian climate scientists have been dedicated to improving understanding of climate in the Pacific through the International Climate Change Adaptation Initiative (the Australian Government Initiative to assist with high priority climate adaptation needs in vulnerable countries in the Asia-Pacific region). The first comprehensive scientific report about the Pacific climate has been published in 2011, as an outcome of the Pacific Climate Change Science Program (PCCSP). A range of web-based information tools such as the Pacific Tropical Cyclone Data Portal, the Pacific Climate Change Data Portal and the Pacific Seasonal Climate Prediction Portal has been also developed through the PCCSP and the Pacific Adaptation Strategy Assistance Program. Currently, further advancement in seasonal climate prediction science and developing enhanced software tools for the Pacific is undertaken through the Theme 1 of the Pacific Australia Climate Change Science and Adaptation Planning (PACCSAP) Program. This new scientific knowledge needs to be transferred to students to provide them with true information about climate change and its impact on the Pacific Island Countries. Teachers and educators need their knowledge-base regularly updated and tools that will help their students critically evaluate information transmitted via the mass media. This is particularly important when educators present to students cutting edge science knowledge on climate change. Climate change skeptics through mass media attack climate scientists and dismiss their findings about magnitude of climate change. A novel approach implemented in our training workshops and teaching courses gives students practical hands on experience in examining climate data using the developed web-based information tools. Using the tools, students can examine climate of the Pacific Island Countries, derive trends in climate variables such as temperature and rainfall and make their own conclusions. An open forum "Is climate change real or not?" has also been included as an integral part of these workshops and teaching, giving an opportunity for students to present their findings. They have also been asked to provide examples of observed change in the environment in their countries which may be related to climate change. Tropical cyclones are the most destructive severe weather events in the Pacific which regularly affect countries in the region. Understanding importance of updating knowledge about cyclones, extensive training in using the Pacific Tropical Cyclone Data Portal (http://www.bom.gov.au/cyclone/history/tracks/) has also been provided. Using this sophisticated web-based tool, students can learn about occurrences of cyclones in waters around their countries and over the whole Pacific. Positive feedback from university students and participants of training workshops has been obtained and this approach may be recommended for educators to include in their courses. Acknowledgement The research discussed in this paper was conducted through the PASAP, PCCSP and PACCSAP supported by the AusAID and Department of Climate Change and Energy Efficiency and delivered by the Bureau of Meteorology and CSIRO.

A Statistical Bias Correction Tool for Generating Climate Change Scenarios in Indonesia based on CMIP5 Datasets

NASA Astrophysics Data System (ADS)

Faqih, A.

2017-03-01

Providing information regarding future climate scenarios is very important in climate change study. The climate scenario can be used as basic information to support adaptation and mitigation studies. In order to deliver future climate scenarios over specific region, baseline and projection data from the outputs of global climate models (GCM) is needed. However, due to its coarse resolution, the data have to be downscaled and bias corrected in order to get scenario data with better spatial resolution that match the characteristics of the observed data. Generating this downscaled data is mostly difficult for scientist who do not have specific background, experience and skill in dealing with the complex data from the GCM outputs. In this regards, it is necessary to develop a tool that can be used to simplify the downscaling processes in order to help scientist, especially in Indonesia, for generating future climate scenario data that can be used for their climate change-related studies. In this paper, we introduce a tool called as “Statistical Bias Correction for Climate Scenarios (SiBiaS)”. The tool is specially designed to facilitate the use of CMIP5 GCM data outputs and process their statistical bias corrections relative to the reference data from observations. It is prepared for supporting capacity building in climate modeling in Indonesia as part of the Indonesia 3rd National Communication (TNC) project activities.

eSACP - a new Nordic initiative towards developing statistical climate services

NASA Astrophysics Data System (ADS)

Thorarinsdottir, Thordis; Thejll, Peter; Drews, Martin; Guttorp, Peter; Venälainen, Ari; Uotila, Petteri; Benestad, Rasmus; Mesquita, Michel d. S.; Madsen, Henrik; Fox Maule, Cathrine

2015-04-01

The Nordic research council NordForsk has recently announced its support for a new 3-year research initiative on "statistical analysis of climate projections" (eSACP). eSACP will focus on developing e-science tools and services based on statistical analysis of climate projections for the purpose of helping decision-makers and planners in the face of expected future challenges in regional climate change. The motivation behind the project is the growing recognition in our society that forecasts of future climate change is associated with various sources of uncertainty, and that any long-term planning and decision-making dependent on a changing climate must account for this. At the same time there is an obvious gap between scientists from different fields and between practitioners in terms of understanding how climate information relates to different parts of the "uncertainty cascade". In eSACP we will develop generic e-science tools and statistical climate services to facilitate the use of climate projections by decision-makers and scientists from all fields for climate impact analyses and for the development of robust adaptation strategies, which properly (in a statistical sense) account for the inherent uncertainty. The new tool will be publically available and include functionality to utilize the extensive and dynamically growing repositories of data and use state-of-the-art statistical techniques to quantify the uncertainty and innovative approaches to visualize the results. Such a tool will not only be valuable for future assessments and underpin the development of dedicated climate services, but will also assist the scientific community in making more clearly its case on the consequences of our changing climate to policy makers and the general public. The eSACP project is led by Thordis Thorarinsdottir, Norwegian Computing Center, and also includes the Finnish Meteorological Institute, the Norwegian Meteorological Institute, the Technical University of Denmark and the Bjerknes Centre for Climate Research, Norway. This poster will present details of focus areas in the project and show some examples of the expected analysis tools.

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

NASA Astrophysics Data System (ADS)

Ragone, Francesco; Lucarini, Valerio; Lunkeit, Frank

2016-03-01

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

Climate Risk Assessment: Technical Guidance Manual for DoD Installations and Built Environment

DTIC Science & Technology

2016-09-06

climate change risks to DoD installations and the built environment. The approach, which we call “decision-scaling,” reveals the core sensitivity of...DoD installations to climate change . It is designed to illuminate the sensitivity of installations and their supporting infrastructure systems...including water and energy, to climate changes and other uncertainties without dependence on climate change projections. In this way the analysis and

Promoting climate literacy through social engagement: the Green Ninja Project

NASA Astrophysics Data System (ADS)

Cordero, E. C.; Todd, A.

2012-12-01

One of the challenges of communicating climate change to younger audiences is the disconnect between global issues and local impacts. The Green Ninja is a climate-action superhero that aims to energize young people about climate science through media and social engagement tools. In this presentation, we'll highlight two of the tools designed to help K-12 students implement appropriate local mitigation strategies. A mobile phone application builds and supports a social community around taking action at local businesses regarding themes such as food, packaging and energy efficiency. An energy efficiency contest in local schools utilizes smart meter technology to provide feedback on household energy use and conservation. These tools are supported by films and lesson plans that link formal and informal education channels. The effectiveness of these methodologies as tools to engage young people in climate science and action will be discussed.

Socio-climatic Exposure of an Afghan Poppy Farmer

NASA Astrophysics Data System (ADS)

Mankin, J. S.; Diffenbaugh, N. S.

2011-12-01

Many posit that climate impacts from anthropogenic greenhouse gas emissions will have consequences for the natural and agricultural systems on which humans rely for food, energy, and livelihoods, and therefore, on stability and human security. However, many of the potential mechanisms of action in climate impacts and human systems response, as well as the differential vulnerabilities of such systems, remain underexplored and unquantified. Here I present two initial steps necessary to characterize and quantify the consequences of climate change for farmer livelihood in Afghanistan, given both climate impacts and farmer vulnerabilities. The first is a conceptual model mapping the potential relationships between Afghanistan's climate, the winter agricultural season, and the country's political economy of violence and instability. The second is a utility-based decision model for assessing farmer response sensitivity to various climate impacts based on crop sensitivities. A farmer's winter planting decision can be modeled roughly as a tradeoff between cultivating the two crops that dominate the winter growing season-opium poppy (a climate tolerant cash crop) and wheat (a climatically vulnerable crop grown for household consumption). Early sensitivity analysis results suggest that wheat yield dominates farmer decision making variability; however, such initial results may dependent on the relative parameter ranges of wheat and poppy yields. Importantly though, the variance in Afghanistan's winter harvest yields of poppy and wheat is tightly linked to household livelihood and thus, is indirectly connected to the wider instability and insecurity within the country. This initial analysis motivates my focused research on the sensitivity of these crops to climate variability in order to project farmer well-being and decision sensitivity in a warmer world.

Development of Climate Change Adaptation Platform using Spatial Information

NASA Astrophysics Data System (ADS)

Lee, J.; Oh, K. Y.; Lee, M. J.; Han, W. J.

2014-12-01

Climate change adaptation has attracted growing attention with the recent extreme weather conditions that affect people around the world. More and more countries, including the Republic of Korea, have begun to hatch adaptation plan to resolve these matters of great concern. They all, meanwhile, have mentioned that it should come first to integrate climate information in all analysed areas. That's because climate information is not independently made through one source; that is to say, the climate information is connected one another in a complicated way. That is the reason why we have to promote integrated climate change adaptation platform before setting up climate change adaptation plan. Therefore, the large-scaled project has been actively launched and worked on. To date, we researched 620 literatures and interviewed 51 government organizations. Based on the results of the researches and interviews, we obtained 2,725 impacts about vulnerability assessment information such as Monitoring and Forecasting, Health, Disaster, Agriculture, Forest, Water Management, Ecosystem, Ocean/Fisheries, Industry/Energy. Among 2,725 impacts, 995 impacts are made into a database until now. This database is made up 3 sub categories like Climate-Exposure, Sensitivity, Adaptive capacity, presented by IPCC. Based on the constructed database, vulnerability assessments were carried out in order to evaluate climate change capacity of local governments all over the country. These assessments were conducted by using web-based vulnerability assessment tool which was newly developed through this project. These results have shown that, metropolitan areas like Seoul, Pusan, Inchon, and so on have high risks more than twice than rural areas. Acknowledgements: The authors appreciate the support that this study has received from "Development of integrated model for climate change impact and vulnerability assessment and strengthening the framework for model implementation ", an initiative of the Korea Environmental & Industry Technology Institute .

Climate sensitivity of shrub growth across the tundra biome

NASA Astrophysics Data System (ADS)

Myers-Smith, Isla H.; Elmendorf, Sarah C.; Beck, Pieter S. A.; Wilmking, Martin; Hallinger, Martin; Blok, Daan; Tape, Ken D.; Rayback, Shelly A.; Macias-Fauria, Marc; Forbes, Bruce C.; Speed, James D. M.; Boulanger-Lapointe, Noémie; Rixen, Christian; Lévesque, Esther; Schmidt, Niels Martin; Baittinger, Claudia; Trant, Andrew J.; Hermanutz, Luise; Collier, Laura Siegwart; Dawes, Melissa A.; Lantz, Trevor C.; Weijers, Stef; Jørgensen, Rasmus Halfdan; Buchwal, Agata; Buras, Allan; Naito, Adam T.; Ravolainen, Virve; Schaepman-Strub, Gabriela; Wheeler, Julia A.; Wipf, Sonja; Guay, Kevin C.; Hik, David S.; Vellend, Mark

2015-09-01

Rapid climate warming in the tundra biome has been linked to increasing shrub dominance. Shrub expansion can modify climate by altering surface albedo, energy and water balance, and permafrost, yet the drivers of shrub growth remain poorly understood. Dendroecological data consisting of multi-decadal time series of annual shrub growth provide an underused resource to explore climate-growth relationships. Here, we analyse circumpolar data from 37 Arctic and alpine sites in 9 countries, including 25 species, and ~42,000 annual growth records from 1,821 individuals. Our analyses demonstrate that the sensitivity of shrub growth to climate was: (1) heterogeneous, with European sites showing greater summer temperature sensitivity than North American sites, and (2) higher at sites with greater soil moisture and for taller shrubs (for example, alders and willows) growing at their northern or upper elevational range edges. Across latitude, climate sensitivity of growth was greatest at the boundary between the Low and High Arctic, where permafrost is thawing and most of the global permafrost soil carbon pool is stored. The observed variation in climate-shrub growth relationships should be incorporated into Earth system models to improve future projections of climate change impacts across the tundra biome.

Will Global Climate Change Alter Fundamental Human Immune Reactivity: Implications for Child Health?

PubMed

Swaminathan, Ashwin; Lucas, Robyn M; Harley, David; McMichael, Anthony J

2014-11-11

The human immune system is an interface across which many climate change sensitive exposures can affect health outcomes. Gaining an understanding of the range of potential effects that climate change could have on immune function will be of considerable importance, particularly for child health, but has, as yet, received minimal research attention. We postulate several mechanisms whereby climate change sensitive exposures and conditions will subtly impair aspects of the human immune response, thereby altering the distribution of vulnerability within populations-particularly for children-to infection and disease. Key climate change-sensitive pathways include under-nutrition, psychological stress and exposure to ambient ultraviolet radiation, with effects on susceptibility to infection, allergy and autoimmune diseases. Other climate change sensitive exposures may also be important and interact, either additively or synergistically, to alter health risks. Conducting directed research in this area is imperative as the potential public health implications of climate change-induced weakening of the immune system at both individual and population levels are profound. This is particularly relevant for the already vulnerable children of the developing world, who will bear a disproportionate burden of future adverse environmental and geopolitical consequences of climate change.

Are Atmospheric Updrafts a Key to Unlocking Climate Forcing and Sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-06-08

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Sensitivity of global terrestrial ecosystems to climate variability.

PubMed

Seddon, Alistair W R; Macias-Fauria, Marc; Long, Peter R; Benz, David; Willis, Kathy J

2016-03-10

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems--be they natural or with a strong anthropogenic signature--to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

Sensitivity of global terrestrial ecosystems to climate variability

NASA Astrophysics Data System (ADS)

Seddon, Alistair W. R.; Macias-Fauria, Marc; Long, Peter R.; Benz, David; Willis, Kathy J.

2016-03-01

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems—be they natural or with a strong anthropogenic signature—to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

Sensitivity of water resources in the Delaware River basin to climate variability and change

USGS Publications Warehouse

Ayers, Mark A.; Wolock, David M.; McCabe, Gregory J.; Hay, Lauren E.; Tasker, Gary D.

1993-01-01

Because of the "greenhouse effect," projected increases in atmospheric carbon dioxide levels might cause global warming, which in turn could result in changes in precipitation patterns and evapotranspiration and in increases in sea level. This report describes the greenhouse effect; discusses the problems and uncertainties associated with the detection, prediction, and effects of climatic change, and presents the results of sensitivity-analysis studies of the potential effects of climate change on water resources in the Delaware River basin. On the basis of sensitivity analyses, potentially serious shortfalls of certain water resources in the basin could result if some climatic-change scenarios become true. The results of basin streamflow-model simulations in this study demonstrate the difficulty in distinguishing effects of climatic change on streamflow and water supply from effects of natural variability in current climate. The future direction of basin changes in most water resources, furthermore, cannot be determined precisely because of uncertainty in current projections of regional temperature and precipitation. This large uncertainty indicates that, for resource planning, information defining the sensitivities of water resources to a range of climate change is most relevant. The sensitivity analyses could be useful in developing contingency plans on how to evaluate and respond to changes, should they occur.

76 FR 71341 - BASINS and WEPP Climate Assessment Tools: Case Study Guide to Potential Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-17

... report presents a series of short case studies designed to illustrate the capabilities of these tools for... change impacts on water. This report presents a series of short case studies using the BASINS and WEPP climate assessment tools. The case studies are designed to illustrate the capabilities of these tools for...

Environmental health indicators of climate change for the United States: findings from the State Environmental Health Indicator Collaborative.

PubMed

English, Paul B; Sinclair, Amber H; Ross, Zev; Anderson, Henry; Boothe, Vicki; Davis, Christine; Ebi, Kristie; Kagey, Betsy; Malecki, Kristen; Shultz, Rebecca; Simms, Erin

2009-11-01

To develop public health adaptation strategies and to project the impacts of climate change on human health, indicators of vulnerability and preparedness along with accurate surveillance data on climate-sensitive health outcomes are needed. We researched and developed environmental health indicators for inputs into human health vulnerability assessments for climate change and to propose public health preventative actions. We conducted a review of the scientific literature to identify outcomes and actions that were related to climate change. Data sources included governmental and nongovernmental agencies and the published literature. Sources were identified and assessed for completeness, usability, and accuracy. Priority was then given to identifying longitudinal data sets that were applicable at the state and community level. We present a list of surveillance indicators for practitioners and policy makers that include climate-sensitive health outcomes and environmental and vulnerability indicators, as well as mitigation, adaptation, and policy indicators of climate change. A review of environmental health indicators for climate change shows that data exist for many of these measures, but more evaluation of their sensitivity and usefulness is needed. Further attention is necessary to increase data quality and availability and to develop new surveillance databases, especially for climate-sensitive morbidity.

Environmental Health Indicators of Climate Change for the United States: Findings from the State Environmental Health Indicator Collaborative

PubMed Central

English, Paul B.; Sinclair, Amber H.; Ross, Zev; Anderson, Henry; Boothe, Vicki; Davis, Christine; Ebi, Kristie; Kagey, Betsy; Malecki, Kristen; Shultz, Rebecca; Simms, Erin

2009-01-01

Objective To develop public health adaptation strategies and to project the impacts of climate change on human health, indicators of vulnerability and preparedness along with accurate surveillance data on climate-sensitive health outcomes are needed. We researched and developed environmental health indicators for inputs into human health vulnerability assessments for climate change and to propose public health preventative actions. Data sources We conducted a review of the scientific literature to identify outcomes and actions that were related to climate change. Data sources included governmental and nongovernmental agencies and the published literature. Data extraction Sources were identified and assessed for completeness, usability, and accuracy. Priority was then given to identifying longitudinal data sets that were applicable at the state and community level. Data synthesis We present a list of surveillance indicators for practitioners and policy makers that include climate-sensitive health outcomes and environmental and vulnerability indicators, as well as mitigation, adaptation, and policy indicators of climate change. Conclusions A review of environmental health indicators for climate change shows that data exist for many of these measures, but more evaluation of their sensitivity and usefulness is needed. Further attention is necessary to increase data quality and availability and to develop new surveillance databases, especially for climate-sensitive morbidity. PMID:20049116

Colorado River basin sensitivity to disturbance impacts

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Urrego-Blanco, J. R.; Jonko, A. K.; Vano, J. A.; Newman, A. J.; Bohn, T. J.; Middleton, R. S.

2017-12-01

The Colorado River basin is an important river for the food-energy-water nexus in the United States and is projected to change under future scenarios of increased CO2emissions and warming. Streamflow estimates to consider climate impacts occurring as a result of this warming are often provided using modeling tools which rely on uncertain inputs—to fully understand impacts on streamflow sensitivity analysis can help determine how models respond under changing disturbances such as climate and vegetation. In this study, we conduct a global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the Variable Infiltration Capacity (VIC) hydrologic model to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in VIC. Additionally, we examine sensitivities of basin-wide model simulations using an approach that incorporates changes in temperature, precipitation and vegetation to consider impact responses for snow-dominated headwater catchments, low elevation arid basins, and for the upper and lower river basins. We find that for the Colorado River basin, snow-dominated regions are more sensitive to uncertainties. New parameter sensitivities identified include runoff/evapotranspiration sensitivity to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI). Basin-wide streamflow sensitivities to precipitation, temperature and vegetation are variable seasonally and also between sub-basins; with the largest sensitivities for smaller, snow-driven headwater systems where forests are dense. For a major headwater basin, a 1ºC of warming equaled a 30% loss of forest cover, while a 10% precipitation loss equaled a 90% forest cover decline. Scenarios utilizing multiple disturbances led to unexpected results where changes could either magnify or diminish extremes, such as low and peak flows and streamflow timing, dependent on the strength and direction of the forcing. These results indicate the importance of understanding model sensitivities under disturbance impacts to manage these shifts; plan for future water resource changes and determine how the impacts will affect the sustainability and adaptability of food-energy-water systems.

Adaptation Design Tool for Climate-Smart Management of Coral Reefs and Other Natural Resources.

PubMed

West, Jordan M; Courtney, Catherine A; Hamilton, Anna T; Parker, Britt A; Gibbs, David A; Bradley, Patricia; Julius, Susan H

2018-06-22

Scientists and managers of natural resources have recognized an urgent need for improved methods and tools to enable effective adaptation of management measures in the face of climate change. This paper presents an Adaptation Design Tool that uses a structured approach to break down an otherwise overwhelming and complex process into tractable steps. The tool contains worksheets that guide users through a series of design considerations for adapting their planned management actions to be more climate-smart given changing environmental stressors. Also provided with other worksheets is a framework for brainstorming new adaptation options in response to climate threats not yet addressed in the current plan. Developed and tested in collaboration with practitioners in Hawai'i and Puerto Rico using coral reefs as a pilot ecosystem, the tool and associated reference materials consist of worksheets, instructions and lessons-learned from real-world examples. On the basis of stakeholder feedback from expert consultations during tool development, we present insights and recommendations regarding how to maximize tool efficiency, gain the greatest value from the thought process, and deal with issues of scale and uncertainty. We conclude by reflecting on how the tool advances the theory and practice of assessment and decision-making science, informs higher level strategic planning, and serves as a platform for a systematic, transparent and inclusive process to tackle the practical implications of climate change for management of natural resources.

Assessing the impact of climate change upon hydrology and agriculture in the Indrawati Basin, Nepal.

NASA Astrophysics Data System (ADS)

Palazzoli, Irene; Bocchiola, Daniele; Nana, Ester; Maskey, Shreedhar; Uhlenbrook, Stefan

2014-05-01

Agriculture is sensitive to climate change, especially to temperature and precipitation changes. The purpose of this study was to evaluate the climate change impacts upon rain-fed crops production in the Indrawati river basin, Nepal. The Soil and Water Assessment Tool SWAT model was used to model hydrology and cropping systems in the catchment, and to predict the influence of different climate change scenarios therein. Daily weather data collected from about 13 weather stations during 4 decades were used to constrain the SWAT model, and data from two hydrometric stations used to calibrate/validate it. Then management practices (crop calendar) were applied to specific Hydrological Response Units (HRUs) for the main crops of the region, rice, corn and wheat. Manual calibration of crop production was also carried, against values of crop yield in the area from literature. The calibrated and validated model was further applied to assess the impact of three future climate change scenarios (RCPs) upon the crop productivity in the region. Three climate models (GCMs) were adopted, each with three RCPs (2.5, 4.5, 8.5). Hence, impacts of climate change were assessed considering three time windows, namely a baseline period (1995-2004), the middle of century (2045-2054) and the end of century (2085-2094). For each GCM and RCP future hydrology and yield was compared to baseline scenario. The results displayed slightly modified hydrological cycle, and somewhat small variation in crop production, variable with models and RCPs, and for crop type, the largest being for wheat. Keywords: Climate Change, Nepal, hydrological cycle, crop yield.

Climate variability, social and environmental factors, and ross river virus transmission: research development and future research needs.

PubMed

Tong, Shilu; Dale, Pat; Nicholls, Neville; Mackenzie, John S; Wolff, Rodney; McMichael, Anthony J

2008-12-01

Arbovirus diseases have emerged as a global public health concern. However, the impact of climatic, social, and environmental variability on the transmission of arbovirus diseases remains to be determined. Our goal for this study was to provide an overview of research development and future research directions about the interrelationship between climate variability, social and environmental factors, and the transmission of Ross River virus (RRV), the most common and widespread arbovirus disease in Australia. We conducted a systematic literature search on climatic, social, and environmental factors and RRV disease. Potentially relevant studies were identified from a series of electronic searches. The body of evidence revealed that the transmission cycles of RRV disease appear to be sensitive to climate and tidal variability. Rainfall, temperature, and high tides were among major determinants of the transmission of RRV disease at the macro level. However, the nature and magnitude of the interrelationship between climate variability, mosquito density, and the transmission of RRV disease varied with geographic area and socioenvironmental condition. Projected anthropogenic global climatic change may result in an increase in RRV infections, and the key determinants of RRV transmission we have identified here may be useful in the development of an early warning system. The analysis indicates that there is a complex relationship between climate variability, social and environmental factors, and RRV transmission. Different strategies may be needed for the control and prevention of RRV disease at different levels. These research findings could be used as an additional tool to support decision making in disease control/surveillance and risk management.

Managing the impact of climate change on the hydrology of the Gallocanta Basin, NE-Spain.

PubMed

Kuhn, Nikolaus J; Baumhauer, Roland; Schütt, Brigitta

2011-02-01

The Gallocanta Basin represents an environment highly sensitive to climate change. Over the past 60 years, the Laguna de Gallocanta, an ephemeral lake situated in the closed Gallocanta basin, experienced a sequence of wet and dry phases. The lake and its surrounding wetlands are one of only a few bird sanctuaries left in NE-Spain for grey cranes on their annual migration from Scandinavia to northern Africa. Understanding the impact of climate change on basin hydrology is therefore of utmost importance for the appropriate management of the bird sanctuary. Changes in lake level are only weakly linked to annual rainfall, with reaction times between hours and months after rainfall. Both the total amount of rainfall over the reaction period, as well as individual extreme events, affect lake level. In this study the characteristics and frequencies of daily, event, monthly and bi-monthly rainfall over the past 60 years were analysed. The results revealed a clear link between increased frequencies of high magnitude rainfall and phases of water filling in the Laguna de Gallocanta. In the middle of the 20th century, the absolute amount of rainfall appears to have been more important for lake level, while more recently the frequency of high magnitude rainfall has emerged as the dominant variable. In the Gallocanta Basin, climate change and the distinct and continuing land use change since Spain joined the EU in 1986 have created an environment that is in a more or less constant state of transition. This highlights two challenges faced by hydrologists and climatologists involved in developing water management tools for the Gallocanta Basin in particular, but also other areas with sensitive and rapidly changing environments. Hydrologists have to understand the processes and the spatial and temporal patterns of surface-climate interaction in a watershed to assess the impact of climate change on its hydrology. Climatologists, on the other hand, have to develop climate models which provide the appropriate output data, such as reliable information on rainfall characteristics relevant for environmental management. Copyright © 2009. Published by Elsevier Ltd.

Integrating Climate Information and Decision Processes for Regional Climate Resilience

NASA Astrophysics Data System (ADS)

Buizer, James; Goddard, Lisa; Guido, Zackry

2015-04-01

An integrated multi-disciplinary team of researchers from the University of Arizona and the International Research Institute for Climate and Society at Columbia University have joined forces with communities and institutions in the Caribbean, South Asia and West Africa to develop relevant, usable climate information and connect it to real decisions and development challenges. The overall objective of the "Integrating Climate Information and Decision Processes for Regional Climate Resilience" program is to build community resilience to negative impacts of climate variability and change. We produce and provide science-based climate tools and information to vulnerable peoples and the public, private, and civil society organizations that serve them. We face significant institutional challenges because of the geographical and cultural distance between the locale of climate tool-makers and the locale of climate tool-users and because of the complicated, often-inefficient networks that link them. To use an accepted metaphor, there is great institutional difficulty in coordinating the supply of and the demand for useful climate products that can be put to the task of building local resilience and reducing climate vulnerability. Our program is designed to reduce the information constraint and to initiate a linkage that is more demand driven, and which provides a set of priorities for further climate tool generation. A demand-driven approach to the co-production of appropriate and relevant climate tools seeks to meet the direct needs of vulnerable peoples as these needs have been canvassed empirically and as the benefits of application have been adequately evaluated. We first investigate how climate variability and climate change affect the livelihoods of vulnerable peoples. In so doing we assess the complex institutional web within which these peoples live -- the public agencies that serve them, their forms of access to necessary information, the structural constraints under which they make their decisions, and the non-public institutions of support that are available to them. We then interpret this complex reality in terms of the demand for science-based climate products and analyze the channels through which such climate support must pass, thus linking demand assessment with the scientific capacity to create appropriate decision support tools. In summary, the approach we employ is: 1) Demand-driven, beginning with a knowledge of the impacts of climate variability and change upon targeted populations, 2) Focused on vulnerability and resilience, which requires an understanding of broader networks of institutional actors who contribute to the adaptive capacity of vulnerable peoples, 3) Needs-based in that the climate needs matrix set priorities for the assessment of relevant climate products, 4) Dynamic in that the producers of climate products are involved at the point of demand assessment and can respond directly to stated needs, 5) Reflective in that the impacts of climate product interventions are subject to monitoring and evaluation throughout the process. Methods, approaches and preliminary results of our work in the Caribbean will be presented.

Using Tree-Ring Data, Research, and Expeditions as an Accessible, Hands-on "Bridge" into Climate Studies for Diverse Audiences

NASA Astrophysics Data System (ADS)

Davi, N. K.; Wattenberg, F.; Pringle, P. T.; Tanenbaum, J.; O'Brien, A.; Greidanus, I.; Perry, M.

2012-12-01

Tree-ring research provides an engaging, intuitive, and relevant entryway into understanding both climate-change and environmental research, as well as the process of science from inspiration, to fieldwork, to analysis, to publishing and communicating. The basic premise of dendrochronology is that annual rings reflect environmental conditions year-by-year and that by studying long-lived trees we can learn about past environments and climates for hundreds-to-thousands of years in the past. Conceptually, this makes tree-ring studies accessible to students and faculty for a number of reasons. First, in order to collect their data, dendrochronologists often launch expeditions to stunningly picturesque and remote places in search of long-lived, climate sensitive trees. Scientist exciting stories and images from the field can be leveraged to connect students to the study and the data. Second, tree-rings can be more easily explained as a proxy for climate than other methods (ice cores, carbon-isotope ratios, etc.), and most people have prior-knowledge about trees and annual growth rings. It is even possible, for example, for non-expert audiences to see climate variability through time with the naked eye by looking at climate sensitive tree cores. Third, tree-rings are interdisciplinary and illustrate the interplay between the mathematical sciences, the biological sciences, and the geosciences—that is, they show that the biosphere is a fundamental component of the Earth system. Here, we will present several projects have been initiated for a range of audiences, including; elementary school, where 5th graders visited a local forest to collect samples and apply their samples and what they learned to math and science classes. 5th grade students also leaned how to use Climate Explorer (KNMI), an online tool that allows scientist and students the opportunity to access and visualize global climate data within a few clicks. Geared to 2 and 4 year colleges, we are also collaboratively developing new interdisciplinary science and mathematical curriculum, interactive game modules, and multi-media that focus on using tree-ring expeditions and research projects that have real-world applications related to societal concerns (drought, warming, or in some cases, finances) to support student-centered inquiry-based learning. We are also creating professional development guides for teachers.

Sensitivity of multiangle photo-polarimetry to absorbing aerosol vertical layering and properties: Quantifying measurement uncertainties for ACE requirements

NASA Astrophysics Data System (ADS)

Kalashnikova, O. V.; Garay, M. J.; Davis, A. B.; Natraj, V.; Diner, D. J.; Tanelli, S.; Martonchik, J. V.; JPl Team

2011-12-01

The impact of tropospheric aerosols on climate can vary greatly based upon relatively small variations in aerosol properties, such as composition, shape and size distributions, as well as vertical layering. Multi-angle polarimetric measurements have been advocated in recent years as an additional tool to better understand and retrieve the aerosol properties needed for improved predictions of aerosol radiative forcing on climate. The central concern of this work is the assessment of the effects of absorbing aerosol properties under measurement uncertainties achievable for future generation multi-angle, polarimetric imaging instruments under ACE mission requirements. As guidelines, the on-orbit performance of MISR for multi-angle intensity measurements and the reported polarization sensitivities of a MSPI prototype were adopted. In particular, we will focus on sensitivities to absorbing aerosol layering and observation-constrained refractive indices (resulting in various single scattering albedos (SSA)) of both spherical and non-spherical absorbing aerosol types. We conducted modeling experiments to determine how the measured Stokes vector elements are affected in UV-NIR range by the vertical distribution, mixing and layering of smoke and dust aerosols, and aerosol SSA under the assumption of a black and polarizing ocean surfaces. We use a vector successive-orders-of-scattering (SOS) and VLIDORT transfer codes that show excellent agreement. Based on our sensitivity studies we will demonstrate advantages and disadvantages of wavelength selection in UV-NIR range to access absorbing aerosol properties. Polarized UV channels do not show particular advantage for absorbing aerosol property characterization due to dominating molecular signal. Polarimetric SSA sensitivity is small, however needed to be considered in the future polarimetric retrievals under ACE-defined uncertainty.

Sensitivity of ocean acidification and oxygen to the uncertainty in climate change

NASA Astrophysics Data System (ADS)

Cao, Long; Wang, Shuangjing; Zheng, Meidi; Zhang, Han

2014-05-01

Due to increasing atmospheric CO2 concentrations and associated climate change, the global ocean is undergoing substantial physical and biogeochemical changes. Among these, changes in ocean oxygen and carbonate chemistry have great implication for marine biota. There is considerable uncertainty in the projections of future climate change, and it is unclear how the uncertainty in climate change would also affect the projection of oxygen and carbonate chemistry. To investigate this issue, we use an Earth system model of intermediate complexity to perform a set of simulations, including that which involves no radiative effect of atmospheric CO2 and those which involve CO2-induced climate change with climate sensitivity varying from 0.5 °C to 4.5 °C. Atmospheric CO2 concentration is prescribed to follow RCP 8.5 pathway and its extensions. Climate change affects carbonate chemistry and oxygen mainly through its impact on ocean temperature, ocean ventilation, and concentration of dissolved inorganic carbon and alkalinity. It is found that climate change mitigates the decrease of carbonate ions at the ocean surface but has negligible effect on surface ocean pH. Averaged over the whole ocean, climate change acts to decrease oxygen concentration but mitigates the CO2-induced reduction of carbonate ion and pH. In our simulations, by year 2500, every degree increase of climate sensitivity warms the ocean by 0.8 °C and reduces ocean-mean dissolved oxygen concentration by 5.0%. Meanwhile, every degree increase of climate sensitivity buffers CO2-induced reduction in ocean-mean carbonate ion concentration and pH by 3.4% and 0.02 units, respectively. Our study demonstrates different sensitivities of ocean temperature, carbonate chemistry, and oxygen, in terms of both the sign and magnitude to the amount of climate change, which have great implications for understanding the response of ocean biota to climate change.

A Data-Driven Assessment of the Sensitivity of Global Ecosystems to Climate Anomalies

NASA Astrophysics Data System (ADS)

Miralles, D. G.; Papagiannopoulou, C.; Demuzere, M.; Decubber, S.; Waegeman, W.; Verhoest, N.; Dorigo, W.

2017-12-01

Vegetation is a central player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and short-term disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a non-linear random forest predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. This overall dependency of ecosystems on water availability is larger than previously reported, partly owed to the ability of our machine-learning framework to disentangle the co-linearites between climatic drivers, and to quantify non-linear impacts of climate on vegetation. Our observation-based results are then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes. Our findings indicate that the sensitivity of vegetation to climatic anomalies is ill-reproduced by some widely-used ESMs.

Measuring Certified Registered Nurse Anesthetist Organizational Climate: Instrument Adaptation.

PubMed

Boyd, Donald; Poghosyan, Lusine

2017-08-01

No tool exists measuring certified registered nurse anesthetist (CRNA) organizational climate. The study's purpose is to adapt a validated tool to measure CRNA organizational climate. Content validity of the Certified Registered Nurse Anesthetist Organizational Climate Questionnaire (CRNA-OCQ) was established. Pilot testing was conducted to determine internal reliability consistency of the subscales. Experts rated the tool as content valid. The subscales had high internal consistency reliability (with respective Cronbach's alphas): CRNA-Anesthesiologist Relations (.753), CRNA-Physician Relations (.833), CRNA-Administration Relations (.895), Independent Practice (.830), Support for CRNA Practice (.683), and Professional Visibility (.772). Further refinement of the CRNA-OCQ is necessary. Measurement and assessment of CRNA organizational climate may produce evidence needed to improve provider and patient outcomes.

Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change

NASA Technical Reports Server (NTRS)

1997-01-01

This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the Goddard Institute for Space Studies (GISS) 8 deg x lO deg atmospheric General Circulation Model (GCM) to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2.

Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change

NASA Technical Reports Server (NTRS)

1998-01-01

This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the GISS 8 deg x lO deg atmospheric GCM to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2.

How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data

NASA Astrophysics Data System (ADS)

Rödenbeck, Christian; Zaehle, Sönke; Keeling, Ralph; Heimann, Martin

2018-04-01

The response of the terrestrial net ecosystem exchange (NEE) of CO2 to climate variations and trends may crucially determine the future climate trajectory. Here we directly quantify this response on inter-annual timescales by building a linear regression of inter-annual NEE anomalies against observed air temperature anomalies into an atmospheric inverse calculation based on long-term atmospheric CO2 observations. This allows us to estimate the sensitivity of NEE to inter-annual variations in temperature (seen as a climate proxy) resolved in space and with season. As this sensitivity comprises both direct temperature effects and the effects of other climate variables co-varying with temperature, we interpret it as inter-annual climate sensitivity. We find distinct seasonal patterns of this sensitivity in the northern extratropics that are consistent with the expected seasonal responses of photosynthesis, respiration, and fire. Within uncertainties, these sensitivity patterns are consistent with independent inferences from eddy covariance data. On large spatial scales, northern extratropical and tropical inter-annual NEE variations inferred from the NEE-T regression are very similar to the estimates of an atmospheric inversion with explicit inter-annual degrees of freedom. The results of this study offer a way to benchmark ecosystem process models in more detail than existing effective global climate sensitivities. The results can also be used to gap-fill or extrapolate observational records or to separate inter-annual variations from longer-term trends.

Increased sensitivity to climate change in disturbed ecosystems.

PubMed

Kröel-Dulay, György; Ransijn, Johannes; Schmidt, Inger Kappel; Beier, Claus; De Angelis, Paolo; de Dato, Giovanbattista; Dukes, Jeffrey S; Emmett, Bridget; Estiarte, Marc; Garadnai, János; Kongstad, Jane; Kovács-Láng, Edit; Larsen, Klaus Steenberg; Liberati, Dario; Ogaya, Romà; Riis-Nielsen, Torben; Smith, Andrew R; Sowerby, Alwyn; Tietema, Albert; Penuelas, Josep

2015-03-24

Human domination of the biosphere includes changes to disturbance regimes, which push many ecosystems towards early-successional states. Ecological theory predicts that early-successional ecosystems are more sensitive to perturbations than mature systems, but little evidence supports this relationship for the perturbation of climate change. Here we show that vegetation (abundance, species richness and species composition) across seven European shrublands is quite resistant to moderate experimental warming and drought, and responsiveness is associated with the dynamic state of the ecosystem, with recently disturbed sites responding to treatments. Furthermore, most of these responses are not rapid (2-5 years) but emerge over a longer term (7-14 years). These results suggest that successional state influences the sensitivity of ecosystems to climate change, and that ecosystems recovering from disturbances may be sensitive to even modest climatic changes. A research bias towards undisturbed ecosystems might thus lead to an underestimation of the impacts of climate change.

Climate and Population Health Vulnerabilities to Vector-Borne Diseases: Increasing Resilience Under Climate Change Conditions in Africa

NASA Astrophysics Data System (ADS)

Ceccato, P.; McDonald, K. C.; Podest, E.; De La Torre Juarez, M.; Kruczkiewicz, A.; Lessel, J.; Jensen, K.; Thomson, M. C.

2014-12-01

The International Research Institute for Climate and Society (IRI), the City University of New York (CUNY) and NASA Jet Propulsion Laboratory (JPL) in collaboration with NASA SERVIR are developing tools to monitor climate variables (precipitation, temperature, vegetation, water bodies, inundation) that help projects in Africa to increase resilience to climate change for vector-borne diseases (i.e. malaria, trypanosomiasis, leishmaniasis, and schistosomiasis). Through the development of new products to monitor precipitation, water bodies and inundation, IRI, CUNY and JPL provide tools and capacity building to research communities, ministries of health and World Health Organization in Africa to: 1) Develop research teams' ability to appropriately use climate data as part of their research 2) Enable research teams and ministries to integrate climate information into social and economic drivers of vulnerability and opportunities for adaptation to climate change 3) Inform better policies and programs for climate change adaptation. This oral presentation will demonstrate how IRI, CUNY, and JPL developed new products, tools and capacity building to achieve the three objectives mentioned above.

BASINs 4.0 Climate Assessment Tool (CAT): Supporting ...

EPA Pesticide Factsheets

EPA announced the availability of the report, BASINS 4.0 Climate Assessment Tool (CAT): Supporting Documentation and User's Manual. This report was prepared by the EPA's Global Change Research Program (GCRP), an assessment-oriented program, that sits within the Office of Research and Development, that focuses on assessing how potential changes in climate and other global environmental stressors may impact water quality, air quality, aquatic ecosystems, and human health in the United States. The Program’s focus on water quality is consistent with the Research Strategy of the U.S. Climate Change Research Program—the federal umbrella organization for climate change science in the U.S. government—and is responsive to U.S. EPA’s mission and responsibilities as defined by the Clean Water Act and the Safe Drinking Water Act. A central goal of the EPA GCRP is to provide EPA program offices, Regions, and other stakeholders with tools and information for assessing and responding to any potential future impacts of climate change. In 2007, the EPA Global Change Research Program (GCRP), in partnership with the EPA Office of Water, supported development of a Climate Assessment Tool (CAT) for version 4 of EPA’s BASINS modeling system. This report provides supporting documentation and user support materials for the BASINS CAT tool. The purpose of this report is to provide in a single document a variety of documentation and user support materials supporting the use

Climate Informatics: Accelerating Discovering in Climate Science with Machine Learning

NASA Technical Reports Server (NTRS)

Monteleoni, Claire; Schmidt, Gavin A.; McQuade, Scott

2014-01-01

The goal of climate informatics, an emerging discipline, is to inspire collaboration between climate scientists and data scientists, in order to develop tools to analyze complex and ever-growing amounts of observed and simulated climate data, and thereby bridge the gap between data and understanding. Here, recent climate informatics work is presented, along with details of some of the field's remaining challenges. Given the impact of climate change, understanding the climate system is an international priority. The goal of climate informatics is to inspire collaboration between climate scientists and data scientists, in order to develop tools to analyze complex and ever-growing amounts of observed and simulated climate data, and thereby bridge the gap between data and understanding. Here, recent climate informatics work is presented, along with details of some of the remaining challenges.

Meningitis and Climate: From Science to Practice

NASA Technical Reports Server (NTRS)

Perez Garcia-Pando, Carlos; Thomson, Madeleine C.; Stanton, Michelle C.; Diggle, Peter J.; Hopson, Thomas; Pandya, Rajul; Miller, Ron L.; Hugonnet, Stephane

2014-01-01

Meningococcal meningitis is a climate sensitive infectious disease. The regional extent of the Meningitis Belt in Africa, where the majority of epidemics occur, was originally defined by Lapeysonnie in the 1960s. A combination of climatic and environmental conditions and biological and social factors have been associated to the spatial and temporal patterns of epidemics observed since the disease first emerged in West Africa over a century ago. However, there is still a lack of knowledge and data that would allow disentangling the relative effects of the diverse risk factors upon epidemics. The Meningitis Environmental Risk Information Technologies Initiative (MERIT), a collaborative research-to-practice consortium, seeks to inform national and regional prevention and control strategies across the African Meningitis Belt through the provision of new data and tools that better determine risk factors. In particular MERIT seeks to consolidate a body of knowledge that provides evidence of the contribution of climatic and environmental factors to seasonal and year-to-year variations in meningococcal meningitis incidence at both district and national scales. Here we review recent research and practice seeking to provide useful information for the epidemic response strategy of National Ministries of Health in the Meningitis Belt of Africa. In particular the research and derived tools described in this paper have focused at "getting science into policy and practice" by engaging with practitioner communities under the umbrella of MERIT to ensure the relevance of their work to operational decision-making. We limit our focus to that of reactive vaccination for meningococcal meningitis. Important but external to our discussion is the development and implementation of the new conjugate vaccine, which specifically targets meningococcus A

BASINs and WEPP Climate Assessment Tools (CAT): Case Study Guide to Potential Applications (Final Report)

EPA Science Inventory

EPA announced the release of the final report, BASINs and WEPP Climate Assessment Tools (CAT): Case Study Guide to Potential Applications. This report supports application of two recently developed water modeling tools, the Better Assessment Science Integrating point & ...

Different sensitivities of snowpacks to warming in Mediterranean climate mountain areas

NASA Astrophysics Data System (ADS)

López-Moreno, J. I.; Gascoin, S.; Herrero, J.; Sproles, E. A.; Pons, M.; Alonso-González, E.; Hanich, L.; Boudhar, A.; Musselman, K. N.; Molotch, N. P.; Sickman, J.; Pomeroy, J.

2017-07-01

In this study we quantified the sensitivity of snow to climate warming in selected mountain sites having a Mediterranean climate, including the Pyrenees in Spain and Andorra, the Sierra Nevada in Spain and California (USA), the Atlas in Morocco, and the Andes in Chile. Meteorological observations from high elevations were used to simulate the snow energy and mass balance (SEMB) and calculate its sensitivity to climate. Very different climate sensitivities were evident amongst the various sites. For example, reductions of 9%-19% and 6-28 days in the mean snow water equivalent (SWE) and snow duration, respectively, were found per °C increase. Simulated changes in precipitation (±20%) did not affect the sensitivities. The Andes and Atlas Mountains have a shallow and cold snowpack, and net radiation dominates the SEMB; and explains their relatively low sensitivity to climate warming. The Pyrenees and USA Sierra Nevada have a deeper and warmer snowpack, and sensible heat flux is more important in the SEMB; this explains the much greater sensitivities of these regions. Differences in sensitivity help explain why, in regions where climate models project relatively greater temperature increases and drier conditions by 2050 (such as the Spanish Sierra Nevada and the Moroccan Atlas Mountains), the decline in snow accumulation and duration is similar to other sites (such as the Pyrenees and the USA Sierra Nevada), where models project stable precipitation and more attenuated warming. The snowpack in the Andes (Chile) exhibited the lowest sensitivity to warming, and is expected to undergo only moderate change (a decrease of <12% in mean SWE, and a reduction of < 7 days in snow duration under RCP 4.5). Snow accumulation and duration in the other regions are projected to decrease substantially (a minimum of 40% in mean SWE and 15 days in snow duration) by 2050.

Getting The Picture: Our Changing Climate- A new learning tool for climate science

NASA Astrophysics Data System (ADS)

Yager, K.; Balog, J. D.

2014-12-01

Earth Vision Trust (EVT), founded by James Balog- photographer and scientist, has developed a free, online, multimedia climate science education tool for students and educators. Getting The Picture (GTP) creates a new learning experience, drawing upon powerful archives of Extreme Ice Survey's unique photographs and time-lapse videos of changing glaciers around the world. GTP combines the latest in climate science through interactive tools that make the basic scientific tenets of climate science accessible and easy to understand. The aim is to use a multidisciplinary approach to encourage critical thinking about the way our planet is changing due to anthropogenic activities, and to inspire students to find their own voice regarding our changing climate The essence of this resource is storytelling through the use of inspiring images, field expedition notes and dynamic multimedia tools. EVT presents climate education in a new light, illustrating the complex interaction between humans and nature through their Art + Science approach. The overarching goal is to educate and empower young people to take personal action. GTP is aligned with national educational and science standards (NGSS, CCSS, Climate Literacy) so it may be used in conventional classrooms as well as education centers, museum kiosks or anywhere with Internet access. Getting The Picture extends far beyond traditional learning to provide an engaging experience for students, educators and all those who wish to explore the latest in climate science.

Critical Climate-Sensitive and Important Grain-Producing Regions: Grain Production/Yield Variations Due to Climate Fluctuations. Volume 1

NASA Technical Reports Server (NTRS)

Welker, J. E.

2004-01-01

Ideally, the Crop Country Inventory, CCI, is a methodology for the pre-harvest prediction of large variations in a country s crop production. This is accomplished by monitoring the historical climatic fluctuations, especially during the crop calendar period, in a climate sensitive large crop production region or sub-country, rather than the entire country. The argument can be made that the climatic fluctuations in the climatic sensitive region are responsible for the major annual crop country variations and that the remainder of the country, without major climatic fluctuations for a given year, can be assumed to be a steady-state crop producer. The principal data set that has been used is the Global Climate Mode (GCM) data from the National Center for Environmental Prediction (NCEP), taken over the last half century. As a test of its accuracy, GCM data can and has been correlated with the actual meteorological station data at the station site.

Climate change impacts on selected global rangeland ecosystem services.

PubMed

Boone, Randall B; Conant, Richard T; Sircely, Jason; Thornton, Philip K; Herrero, Mario

2018-03-01

Rangelands are Earth's dominant land cover and are important providers of ecosystem services. Reliance on rangelands is projected to grow, thus understanding the sensitivity of rangelands to future climates is essential. We used a new ecosystem model of moderate complexity that allows, for the first time, to quantify global changes expected in rangelands under future climates. The mean global annual net primary production (NPP) may decline by 10 g C m -2  year -1 in 2050 under Representative Concentration Pathway (RCP) 8.5, but herbaceous NPP is projected to increase slightly (i.e., average of 3 g C m -2  year -1 ). Responses vary substantially from place-to-place, with large increases in annual productivity projected in northern regions (e.g., a 21% increase in productivity in the US and Canada) and large declines in western Africa (-46% in sub-Saharan western Africa) and Australia (-17%). Soil organic carbon is projected to increase in Australia (9%), the Middle East (14%), and central Asia (16%) and decline in many African savannas (e.g., -18% in sub-Saharan western Africa). Livestock are projected to decline 7.5 to 9.6%, an economic loss of from $9.7 to $12.6 billion. Our results suggest that forage production in Africa is sensitive to changes in climate, which will have substantial impacts on the livelihoods of the more than 180 million people who raise livestock on those rangelands. Our approach and the simulation tool presented here offer considerable potential for forecasting future conditions, highlight regions of concern, and support analyses where costs and benefits of adaptations and policies may be quantified. Otherwise, the technical options and policy and enabling environment that are needed to facilitate widespread adaptation may be very difficult to elucidate. © 2017 John Wiley & Sons Ltd.

Sensitivity of WRF Regional Climate Simulations to Choice of Land Use Dataset

EPA Science Inventory

The goal of this study is to assess the sensitivity of regional climate simulations run with the Weather Research and Forecasting (WRF) model to the choice of datasets representing land use and land cover (LULC). Within a regional climate modeling application, an accurate repres...

The effects of climate sensitivity and carbon cycle interactions on mitigation policy stringency

EPA Science Inventory

Climate sensitivity and climate-carbon cycle feedbacks interact to determine how global carbon and energy cycles will change in the future. While the science of these connections is well documented, their economic implications are not well understood. Here we examine the effect o...

From Awareness to Action: Determining the climate sensitivities that influence decision makers

NASA Astrophysics Data System (ADS)

Brown, C.

2017-12-01

Through the growth of computing power and analytical methods, a range of valuable and innovative tools allow the exhaustive exploration of a water system's response to a limitless set of scenarios. Similarly, possible adaptive actions can be evaluated across this broad set of possible futures. Finally, an ever increasing set of performance indicators is available to judge the relative value of a particular action over others. However, it's unclear whether this is improving the flow of actionable information or further cluttering it. This presentation will share lessons learned and other intuitions from a set of experiences engaging with public and private water managers and investors in the use of robustness-based climate vulnerability and adaptation analysis. Based on this background, a case for reductionism and focus on financial vulnerability will be forwarded. In addition, considerations for simpler, practical approaches for smaller water utilities will be discussed.

Climate Sensitivity of the Community Climate System Model, Version 4

DOE PAGES

Bitz, Cecilia M.; Shell, K. M.; Gent, P. R.; ...

2012-05-01

Equilibrium climate sensitivity of the Community Climate System Model Version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. We use the radiative kernel technique to show that from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude, and the shortwave cloud feedback increases. These twomore » warming effects are partially canceled by cooling due to slight decreases in the global mean water-vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed-layer, slab ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab ocean model version for both CCSM3 and CCSM4. We argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.« less

Development of an Irrigation Scheduling Tool for the High Plains Region

NASA Astrophysics Data System (ADS)

Shulski, M.; Hubbard, K. G.; You, J.

2009-12-01

The High Plains Regional Climate Center (HPRCC) at the University of Nebraska is one of NOAA’s six regional climate centers in the U.S. Primary objectives of the HPRCC are to conduct applied climate research, engage in climate education and outreach, and increase the use and availability of climate information by developing value-added products. Scientists at the center are engaged in utilizing regional weather data to develop tools that can be used directly by area stakeholders, particularly for agricultural sectors. A new study is proposed that will combine NOAA products (short-term forecasts and seasonal outlooks of temperature and precipitation) with existing capabilities to construct an irrigation scheduling tool that can be used by producers in the region. This tool will make use of weather observations from the regional mesonet (specifically the AWDN, Automated Weather Data Network) and the nation-wide relational database and web portal (ACIS, Applied Climate Information System). The primary benefit to stakeholders will be a more efficient use of water and energy resources owing to the reduction of uncertainty in the timing of irrigation.

Parametric sensitivity analysis of an agro-economic model of management of irrigation water

NASA Astrophysics Data System (ADS)

El Ouadi, Ihssan; Ouazar, Driss; El Menyari, Younesse

2015-04-01

The current work aims to build an analysis and decision support tool for policy options concerning the optimal allocation of water resources, while allowing a better reflection on the issue of valuation of water by the agricultural sector in particular. Thus, a model disaggregated by farm type was developed for the rural town of Ait Ben Yacoub located in the east Morocco. This model integrates economic, agronomic and hydraulic data and simulates agricultural gross margin across in this area taking into consideration changes in public policy and climatic conditions, taking into account the competition for collective resources. To identify the model input parameters that influence over the results of the model, a parametric sensitivity analysis is performed by the "One-Factor-At-A-Time" approach within the "Screening Designs" method. Preliminary results of this analysis show that among the 10 parameters analyzed, 6 parameters affect significantly the objective function of the model, it is in order of influence: i) Coefficient of crop yield response to water, ii) Average daily gain in weight of livestock, iii) Exchange of livestock reproduction, iv) maximum yield of crops, v) Supply of irrigation water and vi) precipitation. These 6 parameters register sensitivity indexes ranging between 0.22 and 1.28. Those results show high uncertainties on these parameters that can dramatically skew the results of the model or the need to pay particular attention to their estimates. Keywords: water, agriculture, modeling, optimal allocation, parametric sensitivity analysis, Screening Designs, One-Factor-At-A-Time, agricultural policy, climate change.

Web-based access, aggregation, and visualization of future climate projections with emphasis on agricultural assessments

NASA Astrophysics Data System (ADS)

Villoria, Nelson B.; Elliott, Joshua; Müller, Christoph; Shin, Jaewoo; Zhao, Lan; Song, Carol

2018-01-01

Access to climate and spatial datasets by non-specialists is restricted by technical barriers involving hardware, software and data formats. We discuss an open-source online tool that facilitates downloading the climate data from the global circulation models used by the Inter-Sectoral Impacts Model Intercomparison Project. The tool also offers temporal and spatial aggregation capabilities for incorporating future climate scenarios in applications where spatial aggregation is important. We hope that streamlined access to these data facilitates analysis of climate related issues while considering the uncertainties derived from future climate projections and temporal aggregation choices.

Climate data induced uncertainty in model based estimations of terrestrial primary productivity

NASA Astrophysics Data System (ADS)

Wu, Z.; Ahlström, A.; Smith, B.; Ardö, J.; Eklundh, L.; Fensholt, R.; Lehsten, V.

2016-12-01

Models used to project global vegetation and carbon cycle differ in their estimates of historical fluxes and pools. These differences arise not only from differences between models but also from differences in the environmental and climatic data that forces the models. Here we investigate the role of uncertainties in historical climate data, encapsulated by a set of six historical climate datasets. We focus on terrestrial gross primary productivity (GPP) and analyze the results from a dynamic process-based vegetation model (LPJ-GUESS) forced by six different climate datasets and two empirical datasets of GPP (derived from flux towers and remote sensing). We find that the climate induced uncertainty, defined as the difference among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 33 Pg C yr-1 globally (19% of mean GPP). The uncertainty is partitioned into the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (the data range) and the sensitivity of the modeled GPP to the driver (the ecosystem sensitivity). The analysis is performed globally and stratified into five land cover classes. We find that the dynamic vegetation model overestimates GPP, compared to empirically based GPP data over most areas, except for the tropical region. Both the simulations and empirical estimates agree that the tropical region is a disproportionate source of uncertainty in GPP estimation. This is mainly caused by uncertainties in shortwave radiation forcing, of which climate data range contributes slightly higher uncertainty than ecosystem sensitivity to shortwave radiation. We also find that precipitation dominated the climate induced uncertainty over nearly half of terrestrial vegetated surfaces, which is mainly due to large ecosystem sensitivity to precipitation. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than ecosystem sensitivity. Our study highlights the need to better constrain tropical climate and demonstrate that uncertainty caused by climatic forcing data must be considered when comparing and evaluating model results and empirical datasets.

AgroClimate: Simulating and Monitoring the Risk of Extreme Weather Events from a Crop Phenology Perspective

NASA Astrophysics Data System (ADS)

Fraisse, C.; Pequeno, D.; Staub, C. G.; Perry, C.

2016-12-01

Climate variability, particularly the occurrence of extreme weather conditions such as dry spells and heat stress during sensitive crop developmental phases can substantially increase the prospect of reduced crop yields. Yield losses or crop failure risk due to stressful weather conditions vary mainly due to stress severity and exposure time and duration. The magnitude of stress effects is also crop specific, differing in terms of thresholds and adaptation to environmental conditions. To help producers in the Southeast USA mitigate and monitor the risk of crop losses due to extreme weather events we developed a web-based tool that evaluates the risk of extreme weather events during the season taking into account the crop development stages. Producers can enter their plans for the upcoming season in a given field (e.g. crop, variety, planting date, acreage etc.), select or not a specific El Nino Southern Oscillation (ENSO) phase, and will be presented with the probabilities (ranging from 0 -100%) of extreme weather events occurring during sensitive phases of the growing season for the selected conditions. The DSSAT models CERES-Maize, CROPGRO-Soybean, CROPGRO-Cotton, and N-Wheat phenology models have been translated from FORTRAN to a standalone versions in R language. These models have been tested in collaboration with Extension faculty and producers during the 2016 season and their usefulness for risk mitigation and monitoring evaluated. A companion AgroClimate app was also developed to help producers track and monitor phenology development during the cropping season.

Estimation of root zone storage capacity at the catchment scale using improved Mass Curve Technique

NASA Astrophysics Data System (ADS)

Zhao, Jie; Xu, Zongxue; Singh, Vijay P.

2016-09-01

The root zone storage capacity (Sr) greatly influences runoff generation, soil water movement, and vegetation growth and is hence an important variable for ecological and hydrological modelling. However, due to the great heterogeneity in soil texture and structure, there seems to be no effective approach to monitor or estimate Sr at the catchment scale presently. To fill the gap, in this study the Mass Curve Technique (MCT) was improved by incorporating a snowmelt module for the estimation of Sr at the catchment scale in different climatic regions. The "range of perturbation" method was also used to generate different scenarios for determining the sensitivity of the improved MCT-derived Sr to its influencing factors after the evaluation of plausibility of Sr derived from the improved MCT. Results can be showed as: (i) Sr estimates of different catchments varied greatly from ∼10 mm to ∼200 mm with the changes of climatic conditions and underlying surface characteristics. (ii) The improved MCT is a simple but powerful tool for the Sr estimation in different climatic regions of China, and incorporation of more catchments into Sr comparisons can further improve our knowledge on the variability of Sr. (iii) Variation of Sr values is an integrated consequence of variations in rainfall, snowmelt water and evapotranspiration. Sr values are most sensitive to variations in evapotranspiration of ecosystems. Besides, Sr values with a longer return period are more stable than those with a shorter return period when affected by fluctuations in its influencing factors.

Regional Climate Service in Northern Germany -The North German Climate Office

NASA Astrophysics Data System (ADS)

Meinke, I.; Von Storch, H.

2012-12-01

The North German Climate Office was established in 2006 at the Institute for Coastal Research at the Helmholtz-Zentrum Geesthacht, Germany as consequence of an increased public information need regarding coastal climate change and its impacts in Northern Germany. The service is characterized by an intensive dialogue between regional climate research and stakeholders in Northern Germany. About once a week scientists of the North German climate office are invited to contribute to public dialogue events. Also numerous direct inquiries are answered and expert interviews are conducted. From this dialogue process specific stakeholder information needs are localized and analysed to develop tailored information products. To provide easy and user specific access to research results interactive web tools are developed. One example is the North German climate atlas, an interactive web tool on possible future climate change in Northern Germany. Another interactive web tool is informing on present and future coastal protection needs in Northern Germany. Another aim of our information products is to assess and summarize the existing scientific knowledge on climate, climate change and impacts in Northern Germany. A mini IPCC-like regional assessment report has been published in 2010, which is summarizing, discussing and assessing the scientific knowledge on regional climate, climate change and impacts as well as possible adaptation strategies in the metropolitan region of Hamburg.

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.

Sensitivity of bud burst in key tree species in the UK to recent climate variability and change

NASA Astrophysics Data System (ADS)

Abernethy, Rachel; Cook, Sally; Hemming, Deborah; McCarthy, Mark

2017-04-01

Analysing the relationship between the changing climate of the UK and the spatial and temporal distribution of spring bud burst plays an important role in understanding ecosystem functionality and predicting future phenological trends. The location and timing of bud burst of eleven species of trees alongside climatic factors such as, temperature, precipitation and hours of sunshine (photoperiod) were used to investigate: i. which species' bud burst timing experiences the greatest impact from a changing climate, ii. which climatic factor has the greatest influence on the timing of bud burst, and iii. whether the location of bud burst is influenced by climate variability. Winter heatwave duration was also analysed as part of an investigation into the relationship between temperature trends of a specific winter period and the following spring events. Geographic Information Systems (GIS) and statistical analysis tools were used to visualise spatial patterns and to analyse the phenological and climate data through regression and analysis of variance (ANOVA) tests. Where there were areas that showed a strong positive or negative relationship between phenology and climate, satellite imagery was used to calculate a Normalised Difference Vegetation Index (NDVI) and a Leaf Area Index (LAI) to further investigate the relationships found. It was expected that in the north of the UK, where bud burst tends to occur later in the year than in the south, that the bud bursts would begin to occur earlier due to increasing temperatures and increased hours of sunshine. However, initial results show that for some species, the bud burst timing tends to remain or become later in the year. Interesting results will be found when investigating the statistical significance between the changing location of the bud bursts and each climatic factor.

The CLEAN Workshop Series: Promoting Effective Pedagogy for Teaching Undergraduate Climate Science

NASA Astrophysics Data System (ADS)

Kirk, K. B.; Bruckner, M. Z.; Manduca, C. A.; Buhr, S. M.

2012-12-01

To prepare students to understand a changing climate, it is imperative that we equip educators with the best possible tools and methods for reaching their audience. As part of the Climate Literacy and Energy Awareness Network (CLEAN) professional development efforts, two workshops for undergraduate faculty were held in 2012. These workshops used a variety of activities to help faculty learn about recent climate research, take part in demonstrations of successful activities for teaching climate topics, and collaborate to create new teaching materials. The workshops also facilitated professional networking among participants. Both workshops were held online, eliminating the need for travel, encouraging participants without travel funds to attend, and allowing international collaborations and presentations. To create an authentic experience, the workshop used several technologies such as the Blackboard Collaborate web conferencing platform, SERC's web-based collaboration tools and online discussion threads, and conference calls. The workshop Communicating Climate Science in the Classroom, held in April 2012, explored practices for communicating climate science and policy in the classroom and provided strategies to improve student understanding of this complex and sensitive topic. Workshop presentations featured public opinion research on Americans' perceptions of climate change, tactics for identifying and resolving student misconceptions, and methods to address various "backfire effects" that can result from attempts to correct misinformation. Demonstrations of teaching approaches included a role-playing simulation of emissions negotiations, Princeton's climate stabilization wedges game, and an activity that allows students to use scientific principles to tackle misinformation. The workshop Teaching Climate Complexity was held in May 2012. Teaching the complexities of climate science requires an understanding of many facets of the Earth system and a robust pedagogic approach that fosters systems thinking. Workshop participants heard presentations from top climate scientists about topics such as the role of carbon dioxide in regulating Earth's climate, the silicate-weathering thermostat hypothesis, effects of water vapor in the climate system, and albedo effects from the loss of Artic sea ice. Demonstrations of classroom techniques allowed participants to use a jigsaw approach to understand poleward heat transport, plot atmospheric carbon dioxide concentrations, and use a mass balance model to explore the role of carbon dioxide in Earth's atmosphere. A hallmark of the CLEAN workshops is that participants are actively engaged in team projects to create new teaching materials. In the Communicating Climate workshop, John Cook led a demonstration of techniques featured in his Debunking Handbook and workshop participants created examples of how to respond to common climate myths in the classroom. In the Climate Complexities workshop, participants used existing elements within the CLEAN reviewed collection to create a comprehensive sequence of activities that can be used to teach elements of Earth's climate system. Activities from the workshop are archived on the CLEAN website, including screen cast recordings of all the presentations and materials created at each workshop. For more information, visit the workshop website at the URL below.

Radiation Transfer in the Atmosphere: Scattering

NASA Technical Reports Server (NTRS)

Mishchenko, M.; Travis, L.; Lacis, Andrew A.

2014-01-01

Sunlight illuminating the Earth's atmosphere is scattered by gas molecules and suspended particles, giving rise to blue skies, white clouds, and optical displays such as rainbows and halos. By scattering and absorbing the shortwave solar radiation and the longwave radiation emitted by the underlying surface, cloud and aerosol particles strongly affect the radiation budget of the terrestrial climate system. As a consequence of the dependence of scattering characteristics on particle size, morphology, and composition, scattered light can be remarkably rich in information on particle properties and thus provides a sensitive tool for remote retrievals of macro- and microphysical parameters of clouds and aerosols.

Adaptation to Climate change Impacts on the Mediterranean islands' Agriculture (ADAPT2CLIMA)

NASA Astrophysics Data System (ADS)

Giannakopoulos, Christos; Karali, Anna; Lemesios, Giannis; Loizidou, Maria; Papadaskalopoulou, Christina; Moustakas, Konstantinos; Papadopoulou, Maria; Moriondo, Marco; Markou, Marinos; Hatziyanni, Eleni; Pasotti, Luigi

2016-04-01

Agriculture is one of the economic sectors that will likely be hit hardest by climate change, since it directly depends on climatic factors such as temperature, sunlight, and precipitation. The EU LIFE ADAPT2CLIMA (http://adapt2clima.eu/en/) project aims to facilitate the development of adaptation strategies for agriculture by deploying and demonstrating an innovative decision support tool. The ADAPT2CLIMA tool will make it possible to simulate the impacts of climate change on crop production and the effectiveness of selected adaptation options in decreasing vulnerability to climate change in three Mediterranean islands, namely Crete (Greece), Sicily (Italy), and Cyprus. The islands were selected for two reasons: firstly, they figure among the most important cultivation areas at national level. Secondly, they exhibit similarities in terms of location (climate), size, climate change threats faced (coastal agriculture, own water resources), agricultural practices, and policy relevance. In particular, the tool will provide: i) climate change projections; ii) hydrological conditions related to agriculture: iii) a vulnerability assessment of selected crops; iv) an evaluation of the adaptation options identified. The project is expected to contribute significantly to increasing climate resilience of agriculture areas in Sicily, Cyprus and Crete as well as at EU and international level by: • Developing, implementing and demonstrating an innovative and interactive decision support tool (ADAPT2CLIMA tool) for adaptation planning in agriculture that estimates future climate change impacts on local water resources, as well as the climate change vulnerability of the agricultural crop production in the project areas; • Evaluating the technical and economic viability of the implementation of the ADAPT2CLIMA tool; • Developing climate change adaptation strategies for agriculture (including a monitoring plan) for the three project areas and presenting them to the competent authorities for adoption; • Simulating the effectiveness of the implementation of certain adaptation measures to address climate change impacts on agriculture; • Developing a stakeholder engagement strategy; • Increasing the knowledge of the impacts of climate change on the agricultural areas covered by the project, thus enabling well informed decision-making and enhancing readiness for early action in order to address the potential damages and minimize threats posed by climate change; • Developing a framework for mainstreaming agricultural adaptation measures into relevant national and regional policies; • Promoting the replication of the proposed methodology in order to ensure proper coordination of national and regional policies and between authorities.

Climate and Health Vulnerability to Vector-Borne Diseases: Increasing Resilience under Climate Change Conditions in Africa

NASA Astrophysics Data System (ADS)

Ceccato, P.

2015-12-01

The International Research Institute for Climate and Society (IRI), the City University of New York (CUNY) and NASA Jet Propulsion Laboratory (JPL) in collaboration with NASA SERVIR are developing tools to monitor climate variables (precipitation, temperature, vegetation, water bodies, inundation) that help projects in Africa to increase resilience to climate change for vector-borne diseases ( malaria, trypanosomiasis, leishmaniasis, and schistosomiasis). Through the development of new products to monitor precipitation, water bodies and inundation, IRI, CUNY and JPL provide tools and capacity building to research communities; ministries of health; the WMO Global Framework for Climate and Services; and World Health Organization in Africa to: 1) Develop research teams' ability to appropriately use climate data as part of their research 2) Enable research teams and ministries to integrate climate information into social and economic drivers of vulnerability and opportunities for adaptation to climate change 3) Inform better policies and programs for climate change adaptation. This oral presentation will demonstrate how IRI, CUNY, and JPL developed new products, tools and capacity building to achieve the three objectives mentioned above with examples in South Africa, Zimbabwe, Tanzania and Malawi.

Climate data induced uncertainty in model-based estimations of terrestrial primary productivity

NASA Astrophysics Data System (ADS)

Wu, Zhendong; Ahlström, Anders; Smith, Benjamin; Ardö, Jonas; Eklundh, Lars; Fensholt, Rasmus; Lehsten, Veiko

2017-06-01

Model-based estimations of historical fluxes and pools of the terrestrial biosphere differ substantially. These differences arise not only from differences between models but also from differences in the environmental and climatic data used as input to the models. Here we investigate the role of uncertainties in historical climate data by performing simulations of terrestrial gross primary productivity (GPP) using a process-based dynamic vegetation model (LPJ-GUESS) forced by six different climate datasets. We find that the climate induced uncertainty, defined as the range among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 11 Pg C yr-1 globally (9% of mean GPP). We also assessed a hypothetical maximum climate data induced uncertainty by combining climate variables from different datasets, which resulted in significantly larger uncertainties of 41 Pg C yr-1 globally or 32% of mean GPP. The uncertainty is partitioned into components associated to the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (climate data range) and the apparent sensitivity of the modeled GPP to the driver (apparent model sensitivity). We find that LPJ-GUESS overestimates GPP compared to empirically based GPP data product in all land cover classes except for tropical forests. Tropical forests emerge as a disproportionate source of uncertainty in GPP estimation both in the simulations and empirical data products. The tropical forest uncertainty is most strongly associated with shortwave radiation and precipitation forcing, of which climate data range contributes higher to overall uncertainty than apparent model sensitivity to forcing. Globally, precipitation dominates the climate induced uncertainty over nearly half of the vegetated land area, which is mainly due to climate data range and less so due to the apparent model sensitivity. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than apparent model sensitivity to forcing. Our study highlights the need to better constrain tropical climate, and demonstrates that uncertainty caused by climatic forcing data must be considered when comparing and evaluating carbon cycle model results and empirical datasets.

Sensitivity of crop cover to climate variability: insights from two Indian agro-ecoregions.

PubMed

Mondal, Pinki; Jain, Meha; DeFries, Ruth S; Galford, Gillian L; Small, Christopher

2015-01-15

Crop productivity in India varies greatly with inter-annual climate variability and is highly dependent on monsoon rainfall and temperature. The sensitivity of yields to future climate variability varies with crop type, access to irrigation and other biophysical and socio-economic factors. To better understand sensitivities to future climate, this study focuses on agro-ecological subregions in Central and Western India that span a range of crops, irrigation, biophysical conditions and socioeconomic characteristics. Climate variability is derived from remotely-sensed data products, Tropical Rainfall Measuring Mission (TRMM - precipitation) and Moderate Resolution Imaging Spectroradiometer (MODIS - temperature). We examined green-leaf phenologies as proxy for crop productivity using the MODIS Enhanced Vegetation Index (EVI) from 2000 to 2012. Using both monsoon and winter growing seasons, we assessed phenological sensitivity to inter-annual variability in precipitation and temperature patterns. Inter-annual EVI phenology anomalies ranged from -25% to 25%, with some highly anomalous values up to 200%. Monsoon crop phenology in the Central India site is highly sensitive to climate, especially the timing of the start and end of the monsoon and intensity of precipitation. In the Western India site, monsoon crop phenology is less sensitive to precipitation variability, yet shows considerable fluctuations in monsoon crop productivity across the years. Temperature is critically important for winter productivity across a range of crop and management types, such that irrigation might not provide a sufficient buffer against projected temperature increases. Better access to weather information and usage of climate-resilient crop types would play pivotal role in maintaining future productivity. Effective strategies to adapt to projected climate changes in the coming decades would also need to be tailored to regional biophysical and socio-economic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Contributions of the Atmospheric Radiation Measurement (ARM) Program and the ARM Climate Research Facility to the U.S. Climate Change Science Program

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

SA Edgerton; LR Roeder

The Earth’s surface temperature is determined by the balance between incoming solar radiation and thermal (or infrared) radiation emitted by the Earth back to space. Changes in atmospheric composition, including greenhouse gases, clouds, and aerosols can alter this balance and produce significant climate change. Global climate models (GCMs) are the primary tool for quantifying future climate change; however, there remain significant uncertainties in the GCM treatment of clouds, aerosol, and their effects on the Earth’s energy balance. The 2007 assessment (AR4) by the Intergovernmental Panel on Climate Change (IPCC) reports a substantial range among GCMs in climate sensitivity to greenhousemore » gas emissions. The largest contributor to this range lies in how different models handle changes in the way clouds absorb or reflect radiative energy in a changing climate (Solomon et al. 2007). In 1989, the U.S. Department of Energy (DOE) Office of Science created the Atmospheric Radiation Measurement (ARM) Program within the Office of Biological and Environmental Research (BER) to address scientific uncertainties related to global climate change, with a specific focus on the crucial role of clouds and their influence on the transfer of radiation in the atmosphere. To address this problem, BER has adopted a unique two-pronged approach: * The ARM Climate Research Facility (ACRF), a scientific user facility for obtaining long-term measurements of radiative fluxes, cloud and aerosol properties, and related atmospheric characteristics in diverse climate regimes. * The ARM Science Program, focused on the analysis of ACRF data to address climate science issues associated with clouds, aerosols, and radiation, and to improve GCMs. This report describes accomplishments of the BER ARM Program toward addressing the primary uncertainties related to climate change prediction as identified by the IPCC.« less

Does the stress tolerance of mixed grassland communities change in a future climate? A test with heavy metal stress (zinc pollution).

PubMed

Van den Berge, Joke; Naudts, Kim; Janssens, Ivan A; Ceulemans, Reinhart; Nijs, Ivan

2011-12-01

Will species that are sensitive/tolerant to Zn pollution still have the same sensitivity/tolerance in a future climate? To answer this question we analysed the response of constructed grassland communities to five levels of zinc (Zn) supply, ranging from 0 to 354 mg Zn kg(-1) dry soil, under a current climate and a future climate (elevated CO2 and warming). Zn concentrations increased in roots and shoots with Zn addition but this increase did not differ between climates. Light-saturated net CO2 assimilation rate (A(sat)) of the species, on the other hand, responded differently to Zn addition depending on climate. Still, current and future climate communities have comparable biomass responses to Zn, i.e., no change in root biomass and a 13% decrease of above-ground biomass. Provided that the different response of A(sat) in a future climate will not compromise productivity and survival on the long term, sensitivity is not altered by climate change. Copyright © 2011 Elsevier Ltd. All rights reserved.

A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China

PubMed Central

Yang, Yanzheng; Zhu, Qiuan; Peng, Changhui; Wang, Han; Xue, Wei; Lin, Guanghui; Wen, Zhongming; Chang, Jie; Wang, Meng; Liu, Guobin; Li, Shiqing

2016-01-01

Increasing evidence indicates that current dynamic global vegetation models (DGVMs) have suffered from insufficient realism and are difficult to improve, particularly because they are built on plant functional type (PFT) schemes. Therefore, new approaches, such as plant trait-based methods, are urgently needed to replace PFT schemes when predicting the distribution of vegetation and investigating vegetation sensitivity. As an important direction towards constructing next-generation DGVMs based on plant functional traits, we propose a novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China. The results demonstrated that a Gaussian mixture model (GMM) trained with a LMA-Nmass-LAI data combination yielded an accuracy of 72.82% in simulating vegetation distribution, providing more detailed parameter information regarding community structures and ecosystem functions. The new approach also performed well in analyses of vegetation sensitivity to different climatic scenarios. Although the trait-climate relationship is not the only candidate useful for predicting vegetation distributions and analysing climatic sensitivity, it sheds new light on the development of next-generation trait-based DGVMs. PMID:27052108

Hydrologic analysis for selection and placement of conservation practices at the watershed scale

NASA Astrophysics Data System (ADS)

Wilson, C.; Brooks, E. S.; Boll, J.

2012-12-01

When a water body is exceeding water quality standards and a Total Maximum Daily Load has been established, conservation practices in the watershed are able to reduce point and non-point source pollution. Hydrological analysis is needed to place conservation practices in the most hydrologically sensitive areas. The selection and placement of conservation practices, however, is challenging in ungauged watersheds with little or no data for the hydrological analysis. The objective of this research is to perform a hydrological analysis for mitigation of erosion and total phosphorus in a mixed land use watershed, and to select and place the conservation practices in the most sensitive areas. The study area is the Hangman Creek watershed in Idaho and Washington State, upstream of Long Lake (WA) reservoir, east of Spokane, WA. While the pollutant of concern is total phosphorus (TP), reductions in TP were translated to total suspended solids or reductions in nonpoint source erosion and sediment delivery to streams. Hydrological characterization was done with a simple web-based tool, which runs the Water Erosion Prediction Project (WEPP) model for representative land types in the watersheds, where a land type is defined as a unique combination of soil type, slope configuration, land use and management, and climate. The web-based tool used site-specific spatial and temporal data on land use, soil physical parameters, slope, and climate derived from readily available data sources and provided information on potential pollutant pathways (i.e. erosion, runoff, lateral flow, and percolation). Multiple land types representative in the watershed were ordered from most effective to least effective, and displayed spatially using GIS. The methodology for the Hangman Creek watershed was validated in the nearby Paradise Creek watershed that has long-term stream discharge and monitoring as well as land use data. Output from the web-based tool shows the potential reductions for different tillage practices, buffer strips, streamside management, and conversion to the conservation reserve program in the watershed. The output also includes the relationship between land area where conservation practices are placed and the potential reduction in pollution, showing the diminished returns on investment as less sensitive areas are being treated. This application of a simple web-based tool and the use of a physically-based erosion model (i.e. WEPP) illustrates that quantitative, spatial and temporal analysis of changes in pollutant loading and site-specific recommendations of conservation practices can be made in ungauged watersheds.

Contributions to Future Stratospheric Climate Change: An Idealized Chemistry-Climate Model Sensitivity Study

NASA Technical Reports Server (NTRS)

Hurwitz, M. M.; Braesicke, P.; Pyle, J. A.

2010-01-01

Within the framework of an idealized model sensitivity study, three of the main contributors to future stratospheric climate change are evaluated: increases in greenhouse gas concentrations, ozone recovery, and changing sea surface temperatures (SSTs). These three contributors are explored in combination and separately, to test the interactions between ozone and climate; the linearity of their contributions to stratospheric climate change is also assessed. In a simplified chemistry-climate model, stratospheric global mean temperature is most sensitive to CO2 doubling, followed by ozone depletion, then by increased SSTs. At polar latitudes, the Northern Hemisphere (NH) stratosphere is more sensitive to changes in CO2, SSTs and O3 than is the Southern Hemisphere (SH); the opposing responses to ozone depletion under low or high background CO2 concentrations, as seen with present-day SSTs, are much weaker and are not statistically significant under enhanced SSTs. Consistent with previous studies, the strength of the Brewer-Dobson circulation is found to increase in an idealized future climate; SSTs contribute most to this increase in the upper troposphere/lower stratosphere (UT/LS) region, while CO2 and ozone changes contribute most in the stratosphere and mesosphere.

Tools in Support of Planning for Weather and Climate Extremes

NASA Astrophysics Data System (ADS)

Done, J.; Bruyere, C. L.; Hauser, R.; Holland, G. J.; Tye, M. R.

2016-12-01

A major limitation to planning for weather and climate extremes is the lack of maintained and readily available tools that can provide robust and well-communicated predictions and advice on their impacts. The National Center for Atmospheric Research is facilitating a collaborative international program to develop and support such tools within its Capacity Center for Climate and Weather Extremes aimed at improving community resilience planning and reducing weather and climate impacts. A Global Risk, Resilience and Impacts Toolbox is in development and will provide: A portable web-based interface to process work requests from a variety of users and locations; A sophisticated framework that enables specialized community tools to access a comprehensive database (public and private) of geo-located hazard, vulnerability, exposure, and loss data; A community development toolkit that enables and encourages community tool developments geared towards specific user man­agement and planning needs, and A comprehensive community sup­port facilitated by NCAR utilizing tutorials and a help desk. A number of applications are in development, built off the latest climate science, and in collaboration with private industry and local and state governments. Example applications will be described, including a hurricane damage tool in collaboration with the reinsurance sector, and a weather management tool for the construction industry. These examples will serve as starting points to discuss the broader potential of the toolbox.

LTPP Climate Tool [Tech Brief

DOT National Transportation Integrated Search

2017-01-01

This Product Brief describes the Long-Term Pavement Performance (LTPP) Climate Tool (intended for use by infrastructure engineers) that provides convenient access to the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective An...

The Climate-Agriculture-Modeling and Decision Tool (CAMDT) for Climate Risk Management in Agriculture

NASA Astrophysics Data System (ADS)

Ines, A. V. M.; Han, E.; Baethgen, W.

2017-12-01

Advances in seasonal climate forecasts (SCFs) during the past decades have brought great potential to improve agricultural climate risk managements associated with inter-annual climate variability. In spite of popular uses of crop simulation models in addressing climate risk problems, the models cannot readily take seasonal climate predictions issued in the format of tercile probabilities of most likely rainfall categories (i.e, below-, near- and above-normal). When a skillful SCF is linked with the crop simulation models, the informative climate information can be further translated into actionable agronomic terms and thus better support strategic and tactical decisions. In other words, crop modeling connected with a given SCF allows to simulate "what-if" scenarios with different crop choices or management practices and better inform the decision makers. In this paper, we present a decision support tool, called CAMDT (Climate Agriculture Modeling and Decision Tool), which seamlessly integrates probabilistic SCFs to DSSAT-CSM-Rice model to guide decision-makers in adopting appropriate crop and agricultural water management practices for given climatic conditions. The CAMDT has a functionality to disaggregate a probabilistic SCF into daily weather realizations (either a parametric or non-parametric disaggregation method) and to run DSSAT-CSM-Rice with the disaggregated weather realizations. The convenient graphical user-interface allows easy implementation of several "what-if" scenarios for non-technical users and visualize the results of the scenario runs. In addition, the CAMDT also translates crop model outputs to economic terms once the user provides expected crop price and cost. The CAMDT is a practical tool for real-world applications, specifically for agricultural climate risk management in the Bicol region, Philippines, having a great flexibility for being adapted to other crops or regions in the world. CAMDT GitHub: https://github.com/Agro-Climate/CAMDT

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.

Flip-flop method: A new T1-weighted flow-MRI for plants studies.

PubMed

Buy, Simon; Le Floch, Simon; Tang, Ning; Sidiboulenouar, Rahima; Zanca, Michel; Canadas, Patrick; Nativel, Eric; Cardoso, Maida; Alibert, Eric; Dupont, Guillaume; Ambard, Dominique; Maurel, Christophe; Verdeil, Jean-Luc; Bertin, Nadia; Goze-Bac, Christophe; Coillot, Christophe

2018-01-01

The climate warming implies an increase of stress of plants (drought and torrential rainfall). The understanding of plant behavior, in this context, takes a major importance and sap flow measurement in plants remains a key issue for plant understanding. Magnetic Resonance Imaging (MRI) which is well known to be a powerful tool to access water quantity can be used to measure moving water. We describe a novel flow-MRI method which takes advantage of inflow slice sensitivity. The method involves the slice selectivity in the context of multi slice spin echo sequence. Two sequences such as a given slice is consecutively inflow and outflow sensitive are performed, offering the possiblility to perform slow flow sensitive imaging in a quite straigthforward way. The method potential is demonstrated by imaging both a slow flow measurement on a test bench (as low as 10 μm.s-1) and the Poiseuille's profile of xylemian sap flow velocity in the xylematic tissues of a tomato plant stem.

Sensitivity of summer stream temperatures to climate variability in the Pacific Northwest

Treesearch

Charles Luce; Brian Staab; Marc Kramer; Seth Wenger; Dan Isaak; Callie McConnell

2014-01-01

Estimating the thermal response of streams to a warming climate is important for prioritizing native fish conservation efforts. While there are plentiful estimates of air temperature responses to climate change, the sensitivity of streams, particularly small headwater streams, to warming temperatures is less well understood. A substantial body of literature correlates...

Projections of Water Stress Based on an Ensemble of Socioeconomic Growth and Climate Change Scenarios: A Case Study in Asia.

PubMed

Fant, Charles; Schlosser, C Adam; Gao, Xiang; Strzepek, Kenneth; Reilly, John

2016-01-01

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios--internally consistent across economics, emissions, climate, and population--to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region's population will live in water-stressed regions in the near future. Tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.

Projections of Water Stress Based on an Ensemble of Socioeconomic Growth and Climate Change Scenarios: A Case Study in Asia

PubMed Central

Fant, Charles; Schlosser, C. Adam; Gao, Xiang; Strzepek, Kenneth; Reilly, John

2016-01-01

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers. PMID:27028871

Accurate Radiometry from Space: An Essential Tool for Climate Studies

NASA Technical Reports Server (NTRS)

Fox, Nigel; Kaiser-Weiss, Andrea; Schmutz, Werner; Thome, Kurtis; Young, Dave; Wielicki, Bruce; Winkler, Rainer; Woolliams, Emma

2011-01-01

The Earth s climate is undoubtedly changing; however, the time scale, consequences and causal attribution remain the subject of significant debate and uncertainty. Detection of subtle indicators from a background of natural variability requires measurements over a time base of decades. This places severe demands on the instrumentation used, requiring measurements of sufficient accuracy and sensitivity that can allow reliable judgements to be made decades apart. The International System of Units (SI) and the network of National Metrology Institutes were developed to address such requirements. However, ensuring and maintaining SI traceability of sufficient accuracy in instruments orbiting the Earth presents a significant new challenge to the metrology community. This paper highlights some key measurands and applications driving the uncertainty demand of the climate community in the solar reflective domain, e.g. solar irradiances and reflectances/radiances of the Earth. It discusses how meeting these uncertainties facilitate significant improvement in the forecasting abilities of climate models. After discussing the current state of the art, it describes a new satellite mission, called TRUTHS, which enables, for the first time, high-accuracy SI traceability to be established in orbit. The direct use of a primary standard and replication of the terrestrial traceability chain extends the SI into space, in effect realizing a metrology laboratory in space . Keywords: climate change; Earth observation; satellites; radiometry; solar irradiance

DESYCO: a Decision Support System to provide climate services for coastal stakeholders dealing with climate change impacts.

NASA Astrophysics Data System (ADS)

Torresan, S.; Gallina, V.; Giannini, V.; Rizzi, J.; Zabeo, A.; Critto, A.; Marcomini, A.

2012-04-01

At the international level climate services are recognized as innovative tools aimed at providing and distributing climate data and information according to the needs of end-users. Furthermore, needs-based climate services are extremely effective to manage climate risks and take advantage of the opportunities associated with climate change impacts. To date, climate services are mainly related to climate models that supply climate data (e.g. temperature, precipitations) at different spatial and time scales. However, there is a significant gap of tools aimed at providing information about risks and impacts induced by climate change and allowing non-expert stakeholders to use both climate-model and climate-impact data. DESYCO is a GIS-Decision Support System aimed at the integrated assessment of multiple climate change impacts on vulnerable coastal systems (e.g. beaches, river deltas, estuaries and lagoons, wetlands, agricultural and urban areas). It is an open source software that manages different input data (e.g. raster or shapefiles) coming from climate models (e.g. global and regional climate projections) and high resolution impact models (e.g. hydrodynamic, hydrological and biogeochemical simulations) in order to provide hazard, exposure, susceptibility, risk and damage maps for the identification and prioritization of hot-spot areas and to provide a basis for the definition of coastal adaptation and management strategies. Within the CLIM-RUN project (FP7) DESYCO is proposed as an helpful tool to bridge the gap between climate data and stakeholder needs and will be applied to the coastal area of the North Adriatic Sea (Italy) in order to provide climate services for local authorities involved in coastal zone management. Accordingly, a first workshop was held in Venice (Italy) with coastal authorities, climate experts and climate change risk experts, in order to start an iterative exchange of information about the knowledge related to climate change, climate models and projections, impact and risk parameters and to know what are stakeholder needs related to climate change in a climate service perspective. The preliminary results gained from the workshop showed that DESYCO is an helpful tool for the impact and risk assessment related to climate change that could be improved in order to fulfill stakeholder needs.

A System for Assessing Vulnerability of Species (SAVS) to Climate Change

Treesearch

Karen E. Bagne; Megan M. Friggens; Deborah M. Finch

2011-01-01

Sustained conservation of species requires integration of future climate change effects, but few tools exist to assist managers. The System for Assessing Vulnerability of Species (SAVS) identifies the relative vulnerability or resilience of vertebrate species to climate change. Designed for managers, the SAVS is an easily applied tool that uses a questionnaire of 22...

Transferring climate research results to stakeholder needs in Northern Germany

NASA Astrophysics Data System (ADS)

Meinke, Insa

2013-04-01

The North German Climate Office was established in 2006 at the Institute for Coastal Research at the Helmholtz-Zentrum Geesthacht, Germany as consequence of an increased public information need regarding coastal climate change and its impacts in Northern Germany. The service is characterized by an intensive dialogue between regional climate research and stakeholders in Northern Germany. About once a week scientists of the North German climate office are invited to contribute to public dialogue events. Also, numerous direct inquiries are answered and expert interviews are conducted. From this dialogue process specific stakeholder information needs are localized and analysed to develop tailored information products. To provide easy and user specific access to research results interactive web tools are developed. One example is the North German climate atlas, an interactive web tool on possible future climate change in Northern Germany. Another interactive web tool is informing on present and future coastal protection needs in Northern Germany. Another aim of our information products is to assess and summarize the existing scientific knowledge on climate, climate change and impacts in Northern Germany. A mini IPCC-like regional assessment report has been published in 2010, which is summarizing, discussing and assessing the scientific knowledge on regional climate, climate change and impacts as well as possible adaptation strategies in the metropolitan region of Hamburg.

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.

Sensitivity of simulated maize crop yields to regional climate in the Southwestern United States

NASA Astrophysics Data System (ADS)

Kim, S.; Myoung, B.; Stack, D.; Kim, J.; Hatzopoulos, N.; Kafatos, M.

2013-12-01

The sensitivity of maize yield to the regional climate in the Southwestern United States (SW US) has been investigated by using a crop-yield simulation model (APSIM) in conjunction with meteorological forcings (daily minimum and maximum temperature, precipitation, and radiation) from the North American Regional Reanalysis (NARR) dataset. The primary focus of this study is to look at the effects of interannual variations of atmospheric components on the crop productivity in the SW US over the 21-year period (1991 to 2011). First of all, characteristics and performance of APSIM was examined by comparing simulated maize yields with observed yields from United States Department of Agriculture (USDA) and the leaf-area index (LAI) from MODIS satellite data. Comparisons of the simulated maize yield with the available observations show that the crop model can reasonably reproduce observed maize yields. Sensitivity tests were performed to assess the relative contribution of each climate driver to regional crop yield. Sensitivity experiments show that potential crop production responds nonlinearly to climate drivers and the yield sensitivity varied among geographical locations depending on their mean climates. Lastly, a detailed analysis of both the spatial and temporal variations of each climate driver in the regions where maize is actually grown in three states (CA, AZ, and NV) in the SW US was performed.

Cluster analyses of 20th century growth patterns in high elevation Great Basin bristlecone pine in the Snake Mountain Range, Nevada, USA

NASA Astrophysics Data System (ADS)

Tran, T. J.; Bruening, J. M.; Bunn, A. G.; Salzer, M. W.; Weiss, S. B.

2015-12-01

Great Basin bristlecone pine (Pinus longaeva) is a useful climate proxy because of the species' long lifespan (up to 5000 years) and the climatic sensitivity of its annually-resolved rings. Past studies have shown that growth of individual trees can be limited by temperature, soil moisture, or a combination of the two depending on biophysical setting at the scale of tens of meters. We extend recent research suggesting that trees vary in their growth response depending on their position on the landscape to analyze how growth patterns vary over time. We used hierarchical cluster analysis to examine the growth of 52 bristlecone pine trees near the treeline of Mount Washington, Nevada, USA. We classified growth of individual trees over the instrumental climate record into one of two possible scenarios: trees belonging to a temperature-sensitive cluster and trees belonging to a precipitation-sensitive cluster. The number of trees in the precipitation-sensitive cluster outnumbered the number of trees in the temperature-sensitive cluster, with trees in colder locations belonging to the temperature-sensitive cluster. When we separated the temporal range into two sections (1895-1949 and 1950-2002) spanning the length of the instrumental climate record, we found that most of the 52 trees remained loyal to their cluster membership (e.g., trees in the temperature-sensitive cluster in 1895-1949 were also in the temperature sensitive cluster in 1950-2002), though not without exception. Of those trees that do not remain consistent in cluster membership, the majority changed from temperature-sensitive to precipitation-sensitive as time progressed. This could signal a switch from temperature limitation to water limitation with warming climate. We speculate that topographic complexity in high mountain environments like Mount Washington might allow for climate refugia where growth response could remain constant over the Holocene.

Can increasing carbon dioxide cause climate change?

PubMed Central

Lindzen, Richard S.

1997-01-01

The realistic physical functioning of the greenhouse effect is reviewed, and the role of dynamic transport and water vapor is identified. Model errors and uncertainties are quantitatively compared with the forcing due to doubling CO2, and they are shown to be too large for reliable model evaluations of climate sensitivities. The possibility of directly measuring climate sensitivity is reviewed. A direct approach using satellite data to relate changes in globally averaged radiative flux changes at the top of the atmosphere to naturally occurring changes in global mean temperature is described. Indirect approaches to evaluating climate sensitivity involving the response to volcanic eruptions and Eocene climate change are also described. Finally, it is explained how, in principle, a climate that is insensitive to gross radiative forcing as produced by doubling CO2 might still be able to undergo major changes of the sort associated with ice ages and equable climates. PMID:11607742

An Observationally-Centred Method to Quantify the Changing Shape of Local Temperature Distributions

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2014-12-01

For climate sensitive decisions and adaptation planning, guidance on how local climate is changing is needed at the specific thresholds relevant to particular impacts or policy endeavours. This requires the quantification of how the distributions of variables, such as daily temperature, are changing at specific quantiles. These temperature distributions are non-normal and vary both geographically and in time. We present a method[1,2] for analysing local climatic time series data to assess which quantiles of the local climatic distribution show the greatest and most robust changes. We have demonstrated this approach using the E-OBS gridded dataset[3] which consists of time series of local daily temperature across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. The change in temperature can be tracked at a temperature threshold, at a likelihood, or at a given return time, independently for each geographical location. Geographical correlations are thus an output of our method and reflect both climatic properties (local and synoptic), and spatial correlations inherent in the observation methodology. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. For instance, in a band from Northern France to Denmark the hottest days in the summer temperature distribution have seen changes of at least 2°C over a 43 year period; over four times the global mean change over the same period. We discuss methods to quantify the robustness of these observed sensitivities and their statistical likelihood. This approach also quantifies the level of detail at which one might wish to see agreement between climate models and observations if such models are to be used directly as tools to assess climate change impacts at local scales. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, Phil. Trans. R. Soc. A, 371 20120287. [2] D A Stainforth, S C Chapman, N W Watkins, 2013, Environ. Res. Lett. 8, 034031 [3] Haylock, M.R. et al., 2008, J. Geophys. Res (Atmospheres), 113, D20119

Benchmarking sensitivity of biophysical processes to leaf area changes in land surface models

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Duveiller, Gregory; Georgievski, Goran; Li, Wei; Robestson, Eddy; Kautz, Markus; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

2017-04-01

Land surface models (LSM) are widely applied as supporting tools for policy-relevant assessment of climate change and its impact on terrestrial ecosystems, yet knowledge of their performance skills in representing the sensitivity of biophysical processes to changes in vegetation density is still limited. This is particularly relevant in light of the substantial impacts on regional climate associated with the changes in leaf area index (LAI) following the observed global greening. Benchmarking LSMs on the sensitivity of the simulated processes to vegetation density is essential to reduce their uncertainty and improve the representation of these effects. Here we present a novel benchmark system to assess model capacity in reproducing land surface-atmosphere energy exchanges modulated by vegetation density. Through a collaborative effort of different modeling groups, a consistent set of land surface energy fluxes and LAI dynamics has been generated from multiple LSMs, including JSBACH, JULES, ORCHIDEE, CLM4.5 and LPJ-GUESS. Relationships of interannual variations of modeled surface fluxes to LAI changes have been analyzed at global scale across different climatological gradients and compared with satellite-based products. A set of scoring metrics has been used to assess the overall model performances and a detailed analysis in the climate space has been provided to diagnose possible model errors associated to background conditions. Results have enabled us to identify model-specific strengths and deficiencies. An overall best performing model does not emerge from the analyses. However, the comparison with other models that work better under certain metrics and conditions indicates that improvements are expected to be potentially achievable. A general amplification of the biophysical processes mediated by vegetation is found across the different land surface schemes. Grasslands are characterized by an underestimated year-to-year variability of LAI in cold climates, ultimately affecting the amount of absorbed radiation. In addition patterns of simulated turbulent fluxes appear opposite to observations. Such systematic errors shed light on the current partial understanding of some of the mechanisms controlling the surface energy balance. In contrast forests appear reasonably well represented with respect to the interactions between LAI and turbulent fluxes across most climatological gradients, while for net radiation this is only true for warm climates. These proven strengths increase the confidence on how certain processes are simulated in LSMs. The model capacity to mimic the vegetation-biophysics interplay has been tested over the real scenario of greening that occurred in the last 30 years. We found that the modeled trends in surface heat fluxes associated with the long-term changes in leaf area could vary largely from those observed, with different discrepancies across models and climate zones. Our findings help to identify knowledge gaps and improve model representation of the sensitivity of biophysical processes to changes in leaf area density. In particular, comparing models and observations over a wide range of climate and vegetation conditions, as analyzed here, allowed capturing non-linearity of system responses that may emerge more frequently in future climate scenarios.

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.

Converging Climate Sensitivities of European Forests Between Observed Radial Tree Growth and Vegetation Models

NASA Technical Reports Server (NTRS)

Zhang, Zhen; Babst, Flurin; Bellassen, Valentin; Frank, David; Launois, Thomas; Tan, Kun; Ciais, Philippe; Poulter, Benjamin

2017-01-01

The impacts of climate variability and trends on European forests are unevenly distributed across different bioclimatic zones and species. Extreme climate events are also becoming more frequent and it is unknown how they will affect feed backs of CO2 between forest ecosystems and the atmosphere. An improved understanding of species differences at the regional scale of the response of forest productivity to climate variation and extremes is thus important for forecasting forest dynamics. In this study, we evaluate the climate sensitivity of above ground net primary production (NPP) simulated by two dynamic global vegetation models (DGVM; ORCHIDEE and LPJ-wsl) against tree ring width (TRW) observations from about1000 sites distributed across Europe. In both the model simulations and the TRW observations, forests in northern Europe and the Alps respond positively to warmer spring and summer temperature, and their overall temperature sensitivity is larger than that of the soil-moisture-limited forests in central Europe and Mediterranean regions. Compared with TRW observations, simulated NPP from ORCHIDEE and LPJ-wsl appear to be overly sensitive to climatic factors. Our results indicate that the models lack biological processes that control time lags, such as carbohydrate storage and remobilization, that delay the effects of radial growth dynamics to climate. Our study highlights the need for re-evaluating the physiological controls on the climate sensitivity of NPP simulated by DGVMs. In particular, DGVMs could be further enhanced by a more detailed representation of carbon reserves and allocation that control year-to year variation in plant growth.

Sphagnum-dwelling testate amoebae in subarctic bogs are more sensitive to soil warming in the growing season than in winter: the results of eight-year field climate manipulations.

PubMed

Tsyganov, Andrey N; Aerts, Rien; Nijs, Ivan; Cornelissen, Johannes H C; Beyens, Louis

2012-05-01

Sphagnum-dwelling testate amoebae are widely used in paleoclimate reconstructions as a proxy for climate-induced changes in bogs. However, the sensitivity of proxies to seasonal climate components is an important issue when interpreting proxy records. Here, we studied the effects of summer warming, winter snow addition solely and winter snow addition together with spring warming on testate amoeba assemblages after eight years of experimental field climate manipulations. All manipulations were accomplished using open top chambers in a dry blanket bog located in the sub-Arctic (Abisko, Sweden). We estimated sensitivity of abundance, diversity and assemblage structure of living and empty shell assemblages of testate amoebae in the living and decaying layers of Sphagnum. Our results show that, in a sub-arctic climate, testate amoebae are more sensitive to climate changes in the growing season than in winter. Summer warming reduced species richness and shifted assemblage composition towards predominance of xerophilous species for the living and empty shell assemblages in both layers. The higher soil temperatures during the growing season also decreased abundance of empty shells in both layers hinting at a possible increase in their decomposition rates. Thus, although possible effects of climate changes on preservation of empty shells should always be taken into account, species diversity and structure of testate amoeba assemblages in dry subarctic bogs are sensitive proxies for climatic changes during the growing season. Copyright © 2011 Elsevier GmbH. All rights reserved.

Characterizing the Sensitivity of Groundwater Storage to Climate variation in the Indus Basin

NASA Astrophysics Data System (ADS)

Huang, L.; Sabo, J. L.

2017-12-01

Indus Basin represents an extensive groundwater aquifer facing the challenge of effective management of limited water resources. Groundwater storage is one of the most important variables of water balance, yet its sensitivity to climate change has rarely been explored. To better estimate present and future groundwater storage and its sensitivity to climate change in the Indus Basin, we analyzed groundwater recharge/discharge and their historical evolution in this basin. Several methods are applied to specify the aquifer system including: water level change and storativity estimates, gravity estimates (GRACE), flow model (MODFLOW), water budget analysis and extrapolation. In addition, all of the socioeconomic and engineering aspects are represented in the hydrological system through the change of temporal and spatial distributions of recharge and discharge (e.g., land use, crop structure, water allocation, etc.). Our results demonstrate that the direct impacts of climate change will result in unevenly distributed but increasing groundwater storage in the short term through groundwater recharge. In contrast, long term groundwater storage will decrease as a result of combined indirect and direct impacts of climate change (e.g. recharge/discharge and human activities). The sensitivity of groundwater storage to climate variation is characterized by topography, aquifer specifics and land use. Furthermore, by comparing possible outcomes of different human interventions scenarios, our study reveals human activities play an important role in affecting the sensitivity of groundwater storage to climate variation. Over all, this study presents the feasibility and value of using integrated hydrological methods to support sustainable water resource management under climate change.

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

Fant, Charles; Schlosser, C. Adam; Gao, Xiang

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify themore » primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Lastly, tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.« less

Vulnerability of global food production to extreme climatic events.

PubMed

Yeni, F; Alpas, H

2017-06-01

It is known that the frequency, intensity or duration of the extreme climatic events have been changing substantially. The ultimate goal of this study was to identify current vulnerabilities of global primary food production against extreme climatic events, and to discuss potential entry points for adaptation planning by means of an explorative vulnerability analysis. Outcomes of this analysis were demonstrated as a composite index where 118 country performances in maintaining safety of food production were compared and ranked against climate change. In order to better interpret the results, cluster analysis technique was used as a tool to group the countries based on their vulnerability index (VI) scores. Results suggested that one sixth of the countries analyzed were subject to high level of exposure (0.45-1), one third to high to very high level of sensitivity (0.41-1) and low to moderate level of adaptive capacity (0-0.59). Proper adaptation strategies for reducing the microbial and chemical contamination of food products, soil and waters on the field were proposed. Finally, availability of data on food safety management systems and occurrence of foodborne outbreaks with global coverage were proposed as key factors for improving the robustness of future vulnerability assessments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Utilizing the NASA Data-enhanced Investigations for Climate Change Education Resource for Elementary Pre-service Teachers in a Technology Integration Education Course.

NASA Astrophysics Data System (ADS)

Howard, E. M.; Moore, T.; Hale, S. R.; Hayden, L. B.; Johnson, D.

2014-12-01

The preservice teachers enrolled in the EDUC 203 Introduction to Computer Instructional Technology course, primarily for elementary-level had created climate change educational lessons based upon their use of the NASA Data-enhanced Investigations for Climate Change Education (DICCE). NASA climate education datasets and tools were introduced to faculty of Minority Serving Institutions through a grant from the NASA Innovations in Climate Education program. These lessons were developed to study various ocean processes involving phytoplankton's chlorophyll production over time for specific geographic areas using the Giovanni NASA software tool. The pre-service teachers had designed the climate change content that will assist K-4 learners to identify and predict phytoplankton sources attributed to sea surface temperatures, nutrient levels, sunlight, and atmospheric carbon dioxide associated with annual chlorophyll production. From the EDUC 203 course content, the preservice teachers applied the three phases of the technology integration planning (TIP) model in developing their lessons. The Zunal website (http://www.zunal.com) served as a hypermedia tool for online instructional delivery in presenting the climate change content, the NASA climate datasets, and the visualization tools used for the production of elementary learning units. A rubric was developed to assess students' development of their webquests to meet the overall learning objectives and specific climate education objectives. Accompanying each webquest is a rubric with a defined table of criteria, for a teacher to assess students completing each of the required tasks for each lesson. Two primary challenges of technology integration for elementary pre-service teachers were 1) motivating pre-service teachers to be interested in climate education and 2) aligning elementary learning objectives with the Next Generation science standards of climate education that are non-existent in the Common Core State Standards.

Novel Tools for Climate Change Learning and Responding in Earth Science Education

NASA Astrophysics Data System (ADS)

Sparrow, Elena; Brunacini, Jessica; Pfirman, Stephanie

2015-04-01

Several innovative, polar focused activities and tools including a polar hub website (http://thepolarhub.org) have been developed for use in formal and informal earth science or STEM education by the Polar Learning and Responding (PoLAR) Climate Change Education Partnership (consisting of climate scientists, experts in the learning sciences and education practitioners). In seeking to inform understanding of and response to climate change, these tools and activities range from increasing awareness to informing decisions about climate change, from being used in classrooms (by undergraduate students as well as by pre-college students or by teachers taking online climate graduate courses) to being used in the public arena (by stakeholders, community members and the general public), and from using low technology (card games such as EcoChains- Arctic Crisis, a food web game or SMARTIC - Strategic Management of Resources in Times of Change, an Arctic marine spatial planning game) to high technology (Greenify Network - a mobile real world action game that fosters sustainability and allows players to meaningfully address climate change in their daily lives, or the Polar Explorer Data Visualization Tablet App that allows individuals to explore data collected by scientists and presented for the everyday user through interactive maps and visualizations, to ask questions and go on an individualized tour of polar regions and their connections to the rest of the world). Games are useful tools in integrative and applied learning, in gaining practical and intellectual skills, and in systems thinking. Also, as part of the PoLAR Partnership, a Signs of the Land Climate Change Camp was collaboratively developed and conducted, that can be used as a model for engaging and representing indigenous communities in the co-production of climate change knowledge, communication tools and solutions building. Future camps are planned with Alaska Native Elders, educators including classroom teachers, natural resource managers, community members, leaders, and climate scientists as participants.

Climate change and nutrition: creating a climate for nutrition security.

PubMed

Tirado, M C; Crahay, P; Mahy, L; Zanev, C; Neira, M; Msangi, S; Brown, R; Scaramella, C; Costa Coitinho, D; Müller, A

2013-12-01

Climate change further exacerbates the enormous existing burden of undernutrition. It affects food and nutrition security and undermines current efforts to reduce hunger and promote nutrition. Undernutrition in turn undermines climate resilience and the coping strategies of vulnerable populations. The objectives of this paper are to identify and undertake a cross-sectoral analysis of the impacts of climate change on nutrition security and the existing mechanisms, strategies, and policies to address them. A cross-sectoral analysis of the impacts of climate change on nutrition security and the mechanisms and policies to address them was guided by an analytical framework focused on the three 'underlying causes' of undernutrition: 1) household food access, 2) maternal and child care and feeding practices, 3) environmental health and health access. The analytical framework includes the interactions of the three underlying causes of undernutrition with climate change,vulnerability, adaptation and mitigation. Within broad efforts on climate change mitigation and adaptation and climate-resilient development, a combination of nutrition-sensitive adaptation and mitigation measures, climate-resilient and nutrition-sensitive agricultural development, social protection, improved maternal and child care and health, nutrition-sensitive risk reduction and management, community development measures, nutrition-smart investments, increased policy coherence, and institutional and cross-sectoral collaboration are proposed as a means to address the impacts of climate change to food and nutrition security. This paper proposes policy directions to address nutrition in the climate change agenda and recommendations for consideration by the UN Framework Convention on Climate Change (UNFCCC). Nutrition and health stakeholders need to be engaged in key climate change adaptation and mitigation initiatives, including science-based assessment by the Intergovernmental Panel on Climate Change (IPCC), and policies and actions formulated by the UN Framework Convention on Climate Change (UNFCCC). Improved multi-sectoral coordination and political will is required to integrate nutrition-sensitive actions into climate-resilient sustainable development efforts in the UNFCCC work and in the post 2015 development agenda. Placing human rights at the center of strategies to mitigate and adapt to the impacts of climate change and international solidarity is essential to advance sustainable development and to create a climate for nutrition security.

An Integrated Multivariable Visualization Tool for Marine Sanctuary Climate Assessments

NASA Astrophysics Data System (ADS)

Shein, K. A.; Johnston, S.; Stachniewicz, J.; Duncan, B.; Cecil, D.; Ansari, S.; Urzen, M.

2012-12-01

The comprehensive development and use of ecological climate impact assessments by ecosystem managers can be limited by data access and visualization methods that require a priori knowledge about the various large and complex climate data products necessary to those impact assessments. In addition, it can be difficult to geographically and temporally integrate climate and ecological data to fully characterize climate-driven ecological impacts. To address these considerations, we have enhanced and extended the functionality of the NOAA National Climatic Data Center's Weather and Climate Toolkit (WCT). The WCT is a freely available Java-based tool designed to access and display NCDC's georeferenced climate data products (e.g., satellite, radar, and reanalysis gridded data). However, the WCT requires users already know how to obtain the data products, which products are preferred for a given variable, and which products are most relevant to their needs. Developed in cooperation with research and management customers at the Gulf of the Farallones National Marine Sanctuary, the Integrated Marine Protected Area Climate Tools (IMPACT) modification to the WCT simplifies or eliminates these requirements, while simultaneously adding core analytical functionality to the tool. Designed for use by marine ecosystem managers, WCT-IMPACT accesses a suite of data products that have been identified as relevant to marine ecosystem climate impact assessments, such as NOAA's Climate Data Records. WCT-IMPACT regularly crops these products to the geographic boundaries of each included marine protected area (MPA), and those clipped regions are processed to produce MPA-specific analytics. The tool retrieves the most appropriate data files based on the user selection of MPA, environmental variable(s), and time frame. Once the data are loaded, they may be visualized, explored, analyzed, and exported to other formats (e.g., Google KML). Multiple variables may be simultaneously visualized using a 4-panel display and compared via a variety of statistics such as difference, probability, or correlation maps.; NCDC's Weather and Climate Toolkit image of NARR-A non-convective cloud cover (%) over the Pacific Coast on June 17, 2012 at 09:00 GMT.

Climate Variability, Social and Environmental Factors, and Ross River Virus Transmission: Research Development and Future Research Needs

PubMed Central

Tong, Shilu; Dale, Pat; Nicholls, Neville; Mackenzie, John S.; Wolff, Rodney; McMichael, Anthony J.

2008-01-01

Background Arbovirus diseases have emerged as a global public health concern. However, the impact of climatic, social, and environmental variability on the transmission of arbovirus diseases remains to be determined. Objective Our goal for this study was to provide an overview of research development and future research directions about the interrelationship between climate variability, social and environmental factors, and the transmission of Ross River virus (RRV), the most common and widespread arbovirus disease in Australia. Methods We conducted a systematic literature search on climatic, social, and environmental factors and RRV disease. Potentially relevant studies were identified from a series of electronic searches. Results The body of evidence revealed that the transmission cycles of RRV disease appear to be sensitive to climate and tidal variability. Rainfall, temperature, and high tides were among major determinants of the transmission of RRV disease at the macro level. However, the nature and magnitude of the interrelationship between climate variability, mosquito density, and the transmission of RRV disease varied with geographic area and socioenvironmental condition. Projected anthropogenic global climatic change may result in an increase in RRV infections, and the key determinants of RRV transmission we have identified here may be useful in the development of an early warning system. Conclusions The analysis indicates that there is a complex relationship between climate variability, social and environmental factors, and RRV transmission. Different strategies may be needed for the control and prevention of RRV disease at different levels. These research findings could be used as an additional tool to support decision making in disease control/surveillance and risk management. PMID:19079707

Modeling Climate Change and Sturgeon Populations in the Missouri River

USGS Publications Warehouse

Wildhaber, Mark L.

2010-01-01

The U.S. Geological Survey (USGS) Columbia Environmental Research Center (CERC), in collaboration with researchers from the University of Missouri and Iowa State University, is conducting research to address effects of climate change on sturgeon populations (Scaphirhynchus spp.) in the Missouri River. The CERC is conducting laboratory, field, and modeling research to identify causative factors for the responses of fish populations to natural and human-induced environmental changes and using this information to understand sensitivity of sturgeon populations to potential climate change in the Missouri River drainage basin. Sturgeon response information is being used to parameterize models predicting future population trends. These models will provide a set of tools for natural resource managers to assess management strategies in the context of global climate change. This research complements and builds on the ongoing Comprehensive Sturgeon Research Program (CSRP) at the CERC. The CSRP is designed to provide information critical to restoration of the Missouri River ecosystem and the endangered pallid sturgeon (S. albus). Current research is being funded by USGS through the National Climate Change Wildlife Science Center (NCCWSC) and the Science Support Partnership (SSP) Program that is held by the USGS and the U.S. Fish and Wildlife Service. The national mission of the NCCWSC is to improve the capacity of fish and wildlife agencies to respond to climate change and to address high-priority climate change effects on fish and wildlife. Within the national context, the NCCWSC research on the Missouri River focuses on temporal and spatial downscaling and associated uncertainty in modeling climate change effects on sturgeon species in the Missouri River. The SSP research focuses on improving survival and population estimates for pallid sturgeon population models.

Modeling the effects of weather and climate change on malaria transmission.

PubMed

Parham, Paul Edward; Michael, Edwin

2010-05-01

In recent years, the impact of climate change on human health has attracted considerable attention; the effects on malaria have been of particular interest because of its disease burden and its transmission sensitivity to environmental conditions. We investigated and illustrated the role that dynamic process-based mathematical models can play in providing strategic insights into the effects of climate change on malaria transmission. We evaluated a relatively simple model that permitted valuable and novel insights into the simultaneous effects of rainfall and temperature on mosquito population dynamics, malaria invasion, persistence and local seasonal extinction, and the impact of seasonality on transmission. We illustrated how large-scale climate simulations and infectious disease systems may be modeled and analyzed and how these methods may be applied to predicting changes in the basic reproduction number of malaria across Tanzania. We found extinction to be more strongly dependent on rainfall than on temperature and identified a temperature window of around 32-33 degrees C where endemic transmission and the rate of spread in disease-free regions is optimized. This window was the same for Plasmodium falciparum and P. vivax, but mosquito density played a stronger role in driving the rate of malaria spread than did the Plasmodium species. The results improved our understanding of how temperature shifts affect the global distribution of at-risk regions, as well as how rapidly malaria outbreaks take off within vulnerable populations. Disease emergence, extinction, and transmission all depend strongly on climate. Mathematical models offer powerful tools for understanding geographic shifts in incidence as climate changes. Nonlinear dependences of transmission on climate necessitates consideration of both changing climate trends and variability across time scales of interest.

Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa.

PubMed

Tonnang, Henri E Z; Kangalawe, Richard Y M; Yanda, Pius Z

2010-04-23

Malaria is rampant in Africa and causes untold mortality and morbidity. Vector-borne diseases are climate sensitive and this has raised considerable concern over the implications of climate change on future disease risk. The problem of malaria vectors (Anopheles mosquitoes) shifting from their traditional locations to invade new zones is an important concern. The vision of this study was to exploit the sets of information previously generated by entomologists, e.g. on geographical range of vectors and malaria distribution, to build models that will enable prediction and mapping the potential redistribution of Anopheles mosquitoes in Africa. The development of the modelling tool was carried out through calibration of CLIMEX parameters. The model helped estimate the potential geographical distribution and seasonal abundance of the species in relation to climatic factors. These included temperature, rainfall and relative humidity, which characterized the living environment for Anopheles mosquitoes. The same parameters were used in determining the ecoclimatic index (EI). The EI values were exported to a GIS package for special analysis and proper mapping of the potential future distribution of Anopheles gambiae and Anophles arabiensis within the African continent under three climate change scenarios. These results have shown that shifts in these species boundaries southward and eastward of Africa may occur rather than jumps into quite different climatic environments. In the absence of adequate control, these predictions are crucial in understanding the possible future geographical range of the vectors and the disease, which could facilitate planning for various adaptation options. Thus, the outputs from this study will be helpful at various levels of decision making, for example, in setting up of an early warning and sustainable strategies for climate change and climate change adaptation for malaria vectors control programmes in Africa.

WEPPCAT: An Online tool for assessing and managing the potential impacts of climate change on sediment loading to streams using the Water Erosion Prediction Project (WEPP) Model

EPA Science Inventory

WEPPCAT is an on-line tool that provides a flexible capability for creating user-determined climate change scenarios for assessing the potential impacts of climate change on sediment loading to streams using the USDA’s Water Erosion Prediction Project (WEPP) Model. In combination...

The Adaptation for Conservation Targets (ACT) framework: a tool for incorporating climate change into natural resource management.

PubMed

Cross, Molly S; Zavaleta, Erika S; Bachelet, Dominique; Brooks, Marjorie L; Enquist, Carolyn A F; Fleishman, Erica; Graumlich, Lisa J; Groves, Craig R; Hannah, Lee; Hansen, Lara; Hayward, Greg; Koopman, Marni; Lawler, Joshua J; Malcolm, Jay; Nordgren, John; Petersen, Brian; Rowland, Erika L; Scott, Daniel; Shafer, Sarah L; Shaw, M Rebecca; Tabor, Gary M

2012-09-01

As natural resource management agencies and conservation organizations seek guidance on responding to climate change, myriad potential actions and strategies have been proposed for increasing the long-term viability of some attributes of natural systems. Managers need practical tools for selecting among these actions and strategies to develop a tailored management approach for specific targets at a given location. We developed and present one such tool, the participatory Adaptation for Conservation Targets (ACT) framework, which considers the effects of climate change in the development of management actions for particular species, ecosystems and ecological functions. Our framework is based on the premise that effective adaptation of management to climate change can rely on local knowledge of an ecosystem and does not necessarily require detailed projections of climate change or its effects. We illustrate the ACT framework by applying it to an ecological function in the Greater Yellowstone Ecosystem (Montana, Wyoming, and Idaho, USA)--water flows in the upper Yellowstone River. We suggest that the ACT framework is a practical tool for initiating adaptation planning, and for generating and communicating specific management interventions given an increasingly altered, yet uncertain, climate.

The Adaptation for Conservation Targets (ACT) Framework: A tool for incorporating climate change into natural resource management

USGS Publications Warehouse

Cross, Molly S.; Zavaleta, Erika S.; Bachelet, Dominique; Brooks, Marjorie L.; Enquist, Carolyn A.F.; Fleishman, Erica; Graumlich, Lisa J.; Groves, Craig R.; Hannah, Lee; Hansen, Lara J.; Hayward, Gregory D.; Koopman, Marni; Lawler, Joshua J.; Malcolm, Jay; Nordgren, John R.; Petersen, Brian; Rowland, Erika; Scott, Daniel; Shafer, Sarah L.; Shaw, M. Rebecca; Tabor, Gary

2012-01-01

As natural resource management agencies and conservation organizations seek guidance on responding to climate change, myriad potential actions and strategies have been proposed for increasing the long-term viability of some attributes of natural systems. Managers need practical tools for selecting among these actions and strategies to develop a tailored management approach for specific targets at a given location. We developed and present one such tool, the participatory Adaptation for Conservation Targets (ACT) framework, which considers the effects of climate change in the development of management actions for particular species, ecosystems and ecological functions. Our framework is based on the premise that effective adaptation of management to climate change can rely on local knowledge of an ecosystem and does not necessarily require detailed projections of climate change or its effects. We illustrate the ACT framework by applying it to an ecological function in the Greater Yellowstone Ecosystem (Montana, Wyoming, and Idaho, USA)—water flows in the upper Yellowstone River. We suggest that the ACT framework is a practical tool for initiating adaptation planning, and for generating and communicating specific management interventions given an increasingly altered, yet uncertain, climate.

A decision support tool to compare waterborne and foodborne infection and/or illness risks associated with climate change.

PubMed

Schijven, Jack; Bouwknegt, Martijn; de Roda Husman, Ana Maria; Rutjes, Saskia; Sudre, Bertrand; Suk, Jonathan E; Semenza, Jan C

2013-12-01

Climate change may impact waterborne and foodborne infectious disease, but to what extent is uncertain. Estimating climate-change-associated relative infection risks from exposure to viruses, bacteria, or parasites in water or food is critical for guiding adaptation measures. We present a computational tool for strategic decision making that describes the behavior of pathogens using location-specific input data under current and projected climate conditions. Pathogen-pathway combinations are available for exposure to norovirus, Campylobacter, Cryptosporidium, and noncholera Vibrio species via drinking water, bathing water, oysters, or chicken fillets. Infection risk outcomes generated by the tool under current climate conditions correspond with those published in the literature. The tool demonstrates that increasing temperatures lead to increasing risks for infection with Campylobacter from consuming raw/undercooked chicken fillet and for Vibrio from water exposure. Increasing frequencies of drought generally lead to an elevated infection risk of exposure to persistent pathogens such as norovirus and Cryptosporidium, but decreasing risk of exposure to rapidly inactivating pathogens, like Campylobacter. The opposite is the case with increasing annual precipitation; an upsurge of heavy rainfall events leads to more peaks in infection risks in all cases. The interdisciplinary tool presented here can be used to guide climate change adaptation strategies focused on infectious diseases. © 2013 Society for Risk Analysis.

A Sensitivity-Based Approach to Quantifying the Costs of Weather and Climate Impacts: A Case Study of the Southern Pennsylvania Transportation Authority Adaptation Pilot Project

NASA Astrophysics Data System (ADS)

Casola, J.; Johanson, E.; Groth, P.; Snow, C.; Choate, A.

2012-12-01

Southeastern Pennsylvania Transportation Authority (SEPTA), with support from the Federal Transit Administration, has been investigating its agency's vulnerability to weather-related disruption and damages as a way to inform an overall adaptation strategy for climate variability and change. Exploiting daily rail service records maintained by SEPTA and observations from nearby weather stations, we have developed a methodology for quantifying the sensitivity of SEPTA's Manayunk/Norristown rail line to various weather events (e.g., snow storms, heat waves, heavy rainfall and flooding, tropical storms). For each type of event, sensitivity is equated to the frequency and extent of service disruptions associated with the event, and includes the identification of thresholds beyond which impacts are observed. In addition, we have estimated the monetary costs associated with repair and replacement of infrastructure following these events. Our results have facilitated discussions with SEPTA operational staff, who have outlined the institutional aspects of their preparation and response processes for these weather events. We envision the methodology as being useful for resource and infrastructure managers across the public and private sector, and potentially scalable to smaller or larger operations. There are several advantageous aspects of the method: 1) the quantification of sensitivity, and the coupling of that sensitivity to cost information, provides credible input to SEPTA decision-makers as they establish the priorities and level of investment associated with their adaptation actions for addressing extreme weather; 2) the method provides a conceptual foundation for estimating the magnitude, frequency, and costs of potential future impacts at a local scale, especially with regard to heat waves; 3) the sensitivity information serves as an excellent discussion tool, enabling further research and information gathering about institutional relationships and procedures. These relationships and procedures are critical to the effectiveness of preparation for and responses to extreme weather events, but are often not explicitly documented.

Economic Value of Narrowing the Uncertainty in Climate Sensitivity: Decadal Change in Shortwave Cloud Radiative Forcing and Low Cloud Feedback

NASA Astrophysics Data System (ADS)

Wielicki, B. A.; Cooke, R. M.; Golub, A. A.; Mlynczak, M. G.; Young, D. F.; Baize, R. R.

2016-12-01

Several previous studies have been published on the economic value of narrowing the uncertainty in climate sensitivity (Cooke et al. 2015, Cooke et al. 2016, Hope, 2015). All three of these studies estimated roughly 10 Trillion U.S. dollars for the Net Present Value and Real Option Value at a discount rate of 3%. This discount rate is the nominal discount rate used in the U.S. Social Cost of Carbon Memo (2010). The Cooke et al studies approached this problem by examining advances in accuracy of global temperature measurements, while the Hope 2015 study did not address the type of observations required. While temperature change is related to climate sensitivity, large uncertainties of a factor of 3 in current anthropogenic radiative forcing (IPCC, 2013) would need to be solved for advanced decadal temperature change observations to assist the challenge of narrowing climate sensitivity. The present study takes a new approach by extending the Cooke et al. 2015,2016 papers to replace observations of temperature change to observations of decadal change in the effects of changing clouds on the Earths radiative energy balance, a measurement known as Cloud Radiative Forcing, or Cloud Radiative Effect. Decadal change in this observation is direclty related to the largest uncertainty in climate sensitivity which is cloud feedback from changing amount of low clouds, primarily low clouds over the world's oceans. As a result, decadal changes in shortwave cloud radiative forcing are more directly related to cloud feedback uncertainty which is the dominant uncertainty in climate sensitivity. This paper will show results for the new approach, and allow an examination of the sensitivity of economic value results to different observations used as a constraint on uncertainty in climate sensitivity. The analysis suggests roughly a doubling of economic value to 20 Trillion Net Present Value or Real Option Value at 3% discount rate. The higher economic value results from two changes: a larger increase in accuracy for SW cloud radiative forcing vs temperature, and from a lower confounding noise from natural variability in the cloud radiative forcing variable compared to temperature. In particular, global average temperature is much more sensitive to the climate noise of ENSO cycles.

Global climate change and US agriculture

NASA Technical Reports Server (NTRS)

Adams, Richard M.; Rosenzweig, Cynthia; Peart, Robert M.; Ritchie, Joe T.; Mccarl, Bruce A.

1990-01-01

Agricultural productivity is expected to be sensitive to global climate change. Models from atmospheric science, plant science, and agricultural economics are linked to explore this sensitivity. Although the results depend on the severity of climate change and the compensating effects of carbon dioxide on crop yields, the simulation suggests that irrigated acreage will expand and regional patterns of U.S. agriculture will shift. The impact of the U.S. economy strongly depends on which climate model is used.

Observation-based Estimate of Climate Sensitivity with a Scaling Climate Response Function

NASA Astrophysics Data System (ADS)

Hébert, Raphael; Lovejoy, Shaun

2016-04-01

To properly adress the anthropogenic impacts upon the earth system, an estimate of the climate sensitivity to radiative forcing is essential. Observation-based estimates of climate sensitivity are often limited by their ability to take into account the slower response of the climate system imparted mainly by the large thermal inertia of oceans, they are nevertheless essential to provide an alternative to estimates from global circulation models and increase our confidence in estimates of climate sensitivity by the multiplicity of approaches. It is straightforward to calculate the Effective Climate Sensitivity(EffCS) as the ratio of temperature change to the change in radiative forcing; the result is almost identical to the Transient Climate Response(TCR), but it underestimates the Equilibrium Climate Sensitivity(ECS). A study of global mean temperature is thus presented assuming a Scaling Climate Response Function to deterministic radiative forcing. This general form is justified as there exists a scaling symmetry respected by the dynamics, and boundary conditions, over a wide range of scales and it allows for long-range dependencies while retaining only 3 parameter which are estimated empirically. The range of memory is modulated by the scaling exponent H. We can calculate, analytically, a one-to-one relation between the scaling exponent H and the ratio of EffCS to TCR and EffCS to ECS. The scaling exponent of the power law is estimated by a regression of temperature as a function of forcing. We consider for the analysis 4 different datasets of historical global mean temperature and 100 scenario runs of the Coupled Model Intercomparison Project Phase 5 distributed among the 4 Representative Concentration Pathways(RCP) scenarios. We find that the error function for the estimate on historical temperature is very wide and thus, many scaling exponent can be used without meaningful changes in the fit residuals of historical temperatures; their response in the year 2100 on the other hand, is very broad, especially for a low-emission scenario such as RCP 2.6. CMIP5 scenario runs thus allow for a narrower estimate of H which can then be used to estimate the ECS and TCR from the EffCS estimated from the historical data.

Contribution of precipitation and reference evapotranspiration to drought indices under different climates

NASA Astrophysics Data System (ADS)

Vicente-Serrano, Sergio M.; Van der Schrier, Gerard; Beguería, Santiago; Azorin-Molina, Cesar; Lopez-Moreno, Juan-I.

2015-07-01

In this study we analyzed the sensitivity of four drought indices to precipitation (P) and reference evapotranspiration (ETo) inputs. The four drought indices are the Palmer Drought Severity Index (PDSI), the Reconnaissance Drought Index (RDI), the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Palmer Drought Index (SPDI). The analysis uses long-term simulated series with varying averages and variances, as well as global observational data to assess the sensitivity to real climatic conditions in different regions of the World. The results show differences in the sensitivity to ETo and P among the four drought indices. The PDSI shows the lowest sensitivity to variation in their climate inputs, probably as a consequence of the standardization procedure of soil water budget anomalies. The RDI is only sensitive to the variance but not to the average of P and ETo. The SPEI shows the largest sensitivity to ETo variation, with clear geographic patterns mainly controlled by aridity. The low sensitivity of the PDSI to ETo makes the PDSI perhaps less apt as the suitable drought index in applications in which the changes in ETo are most relevant. On the contrary, the SPEI shows equal sensitivity to P and ETo. It works as a perfect supply and demand system modulated by the average and standard deviation of each series and combines the sensitivity of the series to changes in magnitude and variance. Our results are a robust assessment of the sensitivity of drought indices to P and ETo variation, and provide advice on the use of drought indices to detect climate change impacts on drought severity under a wide variety of climatic conditions.

A Framework Predicting Water Availability in a Rapidly Growing, Semi-Arid Region under Future Climate Change

NASA Astrophysics Data System (ADS)

Han, B.; Benner, S. G.; Glenn, N. F.; Lindquist, E.; Dahal, K. R.; Bolte, J.; Vache, K. B.; Flores, A. N.

2014-12-01

Climate change can lead to dramatic variations in hydrologic regime, affecting both surface water and groundwater supply. This effect is most significant in populated semi-arid regions where water availability are highly sensitive to climate-induced outcomes. However, predicting water availability at regional scales, while resolving some of the key internal variability and structure in semi-arid regions is difficult due to the highly non-linearity relationship between rainfall and runoff. In this study, we describe the development of a modeling framework to evaluate future water availability that captures elements of the coupled response of the biophysical system to climate change and human systems. The framework is built under the Envision multi-agent simulation tool, characterizing the spatial patterns of water demand in the semi-arid Treasure Valley area of Southwest Idaho - a rapidly developing socio-ecological system where urban growth is displacing agricultural production. The semi-conceptual HBV model, a population growth and allocation model (Target), a vegetation state and transition model (SSTM), and a statistically based fire disturbance model (SpatialAllocator) are integrated to simulate hydrology, population and land use. Six alternative scenarios are composed by combining two climate change scenarios (RCP4.5 and RCP8.5) with three population growth and allocation scenarios (Status Quo, Managed Growth, and Unconstrained Growth). Five-year calibration and validation performances are assessed with Nash-Sutcliffe efficiency. Irrigation activities are simulated using local water rights. Results show that in all scenarios, annual mean stream flow decreases as the projected rainfall increases because the projected warmer climate also enhances water losses to evapotranspiration. Seasonal maximum stream flow tends to occur earlier than in current conditions due to the earlier peak of snow melting. The aridity index and water deficit generally increase in the irrigated area. The most sensitive area is along the Boise Foothill which is the transitioning zone from water deficit to water abundant. However, these trends vary significantly between scenarios in space and time. The outcome of the study will serve as a reference for local stakeholders to make decisions on future land use.

Sensitivity of the reference evapotranspiration to key climatic variables during the growing season in the Ejina oasis northwest China.

PubMed

Hou, Lan-Gong; Zou, Song-Bing; Xiao, Hong-Lang; Yang, Yong-Gang

2013-01-01

The standardized FAO56 Penman-Monteith model, which has been the most reasonable method in both humid and arid climatic conditions, provides reference evapotranspiration (ETo) estimates for planning and efficient use of agricultural water resources. And sensitivity analysis is important in understanding the relative importance of climatic variables to the variation of reference evapotranspiration. In this study, a non-dimensional relative sensitivity coefficient was employed to predict responses of ETo to perturbations of four climatic variables in the Ejina oasis northwest China. A 20-year historical dataset of daily air temperature, wind speed, relative humidity and daily sunshine duration in the Ejina oasis was used in the analysis. Results have shown that daily sensitivity coefficients exhibited large fluctuations during the growing season, and shortwave radiation was the most sensitive variable in general for the Ejina oasis, followed by air temperature, wind speed and relative humidity. According to this study, the response of ETo can be preferably predicted under perturbation of air temperature, wind speed, relative humidity and shortwave radiation by their sensitivity coefficients.

Case Study 3: Species vulnerability assessment for the Middle Rio Grande, New Mexico

Treesearch

Deborah M. Finch; Megan Friggens; Karen Bagne

2011-01-01

This case study describes a method for scoring terrestrial species that have potential to be vulnerable to climate change. The assessment tool seeks to synthesize complex information related to projected climate changes into a predictive tool for species conservation. The tool was designed to aid managers in prioritizing species management actions in response to...

STRESSED SEBATES: A TRAIT-BASED EVALUATION OF CLIMATE RISKS TO ROCKFISHES OF THE NORTHEASTERN PACIFIC USING THE COASTAL BIOGEOGRAPHIC RISK ANALYSIS TOOL (CBRAT)

EPA Science Inventory

The EPA and USGS have developed a framework to evaluate the relative vulnerability of near-coastal species to impacts of climate change. This framework is implemented in a web-based tool, the Coastal Biogeographic Risk Analysis Tool (CBRAT). We evaluated the vulnerability of the ...

Stressed Sebastes: A Trait-Based Evaluation of Climate Risks to Rockfishes of the Northeastern Pacific Using the Coastal Biogeographic Risk Analysis Tool (CBRAT)

EPA Science Inventory

The EPA and USGS have developed a framework to evaluate the relative vulnerability of near-coastal species to impacts of climate change. This framework was implemented in a web-based tool, the Coastal Biogeographic Risk Analysis Tool (CBRAT). We evaluated the vulnerability of the...

Developing and Validating a New Classroom Climate Observation Assessment Tool

PubMed Central

Leff, Stephen S.; Thomas, Duane E.; Shapiro, Edward S.; Paskewich, Brooke; Wilson, Kim; Necowitz-Hoffman, Beth; Jawad, Abbas F.

2011-01-01

The climate of school classrooms, shaped by a combination of teacher practices and peer processes, is an important determinant for children’s psychosocial functioning and is a primary factor affecting bullying and victimization. Given that there are relatively few theoretically-grounded and validated assessment tools designed to measure the social climate of classrooms, our research team developed an observation tool through participatory action research (PAR). This article details how the assessment tool was designed and preliminarily validated in 18 third-, fourth-, and fifth-grade classrooms in a large urban public school district. The goals of this study are to illustrate the feasibility of a PAR paradigm in measurement development, ascertain the psychometric properties of the assessment tool, and determine associations with different indices of classroom levels of relational and physical aggression. PMID:21643447

Developing and Validating a New Classroom Climate Observation Assessment Tool.

PubMed

Leff, Stephen S; Thomas, Duane E; Shapiro, Edward S; Paskewich, Brooke; Wilson, Kim; Necowitz-Hoffman, Beth; Jawad, Abbas F

2011-01-01

The climate of school classrooms, shaped by a combination of teacher practices and peer processes, is an important determinant for children's psychosocial functioning and is a primary factor affecting bullying and victimization. Given that there are relatively few theoretically-grounded and validated assessment tools designed to measure the social climate of classrooms, our research team developed an observation tool through participatory action research (PAR). This article details how the assessment tool was designed and preliminarily validated in 18 third-, fourth-, and fifth-grade classrooms in a large urban public school district. The goals of this study are to illustrate the feasibility of a PAR paradigm in measurement development, ascertain the psychometric properties of the assessment tool, and determine associations with different indices of classroom levels of relational and physical aggression.

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

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Can feedback analysis be used to uncover the physical origin of climate sensitivity and efficacy differences?

NASA Astrophysics Data System (ADS)

Rieger, Vanessa S.; Dietmüller, Simone; Ponater, Michael

2017-10-01

Different strengths and types of radiative forcings cause variations in the climate sensitivities and efficacies. To relate these changes to their physical origin, this study tests whether a feedback analysis is a suitable approach. For this end, we apply the partial radiative perturbation method. Combining the forward and backward calculation turns out to be indispensable to ensure the additivity of feedbacks and to yield a closed forcing-feedback-balance at top of the atmosphere. For a set of CO2-forced simulations, the climate sensitivity changes with increasing forcing. The albedo, cloud and combined water vapour and lapse rate feedback are found to be responsible for the variations in the climate sensitivity. An O3-forced simulation (induced by enhanced NOx and CO surface emissions) causes a smaller efficacy than a CO2-forced simulation with a similar magnitude of forcing. We find that the Planck, albedo and most likely the cloud feedback are responsible for this effect. Reducing the radiative forcing impedes the statistical separability of feedbacks. We additionally discuss formal inconsistencies between the common ways of comparing climate sensitivities and feedbacks. Moreover, methodical recommendations for future work are given.

Sensitivity analysis and metamodeling of a toolchain of models to help sizing vetetative filter strips in a watershed.

NASA Astrophysics Data System (ADS)

Lauvernet, Claire; Noll, Dorothea; Muñoz-Carpena, Rafael; Carluer, Nadia

2014-05-01

In Europe, environmental agencies do the finding a significant presence of contaminants in surface water, which is partly due to pesticide applications. Vegetative filter strips (VFS), often located along rivers, are a common tool among other buffer zones to reduce non point source pollution of water by reducing surface runoff. However, they need to be adapted to the agro-pedo-climatic conditions, both in terms of position and size, in order to be efficient. This is one of the roles of TOPPS-PROWADIS project which involves European experts and stakeholders to develop and recommend Best Management Practices (BMPs) to reduce pesticide transfer by drift or runoff in several European countries. In this context, Irstea developed a guide accompanying the use of different tools, which allows designing VFS by simulating their efficiency to limit transfers. It needs the user to define both a scenario of incoming surface runoff and the buffer zone characteristics. First, the contributive zone (surface, length, slope) is derived from the topography by a GIS tool, HydroDem. ; 2nd, the runoff hydrograph coming in the buffer zone is generated from a rainfall hyetogram typical of the area, using Curve Number theory, taking into account soil characteristics. The VFS's optimal width is then deduced for a given desired efficiency (for example 70% of runoff reduction), by using VFSMOD model, which simulates water, suspended matters (and pesticides) transfer inside a vegetative filter strip. Results also indicate if this kind of buffer zone is relevant in that situation (if too high, another type of buffer zone may be more relevant, for example constructed wetland). This method assumes that the user supplies quite a lot of field knowledge and data, which are not always easily available. In order to fill in the lack of real data, a set of virtual scenarios was tested, which is supposed to cover a large range of agro-pedo-climatic conditions in Europe, considering both the upslope agricultural field and the VFS characteristics. These scenarios are based on: 2 types of climates (North and South-west of France), different rainfall intensities and durations, different lengths and slopes of hillslope, different humidity conditions, 4 soil types (silt loam, sandy loam, clay loam, sandy clay loam), 2 crops (wheat and corn) for the contributive area, 2 water table depths (1m and 2.5m) and 4 soil types for the VFS. The sizing method was applied for all these scenarios, and a sensitivity analysis of the VFS optimal length was performed for all the input parameters in order to understand their influence, and to identify for which a special care has to be given. Based on that sensitivity analysis, a metamodel has been developed. The idea is to simplify the whole toolchain and to make it possible to perform the buffer sizing by using a unique tool and a smaller set of parameters, given the available information from the end users. We first compared several mathematical methods to compute the metamodel, and then validated them on an agricultural watershed with real data in the North-West of France.

Climate Voyager: An Iteratively Built Information and Visualization Tool for At-Risk Climate Communities

NASA Astrophysics Data System (ADS)

Terando, A. J.; Lascurain, A.; Aldridge, H. D.; Davis, C.

2016-12-01

Climate Voyager provides an innovative way to visualize both large-scale and local climate change projections using a three-map layout and time series plot. This product includes a suite of tools designed to assist with climate risk and opportunity assessments, including changes in average seasonal conditions and the capability to evaluate a variety of different decision-relevant thresholds (e.g. changes in extreme temperature occurrence). Each tool summarizes output from 20 downscaled global climate models and contains a historical average for comparison with the spread of projected future outcomes. The Climate Voyager website is interactive, allowing users to explore both regional and location-specific guidance for two Representative Concentration Pathways (RCPs) and four future 20-year time periods. By presenting climate model projections and measures of uncertainty of specific parameters beyond just annual temperatures and precipitation, Climate Voyager can help a wide variety of decision makers plan for climate changes that may affect them. We present a case study in which a new module was developed within Climate Voyager for use by Tribes and native communities in the eastern U.S. to help make informed resource decisions. In this first attempt, Ramps (Allium tricoccum), a plant species of great cultural significance, was incorporated through consultation with the tribal organization. We will also discuss the process of engagement employed with end-users and the potential to make the Climate Voyager interface an iterative, co-produced process to enhance the usability of climate model information for adaptation planning.

Climate Twins - a tool to explore future climate impacts by assessing real world conditions: Exploration principles, underlying data, similarity conditions and uncertainty ranges

NASA Astrophysics Data System (ADS)

Loibl, Wolfgang; Peters-Anders, Jan; Züger, Johann

2010-05-01

To achieve public awareness and thorough understanding about expected climate changes and their future implications, ways have to be found to communicate model outputs to the public in a scientifically sound and easily understandable way. The newly developed Climate Twins tool tries to fulfil these requirements via an intuitively usable web application, which compares spatial patterns of current climate with future climate patterns, derived from regional climate model results. To get a picture of the implications of future climate in an area of interest, users may click on a certain location within an interactive map with underlying future climate information. A second map depicts the matching Climate Twin areas according to current climate conditions. In this way scientific output can be communicated to the public which allows for experiencing climate change through comparison with well-known real world conditions. To identify climatic coincidence seems to be a simple exercise, but the accuracy and applicability of the similarity identification depends very much on the selection of climate indicators, similarity conditions and uncertainty ranges. Too many indicators representing various climate characteristics and too narrow uncertainty ranges will judge little or no area as regions with similar climate, while too little indicators and too wide uncertainty ranges will address too large regions as those with similar climate which may not be correct. Similarity cannot be just explored by comparing mean values or by calculating correlation coefficients. As climate change triggers an alteration of various indicators, like maxima, minima, variation magnitude, frequency of extreme events etc., the identification of appropriate similarity conditions is a crucial question to be solved. For Climate Twins identification, it is necessary to find a right balance of indicators, similarity conditions and uncertainty ranges, unless the results will be too vague conducting a useful Climate Twins regions search. The Climate Twins tool works actually comparing future climate conditions of a certain source area in the Greater Alpine Region with current climate conditions of entire Europe and the neighbouring southern as well south-eastern areas as target regions. A next version will integrate web crawling features for searching information about climate-related local adaptations observed today in the target region which may turn out as appropriate solution for the source region under future climate conditions. The contribution will present the current tool functionally and will discuss which indicator sets, similarity conditions and uncertainty ranges work best to deliver scientifically sound climate comparisons and distinct mapping results.

A collaborative characterization of North American grasslands and rangelands: climate, ecohydrology and carbon sink-source dynamics

NASA Astrophysics Data System (ADS)

Petrie, M. D.; Brunsell, N. A.; Vargas, R.; Collins, S. L.

2013-12-01

Grassland and rangeland ecoregions extend across the North American continent and exhibit diversity in climate, ecosystem services, and biophysical processes. In many grasslands and rangelands, the potential for reductions in ecosystem services and for large-scale ecosystem state change may increase under future climate scenarios. Climate change projections for North America vary, however, and the way changing climate will influence specific ecoregions is largely unknown. To better understand the regional effects of climate change on grasslands and rangelands, it is important to better understand the biophysical characteristics of these systems locally, and to identify the sensitivity of these characteristics to observed climate variation. In our study, we propose to use eddy covariance, soil moisture and precipitation data to identify how the grasslands and rangelands of North America differ in their responses to climate variability through time, with specific focus on the active growing season. Our primary goal is to determine the sensitivity of ecosystem Net Primary Productivity [NPP] to variation in temperature and precipitation patterns, and classify North American grasslands and rangelands by these sensitivities in addition to more standard climate and productivity variables. Our preliminary analyses in mesic, semiarid and arid grasslands in Kansas, Colorado and New Mexico show significant (P < 0.05) differences in climate, carbon sink strength and growing season length, and suggest that patterns of seasonal productivity and precipitation sensitivity may elucidate important grassland and rangeland responses to changing climate. Using change in Gross Primary Productivity (GPP) as an indicator of the onset of photosynthesis in spring and of senescense in the fall, grassland and rangeland ecosystems in Kansas (top and bottom left panels) and New Mexico (bottom right panel) display differing patterns of activity throughout the year.

Integrated Framework for an Urban Climate Adaptation Tool

NASA Astrophysics Data System (ADS)

Omitaomu, O.; Parish, E. S.; Nugent, P.; Mei, R.; Sylvester, L.; Ernst, K.; Absar, M.

2015-12-01

Cities have an opportunity to become more resilient to future climate change through investments made in urban infrastructure today. However, most cities lack access to credible high-resolution climate change projection information needed to assess and address potential vulnerabilities from future climate variability. Therefore, we present an integrated framework for developing an urban climate adaptation tool (Urban-CAT). Urban-CAT consists of four modules. Firstly, it provides climate projections at different spatial resolutions for quantifying urban landscape. Secondly, this projected data is combined with socio-economic data using leading and lagging indicators for assessing landscape vulnerability to climate extremes (e.g., urban flooding). Thirdly, a neighborhood scale modeling approach is presented for identifying candidate areas for adaptation strategies (e.g., green infrastructure as an adaptation strategy for urban flooding). Finally, all these capabilities are made available as a web-based tool to support decision-making and communication at the neighborhood and city levels. In this paper, we present some of the methods that drive each of the modules and demo some of the capabilities available to-date using the City of Knoxville in Tennessee as a case study.

Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

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

De Kauwe, M. G.; Zhou, S. -X.; Medlyn, B. E.

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSMmore » and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Furthermore, our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.« less

Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

DOE PAGES

De Kauwe, M. G.; Zhou, S. -X.; Medlyn, B. E.; ...

2015-12-21

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSMmore » and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Furthermore, our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.« less

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

NASA Technical Reports Server (NTRS)

Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.

2015-01-01

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

Climate change refugia as a tool for climate adaptation

EPA Science Inventory

Climate change refugia, areas relatively buffered from contemporary climate change so as to increase persistence of valued physical, ecological, and cultural resources, are considered as potential adaptation options in the face of anthropogenic climate change. In a collaboration ...

A sensitive slope: estimating landscape patterns of forest resilience in a changing climate

Treesearch

Jill F. Johnstone; Eliot J.B. McIntire; Eric J. Pedersen; Gregory King; Michael J.F. Pisaric

2010-01-01

Changes in Earth's environment are expected to stimulate changes in the composition and structure of ecosystems, but it is still unclear how the dynamics of these responses will play out over time. In long-lived forest systems, communities of established individuals may be resistant to respond to directional climate change, but may be highly sensitive to climate...

Earth system sensitivity inferred from Pliocene modelling and data

USGS Publications Warehouse

Lunt, D.J.; Haywood, A.M.; Schmidt, G.A.; Salzmann, U.; Valdes, P.J.; Dowsett, H.J.

2010-01-01

Quantifying the equilibrium response of global temperatures to an increase in atmospheric carbon dioxide concentrations is one of the cornerstones of climate research. Components of the Earths climate system that vary over long timescales, such as ice sheets and vegetation, could have an important effect on this temperature sensitivity, but have often been neglected. Here we use a coupled atmosphere-ocean general circulation model to simulate the climate of the mid-Pliocene warm period (about three million years ago), and analyse the forcings and feedbacks that contributed to the relatively warm temperatures. Furthermore, we compare our simulation with proxy records of mid-Pliocene sea surface temperature. Taking these lines of evidence together, we estimate that the response of the Earth system to elevated atmospheric carbon dioxide concentrations is 30-50% greater than the response based on those fast-adjusting components of the climate system that are used traditionally to estimate climate sensitivity. We conclude that targets for the long-term stabilization of atmospheric greenhouse-gas concentrations aimed at preventing a dangerous human interference with the climate system should take into account this higher sensitivity of the Earth system. ?? 2010 Macmillan Publishers Limited. All rights reserved.

OpenNEX, a private-public partnership in support of the national climate assessment

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Wang, W.; Michaelis, A.; Votava, P.; Ganguly, S.

2016-12-01

The NASA Earth Exchange (NEX) is a collaborative computing platform that has been developed with the objective of bringing scientists together with the software tools, massive global datasets, and supercomputing resources necessary to accelerate research in Earth systems science and global change. NEX is funded as an enabling tool for sustaining the national climate assessment. Over the past five years, researchers have used the NEX platform and produced a number of data sets highly relevant to the National Climate Assessment. These include high-resolution climate projections using different downscaling techniques and trends in historical climate from satellite data. To enable a broader community in exploiting the above datasets, the NEX team partnered with public cloud providers to create the OpenNEX platform. OpenNEX provides ready access to NEX data holdings on a number of public cloud platforms along with pertinent analysis tools and workflows in the form of Machine Images and Docker Containers, lectures and tutorials by experts. We will showcase some of the applications of OpenNEX data and tools by the community on Amazon Web Services, Google Cloud and the NEX Sandbox.

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

Nugent, Philip J; Omitaomu, Olufemi A; Parish, Esther S

The urban climate is changing rapidly. Therefore, climate change and its projected impacts on environmental conditions must be considered in assessing and comparing urban planning alternatives. In this paper, we present an integrated framework for urban climate adaptation tool (Urban-CAT) that will help cities to plan for, rather than react to, possible risks. Urban-CAT will be developed as a scenario planning tool that is locally relevant to existing urban decision-making processes.

Urban-Climate Adaptation Tool: Optimizing Green Infrastructure

NASA Astrophysics Data System (ADS)

Fellows, J. D.; Bhaduri, B. L.

2016-12-01

Cities have an opportunity to become more resilient to future climate change and green through investments made in urban infrastructure today. However, most cities lack access to credible high-resolution climate change projection and other environmental information needed to assess and address potential vulnerabilities from future climate variability. Therefore, we present an integrated framework for developing an urban climate adaptation tool (Urban-CAT). The initial focus of Urban-CAT is to optimize the placement of green infrastructure (e.g., green roofs, porous pavements, retention basins, etc.) to be better control stormwater runoff and lower the ambient urban temperature. Urban-CAT consists of four modules. Firstly, it provides climate projections at different spatial resolutions for quantifying urban landscape. Secondly, this projected data is combined with socio-economic and other environmental data using leading and lagging indicators for assessing landscape vulnerability to climate extremes (e.g., urban flooding). Thirdly, a neighborhood scale modeling approach is presented for identifying candidate areas for adaptation strategies (e.g., green infrastructure as an adaptation strategy for urban flooding). Finally, all these capabilities are made available as a web-based tool to support decision-making and communication at the neighborhood and city levels. This presentation will highlight the methods that drive each of the modules, demo some of the capabilities using Knoxville Tennessee as a case study, and discuss the challenges of working with communities to incorporate climate change into their planning. Next steps on Urban-CAT is to additional capabilities to create a comprehensive climate adaptation tool, including energy, transportation, health, and other key urban services.

Full annual cycle climate change vulnerability assessment for migratory birds

USGS Publications Warehouse

Culp, Leah A.; Cohen, Emily B.; Scarpignato, Amy L.; Thogmartin, Wayne E.; Marra, Peter P.

2017-01-01

Climate change is a serious challenge faced by all plant and animal species. Climate change vulnerability assessments (CCVAs) are one method to assess risk and are increasingly used as a tool to inform management plans. Migratory animals move across regions and continents during their annual cycles where they are exposed to diverse climatic conditions. Climate change during any period and in any region of the annual cycle could influence survival, reproduction, or the cues used to optimize timing of migration. Therefore, CCVAs for migratory animals best estimate risk when they include climate exposure during the entire annual cycle. We developed a CCVA incorporating the full annual cycle and applied this method to 46 species of migratory birds breeding in the Upper Midwest and Great Lakes (UMGL) region of the United States. Our methodology included background risk, climate change exposure × climate sensitivity, adaptive capacity to climate change, and indirect effects of climate change. We compiled information about migratory connectivity between breeding and stationary non-breeding areas using literature searches and U.S. Geological Survey banding and re-encounter data. Climate change exposure (temperature and moisture) was assessed using UMGL breeding season climate and winter climate from non-breeding regions for each species. Where possible, we focused on non-breeding regions known to be linked through migratory connectivity. We ranked 10 species as highly vulnerable to climate change and two as having low vulnerability. The remaining 34 species were ranked as moderately vulnerable. In general, including non-breeding data provided more robust results that were highly individualistic by species. Two species were found to be highly vulnerable throughout their annual cycle. Projected drying will have the greatest effect during the non-breeding season for species overwintering in Mexico and the Caribbean. Projected temperature increases will have the greatest effect during the breeding season in UMGL as well as during the non-breeding season for species overwintering in South America. We provide a model for adaptive management of migratory animals in the face of projected climate change, including identification of priority species, research needs, and regions within non-breeding ranges for potential conservation partnerships.

Validating a work group climate assessment tool for improving the performance of public health organizations

PubMed Central

Perry, Cary; LeMay, Nancy; Rodway, Greg; Tracy, Allison; Galer, Joan

2005-01-01

Background This article describes the validation of an instrument to measure work group climate in public health organizations in developing countries. The instrument, the Work Group Climate Assessment Tool (WCA), was applied in Brazil, Mozambique, and Guinea to assess the intermediate outcomes of a program to develop leadership for performance improvement. Data were collected from 305 individuals in 42 work groups, who completed a self-administered questionnaire. Methods The WCA was initially validated using Cronbach's alpha reliability coefficient and exploratory factor analysis. This article presents the results of a second validation study to refine the initial analyses to account for nested data, to provide item-level psychometrics, and to establish construct validity. Analyses included eigenvalue decomposition analysis, confirmatory factor analysis, and validity and reliability analyses. Results This study confirmed the validity and reliability of the WCA across work groups with different demographic characteristics (gender, education, management level, and geographical location). The study showed that there is agreement between the theoretical construct of work climate and the items in the WCA tool across different populations. The WCA captures a single perception of climate rather than individual sub-scales of clarity, support, and challenge. Conclusion The WCA is useful for comparing the climates of different work groups, tracking the changes in climate in a single work group over time, or examining differences among individuals' perceptions of their work group climate. Application of the WCA before and after a leadership development process can help work groups hold a discussion about current climate and select a target for improvement. The WCA provides work groups with a tool to take ownership of their own group climate through a process that is simple and objective and that protects individual confidentiality. PMID:16223447

The Milankovitch theory and climate sensitivity. I - Equilibrium climate model solutions for the present surface conditions. II - Interaction between the Northern Hemisphere ice sheets and the climate system

NASA Technical Reports Server (NTRS)

Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

1988-01-01

A seasonal climate model was developed to test the climate sensitivity and, in particular, the Milankovitch (1941) theory. Four climate model versions were implemented to investigate the range of uncertainty in the parameterizations of three basic feedback mechanisms: the ice albedo-temperature, the outgoing long-wave radiation-temperature, and the eddy transport-meridional temperature gradient. It was found that the differences between the simulation of the present climate by the four versions were generally small, especially for annually averaged results. The climate model was also used to study the effect of growing/shrinking of a continental ice sheet, bedrock sinking/uplifting, and sea level changes on the climate system, taking also into account the feedback effects on the climate of the building of the ice caps.

Hands-on Approach to Prepare Specialists in Climate Changes Modeling and Analysis Using an Information-Computational Web-GIS Portal "Climate"

NASA Astrophysics Data System (ADS)

Shulgina, T. M.; Gordova, Y. E.; Martynova, Y. V.

2014-12-01

A problem of making education relevant to the workplace tasks is a key problem of higher education in the professional field of environmental sciences. To answer this challenge several new courses for students of "Climatology" and "Meteorology" specialties were developed and implemented at the Tomsk State University, which comprises theoretical knowledge from up-to-date environmental sciences with computational tasks. To organize the educational process we use an open-source course management system Moodle (www.moodle.org). It gave us an opportunity to combine text and multimedia in a theoretical part of educational courses. The hands-on approach is realized through development of innovative trainings which are performed within the information-computational web GIS platform "Climate" (http://climate.scert.ru/). The platform has a set of tools and data bases allowing a researcher to perform climate changes analysis on the selected territory. The tools are also used for students' trainings, which contain practical tasks on climate modeling and climate changes assessment and analysis. Laboratory exercises are covering three topics: "Analysis of regional climate changes"; "Analysis of climate extreme indices on the regional scale"; and "Analysis of future climate". They designed to consolidate students' knowledge of discipline, to instill in them the skills to work independently with large amounts of geophysical data using modern processing and analysis tools of web-GIS platform "Climate" and to train them to present results obtained on laboratory work as reports with the statement of the problem, the results of calculations and logically justified conclusion. Thus, students are engaged in n the use of modern tools of the geophysical data analysis and it cultivates dynamic of their professional learning. The approach can help us to fill in this gap because it is the only approach that offers experience, increases students involvement, advance the use of modern information and communication tools. Financial support for this research from the RFBR (13-05-12034, 14-05-00502), SB RAS project VIII.80.2.1 and grant of the President of RF (№ 181) is acknowledged.

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.

Assessing gendered roles in water decision-making in semi-arid regions through sex-disaggregated water data with UNESCO-WWAP gender toolkit

NASA Astrophysics Data System (ADS)

Miletto, Michela; Greco, Francesca; Belfiore, Elena

2017-04-01

Global climate change is expected to exacerbate current and future stresses on water resources from population growth and land use, and increase the frequency and severity of droughts and floods. Women are more vulnerable to the effects of climate change than men not only because they constitute the majority of the world's poor but also because they are more dependent for their livelihood on natural resources that are threatened by climate change. In addition, social, economic and political barriers often limit their coping capacity. Women play a key role in the provision, management and safeguarding of water, nonetheless, gender inequality in water management framework persists around the globe. Sharp data are essential to inform decisions and support effective policies. Disaggregating water data by sex is crucial to analyse gendered roles in the water realm and inform gender sensitive water policies in light of the global commitments to gender equality of Agenda 2030. In view of this scenario, WWAP has created an innovative toolkit for sex-disaggregated water data collection, as a result of a participatory work of more than 35 experts, part of the WWAP Working Group on Sex-Disaggregated Indicators (http://www.unesco.org/new/en/natural-sciences/environment/water/wwap/water-and-gender/un-wwap-working-group-on-gender-disaggregated-indicators/#c1430774). The WWAP toolkit contains four tools: the methodology (Seager J. WWAP UNESCO, 2015), set of key indicators, the guideline (Pangare V.,WWAP UNESCO, 2015) and a questionnaire for field survey. WWAP key gender-sensitive indicators address water resources management, aspects of water quality and agricultural uses, water resources governance and management, and investigate unaccounted labour in according to gender and age. Managing water resources is key for climate adaptation. Women are particularly sensitive to water quality and the health of water-dependent ecosystems, often source of food and job opportunities. Extreme climatic events like floods and droughts could severely impact the status of water resources and dependent ecosystems and the sustainability of household activities and local economies, given the absence of gender sensitive preparedness to hydrological and meteorological extremes. This paper describes the application of the WWAP Gender Toolkit to water data assessments in semi-arid region of the Stampriet transboundary aquifer shared by Botwana, Namibia and South Africa, in the framework of the "Groundwater Resources Governance in Transboundary Aquifers" - GGRETA project, led and executed by the UNESCO International Hydrological Programme (IHP), and financed by the Swiss Agency for Development and Cooperation (SDC). The tests in the field proved the reliability of WWAP gender toolkit and selected gender-sensitive indicators in the freshwater assessment. Further analysis could inform on the gaps and needs for climate adaptation practices. Field data identified socially-determined differences in roles, and confirmed the prevalent role of women in managing freshwater for drinking and sanitation purposes within the household boundaries, while decision-making for water allocation and use (with implications on hydrological risk) for agriculture and livestock purposes, is broadly under men's responsibility.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-09-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-04-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

The importance of geomorphic and hydrologic factors in shaping the sensitivity of alpine/subalpine lake volumes to shifts in climate

NASA Astrophysics Data System (ADS)

Mercer, J.; Liefert, D. T.; Shuman, B. N.; Befus, K. M.; Williams, D. G.; Kraushaar, B.

2017-12-01

Alpine and subalpine lakes are important components of the hydrologic cycle in mountain ecosystems. These lakes are also highly sensitive to small shifts in temperature and precipitation. Mountain lake volumes and their contributions to mountain hydrology may change in response to even minor declines in snowpack or increases in temperature. However, it is still not clear to what degree non-climatic factors, such as geomorphic setting and lake geometry, play in shaping the sensitivity of high elevation lakes to climate change. We investigated the importance of lake geometry and groundwater connectivity to mountain lakes in the Snowy Range, Wyoming using a combination of hydrophysical and hydrochemical methods, including stable water isotopes, to better understand the role these factors play in controlling lake volume. Water isotope values in open lakes were less sensitive to evaporation compared to those in closed basin lakes. Lake geometry played an important role, with wider, shallower lakes being more sensitive to evaporation over time. Groundwater contributions appear to play only a minor role in buffering volumetric changes to lakes over the growing season. These results confirm that mountain lakes are sensitive to climate factors, but also highlight a significant amount of variability in that sensitivity. This research has implications for water resource managers concerned with downstream water quantity and quality from mountain ecosystems, biologists interested in maintaining aquatic biodiversity, and paleoclimatologists interested in using lake sedimentary information to infer past climate regimes.

Space-based Remote Sensing: A Tool for Studying Bird Migration Across Multiple Scales

NASA Technical Reports Server (NTRS)

Smith, James A.

2005-01-01

The study of bird migration on a global scale is one of the compelling and challenging problems of modern biology with major implications for human health and conservation biology. Migration and conservation efforts cross national boundaries and are subject to numerous international agreements and treaties. Space based technology offers new opportunities to shed understanding on the distribution and migration of organisms on the planet and their sensitivity to human disturbances and environmental changes. Our working hypothesis is that individual organism biophysical models of energy and water balance, driven by satellite measurements of spatio-temporal gradients in climate and habitat, will help us to explain the variability in avian species richness and distribution. Further, these models provide an ecological forecasting tool for science and application users to visualize the possible consequences of loss of wetlands, flooding, or other natural disasters such as hurricanes on avian biodiversity and bird migration.

Greenhouse gas scenario sensitivity and uncertainties in precipitation projections for central Belgium

NASA Astrophysics Data System (ADS)

Van Uytven, E.; Willems, P.

2018-03-01

Climate change impact assessment on meteorological variables involves large uncertainties as a result of incomplete knowledge on the future greenhouse gas concentrations and climate model physics, next to the inherent internal variability of the climate system. Given that the alteration in greenhouse gas concentrations is the driver for the change, one expects the impacts to be highly dependent on the considered greenhouse gas scenario (GHS). In this study, we denote this behavior as GHS sensitivity. Due to the climate model related uncertainties, this sensitivity is, at local scale, not always that strong as expected. This paper aims to study the GHS sensitivity and its contributing role to climate scenarios for a case study in Belgium. An ensemble of 160 CMIP5 climate model runs is considered and climate change signals are studied for precipitation accumulation, daily precipitation intensities and wet day frequencies. This was done for the different seasons of the year and the scenario periods 2011-2040, 2031-2060, 2051-2081 and 2071-2100. By means of variance decomposition, the total variance in the climate change signals was separated in the contribution of the differences in GHSs and the other model-related uncertainty sources. These contributions were found dependent on the variable and season. Following the time of emergence concept, the GHS uncertainty contribution is found dependent on the time horizon and increases over time. For the most distinct time horizon (2071-2100), the climate model uncertainty accounts for the largest uncertainty contribution. The GHS differences explain up to 18% of the total variance in the climate change signals. The results point further at the importance of the climate model ensemble design, specifically the ensemble size and the combination of climate models, whereupon climate scenarios are based. The numerical noise, introduced at scales smaller than the skillful scale, e.g. at local scale, was not considered in this study.

Assessment of bias correction under transient climate change

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Vannitsem, Stéphane

2015-04-01

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

Climate Neutral Research Campuses | NREL

Science.gov Websites

the background. Set an example for climate neutrality. Use NREL's climate action planning process and more. Climate Action Planning Process Identify the best technology options for a climate action plan . Climate Action Planning Tool Identify the best technology options for a climate action plan. Technology

Garrison Leadership: Enlisting Others

DTIC Science & Technology

2010-01-01

days), the GC should conduct an organizational diagnosis to assess the culture and command climate using the existing IMCOM tools of the or...conduct an organizational diagnosis to assess the culture and command climate using the existing IMCOM tools of the or- ganizational self-assessment

Individualistic sensitivities and exposure to climate change explain variation in species’ distribution and abundance changes

PubMed Central

Palmer, Georgina; Hill, Jane K.; Brereton, Tom M.; Brooks, David R.; Chapman, Jason W.; Fox, Richard; Oliver, Tom H.; Thomas, Chris D.

2015-01-01

The responses of animals and plants to recent climate change vary greatly from species to species, but attempts to understand this variation have met with limited success. This has led to concerns that predictions of responses are inherently uncertain because of the complexity of interacting drivers and biotic interactions. However, we show for an exemplar group of 155 Lepidoptera species that about 60% of the variation among species in their abundance trends over the past four decades can be explained by species-specific exposure and sensitivity to climate change. Distribution changes were less well predicted, but nonetheless, up to 53% of the variation was explained. We found that species vary in their overall sensitivity to climate and respond to different components of the climate despite ostensibly experiencing the same climate changes. Hence, species have undergone different levels of population “forcing” (exposure), driving variation among species in their national-scale abundance and distribution trends. We conclude that variation in species’ responses to recent climate change may be more predictable than previously recognized. PMID:26601276

Geobiological constraints on Earth system sensitivity to CO₂ during the Cretaceous and Cenozoic.

PubMed

Royer, D L; Pagani, M; Beerling, D J

2012-07-01

Earth system climate sensitivity (ESS) is the long-term (>10³ year) response of global surface temperature to doubled CO₂ that integrates fast and slow climate feedbacks. ESS has energy policy implications because global temperatures are not expected to decline appreciably for at least 10³ year, even if anthropogenic greenhouse gas emissions drop to zero. We report provisional ESS estimates of 3 °C or higher for some of the Cretaceous and Cenozoic based on paleo-reconstructions of CO₂ and temperature. These estimates are generally higher than climate sensitivities simulated from global climate models for the same ancient periods (approximately 3 °C). Climate models probably do not capture the full suite of positive climate feedbacks that amplify global temperatures during some globally warm periods, as well as other characteristic features of warm climates such as low meridional temperature gradients. These absent feedbacks may be related to clouds, trace greenhouse gases (GHGs), seasonal snow cover, and/or vegetation, especially in polar regions. Better characterization and quantification of these feedbacks is a priority given the current accumulation of atmospheric GHGs. © 2012 Blackwell Publishing Ltd.

Carbon Climate Feedbacks and Climate Sensitivity (Invited)

NASA Astrophysics Data System (ADS)

Fung, I.

2009-12-01

The Charney report (22 pages including bibliography and appendices) was written when atmospheric CO2 was 334 ppmv (1979). It estimates a climate sensitivity of 3 +/- 1.5C for a doubling of CO2, and points out the warming delay due to the slow penetration of heat into intermediate depths in the oceans and the decreasing capacity of the oceans to serve a CO2 sink. “We may not be given a warning until the CO2 loading is such that an appreciable climate change is inevitable. The equilibrium warming will eventually occur; it will merely have been postponed.” CO2 exceeded 385 ppmv in 2008, and the warning signs are now abundantly evident. One of the “slow” feedbacks not included in the Charney Report involves the interaction between the land carbon cycle and climate change. The carbon cycle on land is coupled to the water and energy cycles. This paper reviews positive and negative carbon-climate feedbacks associated with changes in the function and distribution of land ecosystems. These feedbacks, once in gear, will magnify climate sensitivity and accelerate global warming.

A model of nitrous oxide evolution from soil driven by rainfall events. I - Model structure and sensitivity. II - Model applications

NASA Technical Reports Server (NTRS)

Changsheng, LI; Frolking, Steve; Frolking, Tod A.

1992-01-01

Simulations of N2O and CO2 emissions from soils were conducted with a rain-event driven, process-oriented model (DNDC) of nitrogen and carbon cycling processes in soils. The magnitude and trends of simulated N2O (or N2O + N2) and CO2 emissions were consistent with the results obtained in field experiments. The successful simulation of these emissions from the range of soil types examined demonstrates that the DNDC will be a useful tool for the study of linkages among climate, soil-atmosphere interactions, land use, and trace gas fluxes.

Objectively combining AR5 instrumental period and paleoclimate climate sensitivity evidence

NASA Astrophysics Data System (ADS)

Lewis, Nicholas; Grünwald, Peter

2018-03-01

Combining instrumental period evidence regarding equilibrium climate sensitivity with largely independent paleoclimate proxy evidence should enable a more constrained sensitivity estimate to be obtained. Previous, subjective Bayesian approaches involved selection of a prior probability distribution reflecting the investigators' beliefs about climate sensitivity. Here a recently developed approach employing two different statistical methods—objective Bayesian and frequentist likelihood-ratio—is used to combine instrumental period and paleoclimate evidence based on data presented and assessments made in the IPCC Fifth Assessment Report. Probabilistic estimates from each source of evidence are represented by posterior probability density functions (PDFs) of physically-appropriate form that can be uniquely factored into a likelihood function and a noninformative prior distribution. The three-parameter form is shown accurately to fit a wide range of estimated climate sensitivity PDFs. The likelihood functions relating to the probabilistic estimates from the two sources are multiplicatively combined and a prior is derived that is noninformative for inference from the combined evidence. A posterior PDF that incorporates the evidence from both sources is produced using a single-step approach, which avoids the order-dependency that would arise if Bayesian updating were used. Results are compared with an alternative approach using the frequentist signed root likelihood ratio method. Results from these two methods are effectively identical, and provide a 5-95% range for climate sensitivity of 1.1-4.05 K (median 1.87 K).

The influence of local spring temperature variance on temperature sensitivity of spring phenology.

PubMed

Wang, Tao; Ottlé, Catherine; Peng, Shushi; Janssens, Ivan A; Lin, Xin; Poulter, Benjamin; Yue, Chao; Ciais, Philippe

2014-05-01

The impact of climate warming on the advancement of plant spring phenology has been heavily investigated over the last decade and there exists great variability among plants in their phenological sensitivity to temperature. However, few studies have explicitly linked phenological sensitivity to local climate variance. Here, we set out to test the hypothesis that the strength of phenological sensitivity declines with increased local spring temperature variance, by synthesizing results across ground observations. We assemble ground-based long-term (20-50 years) spring phenology database (PEP725 database) and the corresponding climate dataset. We find a prevalent decline in the strength of phenological sensitivity with increasing local spring temperature variance at the species level from ground observations. It suggests that plants might be less likely to track climatic warming at locations with larger local spring temperature variance. This might be related to the possibility that the frost risk could be higher in a larger local spring temperature variance and plants adapt to avoid this risk by relying more on other cues (e.g., high chill requirements, photoperiod) for spring phenology, thus suppressing phenological responses to spring warming. This study illuminates that local spring temperature variance is an understudied source in the study of phenological sensitivity and highlight the necessity of incorporating this factor to improve the predictability of plant responses to anthropogenic climate change in future studies. © 2013 John Wiley & Sons Ltd.

The impacts of land use, radiative forcing, and biological changes on regional climate in Japan

NASA Astrophysics Data System (ADS)

Dairaku, K.; Pielke, R. A., Sr.

2013-12-01

Because regional responses of surface hydrological and biogeochemical changes are particularly complex, it is necessary to develop assessment tools for regional scale adaptation to climate. We developed a dynamical downscaling method using the regional climate model (NIED-RAMS) over Japan. The NIED-RAMS model includes a plant model that considers biological processes, the General Energy and Mass Transfer Model (GEMTM) which adds spatial resolution to accurately assess critical interactions within the regional climate system for vulnerability assessments to climate change. We digitalized a potential vegetation map that formerly existed only on paper into Geographic Information System data. It quantified information on the reduction of green spaces and the expansion of urban and agricultural areas in Japan. We conducted regional climate sensitivity experiments of land use and land cover (LULC) change, radiative forcing, and biological effects by using the NIED-RAMS with horizontal grid spacing of 20 km. We investigated regional climate responses in Japan for three experimental scenarios: 1. land use and land cover is changed from current to potential vegetation; 2. radiative forcing is changed from 1 x CO2 to 2 x CO2; and 3. biological CO2 partial pressures in plants are doubled. The experiments show good accuracy in reproducing the surface air temperature and precipitation. The experiments indicate the distinct change of hydrological cycles in various aspects due to anthropogenic LULC change, radiative forcing, and biological effects. The relative impacts of those changes are discussed and compared. Acknowledgments This study was conducted as part of the research subject "Vulnerability and Adaptation to Climate Change in Water Hazard Assessed Using Regional Climate Scenarios in the Tokyo Region' (National Research Institute for Earth Science and Disaster Prevention; PI: Koji Dairaku) of Research Program on Climate Change Adaptation (RECCA), and was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.

Sensitivity of proxies on non-linear interactions in the climate system

PubMed Central

Schultz, Johannes A.; Beck, Christoph; Menz, Gunter; Neuwirth, Burkhard; Ohlwein, Christian; Philipp, Andreas

2015-01-01

Recent climate change is affecting the earth system to an unprecedented extent and intensity and has the potential to cause severe ecological and socioeconomic consequences. To understand natural and anthropogenic induced processes, feedbacks, trends, and dynamics in the climate system, it is also essential to consider longer timescales. In this context, annually resolved tree-ring data are often used to reconstruct past temperature or precipitation variability as well as atmospheric or oceanic indices such as the North Atlantic Oscillation (NAO) or the Atlantic Multidecadal Oscillation (AMO). The aim of this study is to assess weather-type sensitivity across the Northern Atlantic region based on two tree-ring width networks. Our results indicate that nonstationarities in superordinate space and time scales of the climate system (here synoptic- to global scale, NAO, AMO) can affect the climate sensitivity of tree-rings in subordinate levels of the system (here meso- to synoptic scale, weather-types). This scale bias effect has the capability to impact even large multiproxy networks and the ability of these networks to provide information about past climate conditions. To avoid scale biases in climate reconstructions, interdependencies between the different scales in the climate system must be considered, especially internal ocean/atmosphere dynamics. PMID:26686001

Climate change amplifies the interactions between wind and bark beetle disturbances in forest landscapes.

PubMed

Seidl, Rupert; Rammer, Werner

2017-07-01

Growing evidence suggests that climate change could substantially alter forest disturbances. Interactions between individual disturbance agents are a major component of disturbance regimes, yet how interactions contribute to their climate sensitivity remains largely unknown. Here, our aim was to assess the climate sensitivity of disturbance interactions, focusing on wind and bark beetle disturbances. We developed a process-based model of bark beetle disturbance, integrated into the dynamic forest landscape model iLand (already including a detailed model of wind disturbance). We evaluated the integrated model against observations from three wind events and a subsequent bark beetle outbreak, affecting 530.2 ha (3.8 %) of a mountain forest landscape in Austria between 2007 and 2014. Subsequently, we conducted a factorial experiment determining the effect of changes in climate variables on the area disturbed by wind and bark beetles separately and in combination. iLand was well able to reproduce observations with regard to area, temporal sequence, and spatial pattern of disturbance. The observed disturbance dynamics was strongly driven by interactions, with 64.3 % of the area disturbed attributed to interaction effects. A +4 °C warming increased the disturbed area by +264.7 % and the area-weighted mean patch size by +1794.3 %. Interactions were found to have a ten times higher sensitivity to temperature changes than main effects, considerably amplifying the climate sensitivity of the disturbance regime. Disturbance interactions are a key component of the forest disturbance regime. Neglecting interaction effects can lead to a substantial underestimation of the climate change sensitivity of disturbance regimes.

Demographic Responses To Climate Manipulations Across a Species Range

NASA Astrophysics Data System (ADS)

Oldfather, M. F.

2016-12-01

Species biogeographic responses to climate change will occur through the local extinction and establishment of populations. The overall performance of populations across a species range is shaped by the idiosyncratic sensitivities of demographic rates to the changing climate conditions. Heterogeneous topography partially decouples temperature and soil moisture presenting an opportunity to disentangle demographic sensitivity to multiple local climate variables and refine range shift predictions in response to complex climate change. Since 2013, I have monitored 16 populations of a long-lived alpine plant, Ivesia lycopodioides var. scandularis (Rosaceae) across the entirety of its altitudinal range in the arid White Mountains, CA (3350 - 4420m). I quantified microclimatic soil moisture and temperature, and the demographic rates of over 4,000 individuals. Demographic rates exhibited sensitivity to accumulated degree-days (ex. reproduction), soil volumetric water content (ex. germination), or the interaction between these climate variables (ex. survival). These observations motivated an experimental test of the relationship between demography and local climate with manipulations of increased summertime temperature and precipitation in nine populations. All demographic rates were sensitive to the climate manipulations and the magnitude of the demographic response depended on the population's location within the range. However, the modeled population growth rate was only minimally affected by the manipulations in most populations. The inverse responses of many of the demographic rates may allow populations to demographically buffer against the climate manipulations. However, in one low elevation edge population the negative effect of heating on survival overwhelmed the positive effect on germination, indicating that the capacity of populations to demographically buffer may have a limit.

Geospatial Analysis Tool Kit for Regional Climate Datasets (GATOR) : An Open-source Tool to Compute Climate Statistic GIS Layers from Argonne Climate Modeling Results

DTIC Science & Technology

2017-08-01

This large repository of climate model results for North America (Wang and Kotamarthi 2013, 2014, 2015) is stored in Network Common Data Form (NetCDF...Network Common Data Form (NetCDF). UCAR/Unidata Program Center, Boulder, CO. Available at: http://www.unidata.ucar.edu/software/netcdf. Accessed on 6/20...emissions diverge from each other regarding fossil fuel use, technology, and other socioeconomic factors. As a result, the estimated emissions for each of

A Field Guide to Extra-Tropical Cyclones: Comparing Models to Observations

NASA Astrophysics Data System (ADS)

Bauer, M.

2008-12-01

Climate it is said is the accumulation of weather. And weather is not the concern of climate models. Justification for this latter sentiment has long hidden behind coarse model resolutions and blunt validation tools based on climatological maps and the like. The spatial-temporal resolutions of today's models and observations are converging onto meteorological scales however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough, or at least lacks perverting biases, such that its accumulation does in fact result in a robust climate prediction. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from climate model output. These include the usual cyclone distribution statistics (maps, histograms), but also adaptive cyclone- centric composites. We have also created a complementary dataset, The MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid- latitude cyclones based on Reanalysis products. Using this we then extract complimentary composites from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools will be shown. dime.giss.nasa.gov/mcms/mcms.html

Climate change and vector-borne diseases: what are the implications for public health research and policy?

PubMed Central

Campbell-Lendrum, Diarmid; Manga, Lucien; Bagayoko, Magaran; Sommerfeld, Johannes

2015-01-01

Vector-borne diseases continue to contribute significantly to the global burden of disease, and cause epidemics that disrupt health security and cause wider socioeconomic impacts around the world. All are sensitive in different ways to weather and climate conditions, so that the ongoing trends of increasing temperature and more variable weather threaten to undermine recent global progress against these diseases. Here, we review the current state of the global public health effort to address this challenge, and outline related initiatives by the World Health Organization (WHO) and its partners. Much of the debate to date has centred on attribution of past changes in disease rates to climate change, and the use of scenario-based models to project future changes in risk for specific diseases. While these can give useful indications, the unavoidable uncertainty in such analyses, and contingency on other socioeconomic and public health determinants in the past or future, limit their utility as decision-support tools. For operational health agencies, the most pressing need is the strengthening of current disease control efforts to bring down current disease rates and manage short-term climate risks, which will, in turn, increase resilience to long-term climate change. The WHO and partner agencies are working through a range of programmes to (i) ensure political support and financial investment in preventive and curative interventions to bring down current disease burdens; (ii) promote a comprehensive approach to climate risk management; (iii) support applied research, through definition of global and regional research agendas, and targeted research initiatives on priority diseases and population groups. PMID:25688013

A review on regional convection permitting climate modeling

NASA Astrophysics Data System (ADS)

van Lipzig, Nicole; Prein, Andreas; Brisson, Erwan; Van Weverberg, Kwinten; Demuzere, Matthias; Saeed, Sajjad; Stengel, Martin

2016-04-01

With the increase of computational resources, it has recently become possible to perform climate model integrations where at least part the of convection is resolved. Since convection-permitting models (CPMs) are performing better than models where convection is parameterized, especially for high-impact weather like extreme precipitation, there is currently strong scientific progress in this research domain (Prein et al., 2015). Another advantage of CPMs, that have a horizontal grid spacing <4 km, is that they better resolve complex orography and land use. The regional climate model COSMO-CLM is frequently applied for CPM simulations, due to its non-hydrostatic dynamics and open international network of scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using CPMs to study climate change it is necessary that these deficiencies are addressed in future research. Coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs. Brisson, E., K. Van Weverberg, M. Demuzere, A. Devis, S. Saeed, M. Stengel, N.P.M. van Lipzig, 2016. How well can a convection-permitting climate model reproduce 1 decadal statistics of precipitation, temperature and cloud characteristics? Clim. Dyn. (minor revisions). Prein, Andreas F., Wolfgang Langhans, Giorgia Fosser, Andrew Ferrone, Nikolina Ban, Klaus Goergen, Michael Keller, Merja Tölle, Oliver Gutjahr, Frauke Feser, Erwan Brisson, Stefan Kollet, Juerg Schmidli, Nicole P. M. van Lipzig, Ruby Leung. (2015) A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Reviews of Geophysics 53:10.1002/rog.v53.2, 323-361

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

Emergent Constraints for Cloud Feedbacks and Climate Sensitivity

DOE PAGES

Klein, Stephen A.; Hall, Alex

2015-10-26

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

Climate Sensitivity Controls Uncertainty in Future Terrestrial Carbon Sink

NASA Astrophysics Data System (ADS)

Schurgers, Guy; Ahlström, Anders; Arneth, Almut; Pugh, Thomas A. M.; Smith, Benjamin

2018-05-01

For the 21st century, carbon cycle models typically project an increase of terrestrial carbon with increasing atmospheric CO2 and a decrease with the accompanying climate change. However, these estimates are poorly constrained, primarily because they typically rely on a limited number of emission and climate scenarios. Here we explore a wide range of combinations of CO2 rise and climate change and assess their likelihood with the climate change responses obtained from climate models. Our results demonstrate that the terrestrial carbon uptake depends critically on the climate sensitivity of individual climate models, representing a large uncertainty of model estimates. In our simulations, the terrestrial biosphere is unlikely to become a strong source of carbon with any likely combination of CO2 and climate change in the absence of land use change, but the fraction of the emissions taken up by the terrestrial biosphere will decrease drastically with higher emissions.

Leveraging federal science data and tools to help communities & business build climate resilience

NASA Astrophysics Data System (ADS)

Herring, D.

2016-12-01

Decision-makers in every sector and region of the United States are seeking actionable science-based information to help them understand and manage their climate-related risks. Translating data, tools and information from the domain of climate science to the domains of municipal, social, and economic decision-making raises complex questions—e.g., how to communicate causes and impacts of climate variability and change; how to show projections of plausible future climate scenarios; how to characterize and quantify vulnerabilities, risks, and opportunities facing communities and businesses; and how to make and implement "win-win" adaptation plans. These are the types of challenges being addressed by a public-private partnership of federal agencies, academic institutions, non-governmental organizations, and private businesses that are contributing to the development of the U.S. Climate Resilience Toolkit (toolkit.climate.gov), a new website designed to help people build resilience to extreme events caused by both natural climate variability and long-term climate change. The site's Climate Explorer is designed to help people understand potential climate conditions over the course of this century. It offers easy access to downloadable maps, graphs, and data tables of observed and projected temperature, precipitation and other decision-relevant climate variables dating back to 1950 and out to 2100. Of course, climate change is only one of many variables affecting decisions about the future so the Toolkit also ties climate information to a wide range of other relevant tools and information to help users to explore their vulnerabilities and risks. In this session, we will describe recent enhancements to the Toolkit, lessons learned from user engagements, and evidence that our approach of coupling scientific information with actionable decision-making processes is helping Americans build resilience to climate-related impacts.

The role of updraft velocity in temporal variability of cloud hydrometeor number

NASA Astrophysics Data System (ADS)

Sullivan, Sylvia; Nenes, Athanasios; Lee, Dong Min; Oreopoulos, Lazaros

2016-04-01

Significant effort has been dedicated to incorporating direct aerosol-cloud links, through parameterization of liquid droplet activation and ice crystal nucleation, within climate models. This significant accomplishment has generated the need for understanding which parameters affecting hydrometer formation drives its variability in coupled climate simulations, as it provides the basis for optimal parameter estimation as well as robust comparison with data, and other models. Sensitivity analysis alone does not address this issue, given that the importance of each parameter for hydrometer formation depends on its variance and sensitivity. To address the above issue, we develop and use a series of attribution metrics defined with adjoint sensitivities to attribute the temporal variability in droplet and crystal number to important aerosol and dynamical parameters. This attribution analysis is done both for the NASA Global Modeling and Assimilation Office Goddard Earth Observing System Model, Version 5 and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1. Within the GEOS simulation, up to 48% of temporal variability in output ice crystal number and 61% in droplet number can be attributed to input updraft velocity fluctuations, while for the CAM simulation, they explain as much as 89% of the ice crystal number variability. This above results suggest that vertical velocity in both model frameworks is seen to be a very important (or dominant) driver of hydrometer variability. Yet, observations of vertical velocity are seldomly available (or used) to evaluate the vertical velocities in simulations; this strikingly contrasts the amount and quality of data available for aerosol-related parameters. Consequentially, there is a strong need for retrievals or measurements of vertical velocity for addressing this important knowledge gap that requires a significant investment and effort by the atmospheric community. The attribution metrics as a tool of understanding for hydrometer variability can be instrumental for understanding the source of differences between models used for aerosol-cloud-climate interaction studies.

Adapting wheat to uncertain future

NASA Astrophysics Data System (ADS)

Semenov, Mikhail; Stratonovitch, Pierre

2015-04-01

This study describes integration of climate change projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble with the LARS-WG weather generator, which delivers an attractive option for downscaling of large-scale climate projections from global climate models (GCMs) to local-scale climate scenarios for impact assessments. A subset of 18 GCMs from the CMIP5 ensemble and 2 RCPs, RCP4.5 and RCP8.5, were integrated with LARS-WG. Climate sensitivity indexes for temperature and precipitation were computed for all GCMs and for 21 regions in the world. For computationally demanding impact assessments, where it is not practical to explore all possible combinations of GCM × RCP, climate sensitivity indexes could be used to select a subset of GCMs from CMIP5 with contrasting climate sensitivity. This would allow to quantify uncertainty in impacts resulting from the CMIP5 ensemble by conducting fewer simulation experiments. As an example, an in silico design of wheat ideotype optimised for future climate scenarios in Europe was described. Two contrasting GCMs were selected for the analysis, "hot" HadGEM2-ES and "cool" GISS-E2-R-CC, along with 2 RCPs. Despite large uncertainty in climate projections, several wheat traits were identified as beneficial for the high-yielding wheat ideotypes that could be used as targets for wheat improvement by breeders.

A modeling tool to evaluate regional coral reef responses to changes in climate and ocean chemistry

USGS Publications Warehouse

Buddemeier, R.W.; Jokiel, P.L.; Zimmerman, K.M.; Lane, D.R.; Carey, J.M.; Bohling, Geoffrey C.; Martinich, J.A.

2008-01-01

We developed a spreadsheet-based model for the use of managers, conservationists, and biologists for projecting the effects of climate change on coral reefs at local-to-regional scales. The COMBO (Coral Mortality and Bleaching Output) model calculates the impacts to coral reefs from changes in average SST and CO2 concentrations, and from high temperature mortality (bleaching) events. The model uses a probabilistic assessment of the frequency of high temperature events under a future climate to address scientific uncertainties about potential adverse effects. COMBO offers data libraries and default factors for three selected regions (Hawai'i, Great Barrier Reef, and Caribbean), but it is structured with user-selectable parameter values and data input options, making possible modifications to reflect local conditions or to incorporate local expertise. Preliminary results from sensitivity analyses and simulation examples for Hawai'i demonstrate the relative importance of high temperature events, increased average temperature, and increased CO2 concentration on the future status of coral reefs; Illustrate significant interactions among variables; and allow comparisons of past environmental history with future predictions. ?? 2008, by the American Society of Limnology and Oceanugraphy, Inc.

Geospatial Analysis of Climate-Related Changes in North American Arctic Ecosystems and Implications for Terrestrial Flora and Fauna

NASA Astrophysics Data System (ADS)

Amirazodi, S.; Griffin, R.

2016-12-01

Climate change induces range shifts among many terrestrial species in Arctic regions. At best, warming often forces poleward migration if a stable environment is to be maintained. At worst, marginal ecosystems may disappear entirely without a contiguous shift allowing migratory escape to similar environs. These changing migration patterns and poleward range expansion push species into higher latitudes where ecosystems are less stable and more sensitive to change. This project focuses on ecosystem geography and interspecies relationships and interactions by analyzing seasonality and changes over time in variables including the following: temperature, precipitation, vegetation, physical boundaries, population demographics, permafrost, sea ice, and food and water availability. Publicly available data from remote sensing platforms are used throughout, and processed with both commercially available and open sourced GIS tools. This analysis describes observed range changes for selected North American species, and attempts to provide insight into the causes and effects of these phenomena. As the responses to climate change are complex and varied, the goal is to produce the aforementioned results in an easily understood set of geospatial representations to better support decision making regarding conservation prioritization and enable adaptive responses and mitigation strategies.

Paleogeographic Control on Climate Sensitivity of the Cretaceous-Palaeogene-Eocene.

NASA Astrophysics Data System (ADS)

Farnsworth, A.; Lunt, D. J.; Robinson, S.; O'Brien, C. L.; Pancost, R.

2016-12-01

Just how sensitive are warm climates of the past (Cretaceous-Eocene-Palaeogene (CPE)) to atmospheric carbon dioxide (pCO2) concentrations. We present an ensemble [1] of 21 climate model simulations spanning the CPE at both 560ppm and 1120ppm using state of the art paleogeographies (GETECH Plc. [1]), to ascertain how sensitive warm climates of the past are to pCO2. We find depending on the time period in the CPE, a doubling of pCO2results in a 2-3°C increase in SST and a 3-5°C increase in surface air temperature. We analyse the reasons behind the varying climate sensitivity, and the geographical distribution of warming, including some of the periods with regions of cooling (figure 1) and how this may help inform future climate change. Further to this we construct a model derived CO2 curve through the CPE based on avaliable proxy-data. Figure 1 - Mean surface annual surface temperature (°C) anomaly (4 x Pre-Industrial pCO2 (1120ppm) minus 2 x Pre-Industrial pCO2(560ppm)) in the Ypresian ( 52 Myr). [1] Lunt, D. J., Farnsworth, A., Loptson, C., Foster, G. L., Markwick, P., O'Brien, C. L., Pancost, R. D., Robinson, S. A., and Wrobel, N.: Palaeogeographic controls on climate and proxy interpretation, Clim. Past Discuss., 11, 5683-5725, doi:10.5194/cpd-11-5683-2015, 2015.

High regional climate sensitivity over continental China constrained by glacial-recent changes in temperature and the hydrological cycle.

PubMed

Eagle, Robert A; Risi, Camille; Mitchell, Jonathan L; Eiler, John M; Seibt, Ulrike; Neelin, J David; Li, Gaojun; Tripati, Aradhna K

2013-05-28

The East Asian monsoon is one of Earth's most significant climatic phenomena, and numerous paleoclimate archives have revealed that it exhibits variations on orbital and suborbital time scales. Quantitative constraints on the climate changes associated with these past variations are limited, yet are needed to constrain sensitivity of the region to changes in greenhouse gas levels. Here, we show central China is a region that experienced a much larger temperature change since the Last Glacial Maximum than typically simulated by climate models. We applied clumped isotope thermometry to carbonates from the central Chinese Loess Plateau to reconstruct temperature and water isotope shifts from the Last Glacial Maximum to present. We find a summertime temperature change of 6-7 °C that is reproduced by climate model simulations presented here. Proxy data reveal evidence for a shift to lighter isotopic composition of meteoric waters in glacial times, which is also captured by our model. Analysis of model outputs suggests that glacial cooling over continental China is significantly amplified by the influence of stationary waves, which, in turn, are enhanced by continental ice sheets. These results not only support high regional climate sensitivity in Central China but highlight the fundamental role of planetary-scale atmospheric dynamics in the sensitivity of regional climates to continental glaciation, changing greenhouse gas levels, and insolation.

Projections of water stress based on an ensemble of socioeconomic growth and climate change scenarios: A case study in Asia

DOE PAGES

Fant, Charles; Schlosser, C. Adam; Gao, Xiang; ...

2016-03-30

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify themore » primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Lastly, tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.« less

Evaluation of probable maximum snow accumulation: Development of a methodology for climate change studies

NASA Astrophysics Data System (ADS)

Klein, Iris M.; Rousseau, Alain N.; Frigon, Anne; Freudiger, Daphné; Gagnon, Patrick

2016-06-01

Probable maximum snow accumulation (PMSA) is one of the key variables used to estimate the spring probable maximum flood (PMF). A robust methodology for evaluating the PMSA is imperative so the ensuing spring PMF is a reasonable estimation. This is of particular importance in times of climate change (CC) since it is known that solid precipitation in Nordic landscapes will in all likelihood change over the next century. In this paper, a PMSA methodology based on simulated data from regional climate models is developed. Moisture maximization represents the core concept of the proposed methodology; precipitable water being the key variable. Results of stationarity tests indicate that CC will affect the monthly maximum precipitable water and, thus, the ensuing ratio to maximize important snowfall events. Therefore, a non-stationary approach is used to describe the monthly maximum precipitable water. Outputs from three simulations produced by the Canadian Regional Climate Model were used to give first estimates of potential PMSA changes for southern Quebec, Canada. A sensitivity analysis of the computed PMSA was performed with respect to the number of time-steps used (so-called snowstorm duration) and the threshold for a snowstorm to be maximized or not. The developed methodology is robust and a powerful tool to estimate the relative change of the PMSA. Absolute results are in the same order of magnitude as those obtained with the traditional method and observed data; but are also found to depend strongly on the climate projection used and show spatial variability.

How sensitive are temperate tadpoles to climate change? The use of thermal physiology and niche model tools to assess vulnerability.

PubMed

Perotti, María Gabriela; Bonino, Marcelo Fabián; Ferraro, Daiana; Cruz, Félix Benjamín

2018-04-01

Ectotherms are vulnerable to climate change, given their dependence on temperature, and amphibians are particularly interesting because of their complex life cycle. Tadpoles may regulate their body temperature by using suitable thermal microhabitats. Thus, their physiological responses are the result of adjustment to the local thermal limits experienced in their ponds. We studied three anuran tadpole species present in Argentina and Chile: Pleurodema thaul and Pleurodema bufoninum that are seasonal and have broad geographic ranges, and Batrachyla taeniata, a geographically restricted species with overwintering tadpoles. Species with restricted distribution are more susceptible to climate change than species with broader distribution that may cope with potential climatic changes in the environments in which they occur. We aim to test whether these species can buffer the potential effects of climate warming. We used ecological niche models and the outcomes of their thermal attributes (critical thermal limits, optimal temperature, and locomotor performance breadth) as empirical evidence of their capacity. We found that Pleurodema species show broader performance curves, related to their occurrence, while the geographically restricted B. taeniata shows a narrower thermal breadth, but is faster in warmer conditions. The modeled distributions and empirical physiological results suggest no severe threats for these three anurans. However, the risk level is increasing and a retraction of their distribution range might be possible for Pleurodema species, and some local population extinctions may happen, particularly for the narrowly distributed B. taeniata. Copyright © 2018 Elsevier GmbH. All rights reserved.

Thermoregulation of two sympatric species of horned lizards in the Chihuahuan Desert and their local extinction risk.

PubMed

Lara-Reséndiz, Rafael A; Gadsden, Héctor; Rosen, Philip C; Sinervo, Barry; Méndez-De la Cruz, Fausto R

2015-02-01

Thermoregulatory studies of ectothermic organisms are an important tool for ecological physiology, evolutionary ecology and behavior, and recently have become central for evaluating and predicting global climate change impacts. Here, we present a novel combination of field, laboratory, and modeling approaches to examine body temperature regulation, habitat thermal quality, and hours of thermal restriction on the activity of two sympatric, aridlands horned lizards (Phrynosoma cornutum and Phrynosoma modestum) at three contrasting Chihuahuan Desert sites in Mexico. Using these physiological data, we estimate local extinction risk under predicted climate change within their current geographical distribution. We followed the Hertz et al. (1993, Am. Nat., 142, 796-818) protocol for evaluating thermoregulation and the Sinervo et al. (2010, Science, 328, 894-899) eco-physiological model of extinction under climatic warming. Thermoregulatory indices suggest that both species thermoregulate effectively despite living in habitats of low thermal quality, although high environmental temperatures restrict the activity period of both species. Based on our measurements, if air temperature rises as predicted by climate models, the extinction model projects that P. cornutum will become locally extinct at 6% of sites by 2050 and 18% by 2080 and P. modestum will become extinct at 32% of sites by 2050 and 60% by 2080. The method we apply, using widely available or readily acquired thermal data, along with the modeling, appeared to identify several unique ecological traits that seemingly exacerbate climate sensitivity of P. modestum. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparison of the sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern, climate and weather.

Treesearch

Geoffrey J. Cary; Robert E. Keane; Robert H. Gardner; Sandra Lavorel; Mike D. Flannigan; Ian D. Davies; Chao Li; James M. Lenihan; T. Scott Rupp; Florent Mouillot

2006-01-01

The purpose of this study was to compare the sensitivity of nlodelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer &...

Comparison of the sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern, climate and weather

Treesearch

Geoffrey J. Cary; Robert E. Keane; Robert H. Gardner; Sandra Lavorel; Michael D. Flannigan; Ian D. Davies; Chao Li; James M. Lenihan; T. Scott Rupp; Florent Mouillot

2006-01-01

The purpose of this study was to compare the sensitivity of modelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer &...

Hydrological projections of climate change scenarios over the 3H region of China: A VIC model assessment

NASA Astrophysics Data System (ADS)

Dan, Li; Ji, Jinjun; Xie, Zhenghui; Chen, Feng; Wen, Gang; Richey, Jeffrey E.

2012-06-01

To examine the potential sensitivity of the Huang-Huai-Hai Plain (3H) region of China to potential changes in future precipitation and temperature, a hydrological evaluation using the VIC hydrological model under different climate scenarios was carried out. The broader perspective is providing a scientific background for the adaptation in water resource management and rural development to climate change. Twelve climate scenarios were designed to account for possible variations in the future with respect to the baseline of historic climate patterns. Results from the six representative types of climate scenarios (+2°C and +5°C warming, and 0%, +15%, -15% change in precipitation) show that rising temperatures for normal precipitation and for wet scenarios (+15% precipitation) yield greater increased evapotranspiration in the south than in the north, which is confirmed by the remaining six scenarios described below. For a 15% change in precipitation, the largest increase or decrease of evapotranspiration occurs between 33 and 36°N and west of 118°E, a region where evapotranspiration is sensitive to precipitation variation and is affected by the amount of water available for evaporation. Rising temperatures can lead to a south-to-north decreasing gradient of surface runoff. The six scenarios yield a large variation of runoff in the southern end of the 3H, which means that this zone is sensitive to climate change through surface runoff change. The Jiangsu province in the southeastern part of the 3H region shows an obvious sensitivity in soil moisture to climate change. On a regional mean scale, the hydrological change induced by the increasing precipitation from 15% to 30% is more obvious than that induced by greater warming of +5°C relative to +2°C. These simulations identify key regions of sensitivity in hydrological variation to climate change in the provinces of 3H, which can be used as guides in implementing adaptation.

A Hybrid Evaluation System Framework (Shell & Web) with Standardized Access to Climate Model Data and Verification Tools for a Clear Climate Science Infrastructure on Big Data High Performance Computers

NASA Astrophysics Data System (ADS)

Kadow, C.; Illing, S.; Kunst, O.; Cubasch, U.

2014-12-01

The project 'Integrated Data and Evaluation System for Decadal Scale Prediction' (INTEGRATION) as part of the German decadal prediction project MiKlip develops a central evaluation system. The fully operational hybrid features a HPC shell access and an user friendly web-interface. It employs one common system with a variety of verification tools and validation data from different projects in- and outside of MiKlip. The evaluation system is located at the German Climate Computing Centre (DKRZ) and has direct access to the bulk of its ESGF node including millions of climate model data sets, e.g. from CMIP5 and CORDEX. The database is organized by the international CMOR standard using the meta information of the self-describing model, reanalysis and observational data sets. Apache Solr is used for indexing the different data projects into one common search environment. This implemented meta data system with its advanced but easy to handle search tool supports users, developers and their tools to retrieve the required information. A generic application programming interface (API) allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language used. Users of the evaluation techniques benefit from the common interface of the evaluation system without any need to understand the different scripting languages. Facilitating the provision and usage of tools and climate data increases automatically the number of scientists working with the data sets and identify discrepancies. Additionally, the history and configuration sub-system stores every analysis performed with the evaluation system in a MySQL database. Configurations and results of the tools can be shared among scientists via shell or web-system. Therefore, plugged-in tools gain automatically from transparency and reproducibility. Furthermore, when configurations match while starting a evaluation tool, the system suggests to use results already produced by other users-saving CPU time, I/O and disk space. This study presents the different techniques and advantages of such a hybrid evaluation system making use of a Big Data HPC in climate science. website: www-miklip.dkrz.de visitor-login: guest password: miklip

A Hybrid Evaluation System Framework (Shell & Web) with Standardized Access to Climate Model Data and Verification Tools for a Clear Climate Science Infrastructure on Big Data High Performance Computers

NASA Astrophysics Data System (ADS)

Kadow, Christopher; Illing, Sebastian; Kunst, Oliver; Ulbrich, Uwe; Cubasch, Ulrich

2015-04-01

The project 'Integrated Data and Evaluation System for Decadal Scale Prediction' (INTEGRATION) as part of the German decadal prediction project MiKlip develops a central evaluation system. The fully operational hybrid features a HPC shell access and an user friendly web-interface. It employs one common system with a variety of verification tools and validation data from different projects in- and outside of MiKlip. The evaluation system is located at the German Climate Computing Centre (DKRZ) and has direct access to the bulk of its ESGF node including millions of climate model data sets, e.g. from CMIP5 and CORDEX. The database is organized by the international CMOR standard using the meta information of the self-describing model, reanalysis and observational data sets. Apache Solr is used for indexing the different data projects into one common search environment. This implemented meta data system with its advanced but easy to handle search tool supports users, developers and their tools to retrieve the required information. A generic application programming interface (API) allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language used. Users of the evaluation techniques benefit from the common interface of the evaluation system without any need to understand the different scripting languages. Facilitating the provision and usage of tools and climate data increases automatically the number of scientists working with the data sets and identify discrepancies. Additionally, the history and configuration sub-system stores every analysis performed with the evaluation system in a MySQL database. Configurations and results of the tools can be shared among scientists via shell or web-system. Therefore, plugged-in tools gain automatically from transparency and reproducibility. Furthermore, when configurations match while starting a evaluation tool, the system suggests to use results already produced by other users-saving CPU time, I/O and disk space. This study presents the different techniques and advantages of such a hybrid evaluation system making use of a Big Data HPC in climate science. website: www-miklip.dkrz.de visitor-login: click on "Guest"

Range position and climate sensitivity: The structure of among-population demographic responses to climatic variation

USGS Publications Warehouse

Amburgey, Staci M.; Miller, David A. W.; Grant, Evan H. Campbell; Rittenhouse, Tracy A. G.; Benard, Michael F.; Richardson, Jonathan L.; Urban, Mark C.; Hughson, Ward; Brand, Adrianne B,; Davis, Christopher J.; Hardin, Carmen R.; Paton, Peter W. C.; Raithel, Christopher J.; Relyea, Rick A.; Scott, A. Floyd; Skelly, David K.; Skidds, Dennis E.; Smith, Charles K.; Werner, Earl E.

2018-01-01

Species’ distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species’ climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs (Lithobates sylvaticus) in North America. Using long-term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long-term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species’ climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species-interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the need to measure demographic responses to changing climate.

A Geographic Mosaic of Climate Change Impacts on Terrestrial Vegetation: Which Areas Are Most at Risk?

PubMed Central

Ackerly, David D.; Cornwell, William K.; Weiss, Stuart B.; Flint, Lorraine E.; Flint, Alan L.

2015-01-01

Changes in climate projected for the 21st century are expected to trigger widespread and pervasive biotic impacts. Forecasting these changes and their implications for ecosystem services is a major research goal. Much of the research on biotic responses to climate change has focused on either projected shifts in individual species distributions or broad-scale changes in biome distributions. Here, we introduce a novel application of multinomial logistic regression as a powerful approach to model vegetation distributions and potential responses to 21st century climate change. We modeled the distribution of 22 major vegetation types, most defined by a single dominant woody species, across the San Francisco Bay Area. Predictor variables included climate and topographic variables. The novel aspect of our model is the output: a vector of relative probabilities for each vegetation type in each location within the study domain. The model was then projected for 54 future climate scenarios, spanning a representative range of temperature and precipitation projections from the CMIP3 and CMIP5 ensembles. We found that sensitivity of vegetation to climate change is highly heterogeneous across the region. Surprisingly, sensitivity to climate change is higher closer to the coast, on lower insolation, north-facing slopes and in areas of higher precipitation. While such sites may provide refugia for mesic and cool-adapted vegetation in the face of a warming climate, the model suggests they will still be highly dynamic and relatively sensitive to climate-driven vegetation transitions. The greater sensitivity of moist and low insolation sites is an unexpected outcome that challenges views on the location and stability of climate refugia. Projections provide a foundation for conservation planning and land management, and highlight the need for a greater understanding of the mechanisms and time scales of potential climate-driven vegetation transitions. PMID:26115485

Large-Scale Features of Pliocene Climate: Results from the Pliocene Model Intercomparison Project

NASA Technical Reports Server (NTRS)

Haywood, A. M.; Hill, D.J.; Dolan, A. M.; Otto-Bliesner, B. L.; Bragg, F.; Chan, W.-L.; Chandler, M. A.; Contoux, C.; Dowsett, H. J.; Jost, A.;

Vegetation sensitivity to global anthropogenic carbon dioxide emissions in a topographically complex region

USGS Publications Warehouse

Diffenbaugh, N.S.; Sloan, L.C.; Snyder, M.A.; Bell, J.L.; Kaplan, J.; Shafer, S.L.; Bartlein, P.J.

2003-01-01

Anthropogenic increases in atmospheric carbon dioxide (CO2) concentrations may affect vegetation distribution both directly through changes in photosynthesis and water-use efficiency, and indirectly through CO2-induced climate change. Using an equilibrium vegetation model (BIOME4) driven by a regional climate model (RegCM2.5), we tested the sensitivity of vegetation in the western United States, a topographically complex region, to the direct, indirect, and combined effects of doubled preindustrial atmospheric CO2 concentrations. Those sensitivities were quantified using the kappa statistic. Simulated vegetation in the western United States was sensitive to changes in atmospheric CO2 concentrations, with woody biome types replacing less woody types throughout the domain. The simulated vegetation was also sensitive to climatic effects, particularly at high elevations, due to both warming throughout the domain and decreased precipitation in key mountain regions such as the Sierra Nevada of California and the Cascade and Blue Mountains of Oregon. Significantly, when the direct effects of CO2 on vegetation were tested in combination with the indirect effects of CO2-induced climate change, new vegetation patterns were created that were not seen in either of the individual cases. This result indicates that climatic and nonclimatic effects must be considered in tandem when assessing the potential impacts of elevated CO2 levels.

A tool to assess potential for alien plant establishment and expansion under climate change.

PubMed

Roger, Erin; Duursma, Daisy Englert; Downey, Paul O; Gallagher, Rachael V; Hughes, Lesley; Steel, Jackie; Johnson, Stephen B; Leishman, Michelle R

2015-08-15

Predicting the influence of climate change on the potential distribution of naturalised alien plant species is an important and challenging task. While prioritisation of management actions for alien plants under current climatic conditions has been widely adopted, very few systems explicitly incorporate the potential of future changes in climate conditions to influence the distribution of alien plant species. Here, we develop an Australia-wide screening tool to assess the potential of naturalised alien plants to establish and spread under both current and future climatic conditions. The screening tool developed uses five spatially explicit criteria to establish the likelihood of alien plant population establishment and expansion under baseline climate conditions and future climates for the decades 2035 and 2065. Alien plants are then given a threat rating according to current and future threat to enable natural resource managers to focus on those species that pose the largest potential threat now and in the future. To demonstrate the screening tool, we present results for a representative sample of approximately 10% (n = 292) of Australia's known, naturalised alien plant species. Overall, most alien plant species showed decreases in area of habitat suitability under future conditions compared to current conditions and therefore the threat rating of most alien plant species declined between current and future conditions. Use of the screening tool is intended to assist natural resource managers in assessing the threat of alien plant establishment and spread under current and future conditions and thus prioritise detailed weed risk assessments for those species that pose the greatest threat. The screening tool is associated with a searchable database for all 292 alien plant species across a range of spatial scales, available through an interactive web-based portal at http://weedfutures.net/. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Association between organizational climate and perceptions and use of an innovation in Swedish primary health care: a prospective study of an implementation.

PubMed

Carlfjord, Siw; Festin, Karin

2015-09-10

There is a need for new knowledge regarding determinants of a successful implementation of new methods in health care. The role of a receptive context for change to support effective diffusion has been underlined, and could be studied by assessing the organizational climate. The aim of this study was to assess the association between organizational climate when a computer-based lifestyle intervention tool (CLT) was introduced in primary health care (PHC) and the implementation outcome in terms of how the tool was perceived and used after 2 years. The CLT was offered to 32 PHC units in Sweden, of which 22 units agreed to participate in the study. Before the introduction of the CLT, the creative climate at each participating unit was assessed. After 24 months, a follow-up questionnaire was distributed to the staff to assess how the CLT was perceived and how it was used. A question on the perceived need for the CLT was also included. The units were divided into three groups according to the creative climate: high, medium and low. The main finding was that the units identified as having a positive creative climate demonstrated more frequent use and more positive perceptions regarding the new tool than those with the least positive creative climate. More positive perceptions were seen at both individual and unit levels. According to the results from this study there is an association between organizational climate at baseline and implementation outcome after 2 years when a tool for lifestyle intervention is introduced in PHC in Sweden. Further studies are needed before measurement of organizational climate at baseline can be recommended in order to predict implementation outcome.

Climate Adaptation is About More Than Climate: Value-Driven Science Delivery

NASA Astrophysics Data System (ADS)

Swanston, C.

2015-12-01

Efforts to deliver relevant scientific information and tools to diverse stakeholders have dramatically increased in recent years with the intention of promoting climate change adaptation. Much work has been done to understand the barriers to action, but these largely overlook the need to frame the discussion in terms of stakeholder values and co-create innovative solutions that meet their individual needs. A partnership-based effort in the upper Midwest and Northeast called the Climate Change Response Framework (CCRF; www.forestadaptation.org) ensures relevance, breadth, and credibility of its products through stakeholder inclusion at all levels. The fundamental role of the CCRF is to help people meet their land stewardship goals while minimizing climate risk. This represents a subtle but important shift in focus to people and their values, as opposed to climate change and its effects. The CCRF uses a climate planning tool, the Adaptation Workbook (www.adaptationworkbook.org), along with ecosystem vulnerability assessments and a diverse "menu" of adaptation approaches to generate site-specific adaptation actions that meet explicit conservation objectives. These tools are integrated into an Adaptation Planning and Practices workshop that leads organizations through this structured process of designing adaptation tactics for their projects and plans. All of these tools were developed with stakeholders, or in response to their direct and continuing feedback. The CCRF has involved thousands of people and over 100 organizations, published six ecoregional vulnerability assessments with more than 130 authors, and generated more than 125 intentional adaptation demonstrations in real-world land management projects on federal, state, tribal, county, conservancy, and private lands. The CCRF contributes strongly to the USDA Regional Climate Hubs, working on the applied end of the continuum of climate services occupied by providers such as the CSCs, LCCs, RISAs, and RCCs.

ClimatePipes: User-Friendly Data Access, Manipulation, Analysis & Visualization of Community Climate Models

NASA Astrophysics Data System (ADS)

Chaudhary, A.; DeMarle, D.; Burnett, B.; Harris, C.; Silva, W.; Osmari, D.; Geveci, B.; Silva, C.; Doutriaux, C.; Williams, D. N.

2013-12-01

The impact of climate change will resonate through a broad range of fields including public health, infrastructure, water resources, and many others. Long-term coordinated planning, funding, and action are required for climate change adaptation and mitigation. Unfortunately, widespread use of climate data (simulated and observed) in non-climate science communities is impeded by factors such as large data size, lack of adequate metadata, poor documentation, and lack of sufficient computational and visualization resources. We present ClimatePipes to address many of these challenges by creating an open source platform that provides state-of-the-art, user-friendly data access, analysis, and visualization for climate and other relevant geospatial datasets, making the climate data available to non-researchers, decision-makers, and other stakeholders. The overarching goals of ClimatePipes are: - Enable users to explore real-world questions related to climate change. - Provide tools for data access, analysis, and visualization. - Facilitate collaboration by enabling users to share datasets, workflows, and visualization. ClimatePipes uses a web-based application platform for its widespread support on mainstream operating systems, ease-of-use, and inherent collaboration support. The front-end of ClimatePipes uses HTML5 (WebGL, Canvas2D, CSS3) to deliver state-of-the-art visualization and to provide a best-in-class user experience. The back-end of the ClimatePipes is built around Python using the Visualization Toolkit (VTK, http://vtk.org), Climate Data Analysis Tools (CDAT, http://uv-cdat.llnl.gov), and other climate and geospatial data processing tools such as GDAL and PROJ4. ClimatePipes web-interface to query and access data from remote sources (such as ESGF). Shown in the figure is climate data layer from ESGF on top of map data layer from OpenStreetMap. The ClimatePipes workflow editor provides flexibility and fine grained control, and uses the VisTrails (http://www.vistrails.org) workflow engine in the backend.

Climate change risk analysis framework (CCRAF) a probabilistic tool for analyzing climate change uncertainties

NASA Astrophysics Data System (ADS)

Legget, J.; Pepper, W.; Sankovski, A.; Smith, J.; Tol, R.; Wigley, T.

2003-04-01

Potential risks of human-induced climate change are subject to a three-fold uncertainty associated with: the extent of future anthropogenic and natural GHG emissions; global and regional climatic responses to emissions; and impacts of climatic changes on economies and the biosphere. Long-term analyses are also subject to uncertainty regarding how humans will respond to actual or perceived changes, through adaptation or mitigation efforts. Explicitly addressing these uncertainties is a high priority in the scientific and policy communities Probabilistic modeling is gaining momentum as a technique to quantify uncertainties explicitly and use decision analysis techniques that take advantage of improved risk information. The Climate Change Risk Assessment Framework (CCRAF) presented here a new integrative tool that combines the probabilistic approaches developed in population, energy and economic sciences with empirical data and probabilistic results of climate and impact models. The main CCRAF objective is to assess global climate change as a risk management challenge and to provide insights regarding robust policies that address the risks, by mitigating greenhouse gas emissions and by adapting to climate change consequences. The CCRAF endogenously simulates to 2100 or beyond annual region-specific changes in population; GDP; primary (by fuel) and final energy (by type) use; a wide set of associated GHG emissions; GHG concentrations; global temperature change and sea level rise; economic, health, and biospheric impacts; costs of mitigation and adaptation measures and residual costs or benefits of climate change. Atmospheric and climate components of CCRAF are formulated based on the latest version of Wigley's and Raper's MAGICC model and impacts are simulated based on a modified version of Tol's FUND model. The CCRAF is based on series of log-linear equations with deterministic and random components and is implemented using a Monte-Carlo method with up to 5000 variants per set of fixed input parameters. The shape and coefficients of CCRAF equations are derived from regression analyses of historic data and expert assessments. There are two types of random components in CCRAF - one reflects a year-to-year fluctuations around the expected value of a given variable (e.g., standard error of the annual GDP growth) and another is fixed within each CCRAF variant and represents some essential constants within a "world" represented by that variant (e.g., the value of climate sensitivity). Both types of random components are drawn from pre-defined probability distributions functions developed based on historic data or expert assessments. Preliminary CCRAF results emphasize the relative importance of uncertainties associated with the conversion of GHG and particulate emissions into radiative forcing and quantifying climate change effects at the regional level. A separates analysis involves an "adaptive decision-making", which optimizes the expected future policy effects given the estimated probabilistic uncertainties. As uncertainty for some variables evolve over the time steps, the decisions also adapt. This modeling approach is feasible only with explicit modeling of uncertainties.

A review of climate-change adaptation strategies for wildlife management and biodiversity conservation.

PubMed

Mawdsley, Jonathan R; O'Malley, Robin; Ojima, Dennis S

2009-10-01

The scientific literature contains numerous descriptions of observed and potential effects of global climate change on species and ecosystems. In response to anticipated effects of climate change, conservation organizations and government agencies are developing "adaptation strategies" to facilitate the adjustment of human society and ecological systems to altered climate regimes. We reviewed the literature and climate-change adaptation plans that have been developed in United States, Canada, England, México, and South Africa and found 16 general adaptation strategies that relate directly to the conservation of biological diversity. These strategies can be grouped into four broad categories: land and water protection and management; direct species management; monitoring and planning; and law and policy. Tools for implementing these strategies are similar or identical to those already in use by conservationists worldwide (land and water conservation, ecological restoration, agrienvironment schemes, species translocation, captive propagation, monitoring, natural resource planning, and legislation/regulation). Although our review indicates natural resource managers already have many tools that can be used to address climate-change effects, managers will likely need to apply these tools in novel and innovative ways to meet the unprecedented challenges posed by climate change.

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.

Disentangling Aerosol Cooling and Greenhouse Warming to Reveal Earth's Climate Sensitivity

NASA Astrophysics Data System (ADS)

Storelvmo, Trude; Leirvik, Thomas; Phillips, Petter; Lohmann, Ulrike; Wild, Martin

2015-04-01

Earth's climate sensitivity has been the subject of heated debate for decades, and recently spurred renewed interest after the latest IPCC assessment report suggested a downward adjustment of the most likely range of climate sensitivities. Here, we present a study based on the time period 1964 to 2010, which is unique in that it does not rely on global climate models (GCMs) in any way. The study uses surface observations of temperature and incoming solar radiation from approximately 1300 surface sites, along with observations of the equivalent CO2 concentration (CO2,eq) in the atmosphere, to produce a new best estimate for the transient climate sensitivity of 1.9K (95% confidence interval 1.2K - 2.7K). This is higher than other recent observation-based estimates, and is better aligned with the estimate of 1.8K and range (1.1K - 2.5K) derived from the latest generation of GCMs. The new estimate is produced by incorporating the observations in an energy balance framework, and by applying statistical methods that are standard in the field of Econometrics, but less common in climate studies. The study further suggests that about a third of the continental warming due to increasing CO2,eq was masked by aerosol cooling during the time period studied.

Disentangling Greenhouse Warming and Aerosol Cooling to Reveal Earth's Transient Climate Sensitivity

NASA Astrophysics Data System (ADS)

Storelvmo, T.

2015-12-01

Earth's climate sensitivity has been the subject of heated debate for decades, and recently spurred renewed interest after the latest IPCC assessment report suggested a downward adjustment of the most likely range of climate sensitivities. Here, we present an observation-based study based on the time period 1964 to 2010, which is unique in that it does not rely on global climate models (GCMs) in any way. The study uses surface observations of temperature and incoming solar radiation from approximately 1300 surface sites, along with observations of the equivalent CO2 concentration (CO2,eq) in the atmosphere, to produce a new best estimate for the transient climate sensitivity of 1.9K (95% confidence interval 1.2K - 2.7K). This is higher than other recent observation-based estimates, and is better aligned with the estimate of 1.8K and range (1.1K - 2.5K) derived from the latest generation of GCMs. The new estimate is produced by incorporating the observations in an energy balance framework, and by applying statistical methods that are standard in the field of Econometrics, but less common in climate studies. The study further suggests that about a third of the continental warming due to increasing CO2,eq was masked by aerosol cooling during the time period studied.

Empowering America's Communities to Prepare for the Effects of Climate Change: Developing Actionable Climate Science Under the President's Climate Action Plan

NASA Astrophysics Data System (ADS)

Duffy, P. B.; Colohan, P.; Driggers, R.; Herring, D.; Laurier, F.; Petes, L.; Ruffo, S.; Tilmes, C.; Venkataraman, B.; Weaver, C. P.

2014-12-01

Effective adaptation to impacts of climate change requires best-available information. To be most useful, this information should be easily found, well-documented, and translated into tools that decision-makers use and trust. To meet these needs, the President's Climate Action Plan includes efforts to develop "actionable climate science". The Climate Data Initiative (CDI) leverages the Federal Government's extensive, open data resources to stimulate innovation and private-sector entrepreneurship in support of actions to prepare for climate change. The Initiative forges commitments and partnerships from the private, NGO, academic, and public sectors to create data-driven tools. Open data from Federal agencies to support this innovation is available on Climate.Data.gov, initially focusing on coastal flooding but soon to expand to topics including food, energy, water, energy, transportation, and health. The Climate Resilience Toolkit (CRT) will facilitate access to data-driven resilience tools, services, and best practices, including those accessible through the CDI. The CRT will also include access to training and tutorials, case studies, engagement forums, and other information sources. The Climate Action Plan also calls for a public-private partnership on extreme weather risk, with the goal of generating improved assessments of risk from different types of extreme weather events, using methods and data that are transparent and accessible. Finally, the U.S. Global Change Research Program and associated agencies work to advance the science necessary to inform decisions and sustain assessments. Collectively, these efforts represent increased emphasis across the Federal Government on the importance of information to support climate resilience.

Complex interactions between climate change and toxicants: evidence that temperature variability increases sensitivity to cadmium.

PubMed

Kimberly, David A; Salice, Christopher J

2014-07-01

The Intergovernmental Panel on Climate Change projects that global climate change will have significant impacts on environmental conditions including potential effects on sensitivity of organisms to environmental contaminants. The objective of this study was to test the climate-induced toxicant sensitivity (CITS) hypothesis in which acclimation to altered climate parameters increases toxicant sensitivity. Adult Physa pomilia snails were acclimated to a near optimal 22 °C or a high-normal 28 °C for 28 days. After 28 days, snails from each temperature group were challenged with either low (150 μg/L) or high (300 μg/L) cadmium at each temperature (28 or 22 °C). In contrast to the CITS hypothesis, we found that acclimation temperature did not have a strong influence on cadmium sensitivity except at the high cadmium test concentration where snails acclimated to 28 °C were more cadmium tolerant. However, snails that experienced a switch in temperature for the cadmium challenge, regardless of the switch direction, were the most sensitive to cadmium. Within the snails that were switched between temperatures, snails acclimated at 28 °C and then exposed to high cadmium at 22 °C exhibited significantly greater mortality than those snails acclimated to 22 °C and then exposed to cadmium at 28 °C. Our results point to the importance of temperature variability in increasing toxicant sensitivity but also suggest a potentially complex cost of temperature acclimation. Broadly, the type of temporal stressor exposures we simulated may reduce overall plasticity in responses to stress ultimately rendering populations more vulnerable to adverse effects.

Exploring the potential of machine learning to break deadlock in convection parameterization

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Gentine, P.

2017-12-01

We explore the potential of modern machine learning tools (via TensorFlow) to replace parameterization of deep convection in climate models. Our strategy begins by generating a large ( 1 Tb) training dataset from time-step level (30-min) output harvested from a one-year integration of a zonally symmetric, uniform-SST aquaplanet integration of the SuperParameterized Community Atmosphere Model (SPCAM). We harvest the inputs and outputs connecting each of SPCAM's 8,192 embedded cloud-resolving model (CRM) arrays to its host climate model's arterial thermodynamic state variables to afford 143M independent training instances. We demonstrate that this dataset is sufficiently large to induce preliminary convergence for neural network prediction of desired outputs of SP, i.e. CRM-mean convective heating and moistening profiles. Sensitivity of the machine learning convergence to the nuances of the TensorFlow implementation are discussed, as well as results from pilot tests from the neural network operating inline within the SPCAM as a replacement to the (super)parameterization of convection.

GC31G-1182: Opennex, a Private-Public Partnership in Support of the National Climate Assessment

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna R.; Wang, Weile; Michaelis, Andrew; Votava, Petr; Ganguly, Sangram

2016-01-01

The NASA Earth Exchange (NEX) is a collaborative computing platform that has been developed with the objective of bringing scientists together with the software tools, massive global datasets, and supercomputing resources necessary to accelerate research in Earth systems science and global change. NEX is funded as an enabling tool for sustaining the national climate assessment. Over the past five years, researchers have used the NEX platform and produced a number of data sets highly relevant to the National Climate Assessment. These include high-resolution climate projections using different downscaling techniques and trends in historical climate from satellite data. To enable a broader community in exploiting the above datasets, the NEX team partnered with public cloud providers to create the OpenNEX platform. OpenNEX provides ready access to NEX data holdings on a number of public cloud platforms along with pertinent analysis tools and workflows in the form of Machine Images and Docker Containers, lectures and tutorials by experts. We will showcase some of the applications of OpenNEX data and tools by the community on Amazon Web Services, Google Cloud and the NEX Sandbox.

Tempest: Tools for Addressing the Needs of Next-Generation Climate Models

NASA Astrophysics Data System (ADS)

Ullrich, P. A.; Guerra, J. E.; Pinheiro, M. C.; Fong, J.

2015-12-01

Tempest is a comprehensive simulation-to-science infrastructure that tackles the needs of next-generation, high-resolution, data intensive climate modeling activities. This project incorporates three key components: TempestDynamics, a global modeling framework for experimental numerical methods and high-performance computing; TempestRemap, a toolset for arbitrary-order conservative and consistent remapping between unstructured grids; and TempestExtremes, a suite of detection and characterization tools for identifying weather extremes in large climate datasets. In this presentation, the latest advances with the implementation of this framework will be discussed, and a number of projects now utilizing these tools will be featured.

Introduction to Federal and EPA Climate Change Web Resources

EPA Science Inventory

Presentation provides an overview of four climate data and tool websites: the US Global Change Research Program (USGCRP) and Climate Resilience Toolkit (interagency websites); the main EPA climate change website; and the internal EPA Adaptation Resource Center website.

Transforming data into usable knowledge: the CIRC experience

NASA Astrophysics Data System (ADS)

Mote, P.; Lach, D.; Hartmann, H.; Abatzoglou, J. T.; Stevenson, J.

2017-12-01

NOAA's northwest RISA, the Climate Impacts Research Consortium, emphasizes the transformation of data into usable knowledge. This effort involves physical scientists (e.g., Abatzoglou) building web-based tools with climate and hydrologic data and model output, a team performing data mining to link crop loss claims to droughts, social scientists (eg., Lach, Hartmann) evaluating the effectiveness of such tools at communicating with end users, and two-way engagement with a wide variety of audiences who are interested in using and improving the tools. Unusual in this effort is the seamless integration across timescales past, present, and future; data mining; and the level of effort in evaluating the tools. We provide examples of agriculturally relevant climate variables (e.g. growing degree days, day of first fall freeze) and describe the iterative process of incorporating user feedback.

Determining spatially discretized surface flow and baseflow in the context of climate change and water quality management

NASA Astrophysics Data System (ADS)

Raimonet, M.; Oudin, L.; Rabouille, C.; Garnier, J.; Silvestre, M.; Vautard, R.; Thieu, V.

2016-12-01

Water quality management of fresh and marine aquatic systems requires modelling tools along the land-ocean continuum in order to evaluate the effect of climate change on nutrient transfer and on potential ecosystem dysfonctioning (e.g. eutrophication, anoxia). In addition to direct effects of climate change on water temperature, it is essential to consider indirect effects of precipitation and temperature changes on hydrology since nutrient transfers are particularly sensitive to the partition of streamflow between surface flow and baseflow. Yet, the determination of surface flow and baseflow, their spatial repartition on drainage basins, and their relative potential evolution under climate change remains challenging. In this study, we developed a generic approach to determine 10-day surface flow and baseflow using a regionalized hydrological model applied at a high spatial resolution (unitary catchments of area circa 10km²). Streamflow data at gauged basins were used to calibrate hydrological model parameters that were then applied on neighbor ungauged basins to estimate streamflow at the scale of the French territory. The proposed methodology allowed representing spatialized surface flow and baseflow that are consistent with climatic and geomorphological settings. The methodology was then used to determine the effect of climate change on the spatial repartition of surface flow and baseflow on the Seine drainage bassin. Results showed large discrepancies of both the amount and the spatial repartition of changes of surface flow and baseflow according to the several GCM and RCM used to derive projected climatic forcing. Consequently, it is expected that the impact of climate change on nutrient transfer might also be quite heterogeneous for the Seine River. This methodology could be applied in any drainage basin where at least several gauged hydrometric stations are available. The estimated surface flow and baseflow can then be used in hydro-ecological models in order to evaluate direct and indirect impacts of climate change on nutrient transfers and potential ecosystem dysfunctioning along the land-ocean continuum.

Advance strategy for climate change adaptation and mitigation in cities

NASA Astrophysics Data System (ADS)

Varquez, A. C. G.; Kanda, M.; Darmanto, N. S.; Sueishi, T.; Kawano, N.

2017-12-01

An on-going 5-yr project financially supported by the Ministry of Environment, Japan, has been carried out to specifically address the issue of prescribing appropriate adaptation and mitigation measures to climate change in cities. Entitled "Case Study on Mitigation and Local Adaptation to Climate Change in an Asian Megacity, Jakarta", the project's relevant objectives is to develop a research framework that can consider both urbanization and climate change with the main advantage of being readily implementable for all cities around the world. The test location is the benchmark city, Jakarta, Indonesia, with the end focus of evaluating the benefits of various mitigation and adaptation strategies in Jakarta and other megacities. The framework was designed to improve representation of urban areas when conducting climate change investigations in cities; and to be able to quantify separately the impacts of urbanization and climate change to all cities globally. It is comprised of a sophisticated, top-down, multi-downscaling approach utilizing a regional model (numerical weather model) and a microscale model (energy balance model and CFD model), with global circulation models (GCM) as input. The models, except the GCM, were configured to reasonably consider land cover, urban morphology, and anthropogenic heating (AH). Equally as important, methodologies that can collect and estimate global distribution of urban parametric and AH datasets are continually being developed. Urban growth models, climate scenario matrices that match representative concentration pathways with shared socio-economic pathways, present distribution of socio-demographic indicators such as population and GDP, existing GIS datasets of urban parameters, are utilized. From these tools, future urbanization (urban morphological parameters and AH) can be introduced into the models. Sensitivity using various combinations of GCM and urbanization can be conducted. Furthermore, since the models utilize parameters that can be readily modified to suit certain countermeasures, adaptation and mitigation strategies can be evaluated using thermal comfort and other social indicators. With the approaches introduced through this project, a deeper understanding of urban-climate interactions in the changing global climate can be achieved.

Parameter identification of the SWAT model on the BANI catchment (West Africa) under limited data condition

NASA Astrophysics Data System (ADS)

Chaibou Begou, Jamilatou; Jomaa, Seifeddine; Benabdallah, Sihem; Rode, Michael

2015-04-01

Due to the climate change, drier conditions have prevailed in West Africa, since the seventies, and the consequences are important on water resources. In order to identify and implement management strategies of adaptation to climate change in the sector of water, it is crucial to improve our physical understanding of water resources evolution in the region. To this end, hydrologic modelling is an appropriate tool for flow predictions under changing climate and land use conditions. In this study, the applicability and performance of the recent version of Soil and Water Assessment Tool (SWAT2012) model were tested on the Bani catchment in West Africa under limited data condition. Model parameters identification was also tested using one site and multisite calibration approaches. The Bani is located in the upper part of the Niger River and drains an area of about 101, 000 km2 at the outlet of Douna. The climate is tropical, humid to semi-arid from the South to the North with an average annual rainfall of 1050 mm (period 1981-2000). Global datasets were used for the model setup such as: USGS hydrosheds DEM, USGS LCI GlobCov2009 and the FAO Digital Soil Map of the World. Daily measured rainfall from nine rain gauges and maximum and minimum temperature from five weather stations covering the period 1981-1997 were used for model setup. Sensitivity analysis, calibration and validation are performed within SWATCUP using GLUE procedure at Douna station first (one site calibration), then at three additional internal stations, Bougouni, Pankourou and Kouoro1 (multi-site calibration). Model parameters were calibrated at daily time step for the period 1983-1992, then validated for the period 1993-1997. A period of two years (1981-1982) was used for model warming up. Results of one-site calibration showed that the model performance is evaluated by 0.76 and 0.79 for Nash-Sutcliffe (NS) and correlation coefficient (R2), respectively. While for the validation period the performance improved considerably with NS and R2 equal to 0.84 and 0.87, respectively. The degree of total uncertainties is quantified by a minimum P-factor of 0.61 and a maximum R-factor of 0.59. These statistics suggest that the model performance can be judged as very good, especially considering limited data condition and high climate, land use and soil variability in the studied basin. The most sensitive parameters (CN2, OVN and SLSUBBSN) are related to surface runoff reflecting the dominance of this process on the streamflow generation. In the next step, multisite calibration approach will be performed on the BANI basin to assess how much additional observations improve the model parameter identification.

Thermal affinity as the dominant factor changing Mediterranean fish abundances.

PubMed

Givan, Or; Edelist, Dor; Sonin, Oren; Belmaker, Jonathan

2018-01-01

Recent decades have seen profound changes in species abundance and community composition. In the marine environment, the major anthropogenic drivers of change comprise exploitation, invasion by nonindigenous species, and climate change. However, the magnitude of these stressors has been widely debated and we lack empirical estimates of their relative importance. In this study, we focused on Eastern Mediterranean, a region exposed to an invasion of species of Red Sea origin, extreme climate change, and high fishing pressure. We estimated changes in fish abundance using two fish trawl surveys spanning a 20-year period, and correlated these changes with estimated sensitivity of species to the different stressors. We estimated sensitivity to invasion using the trait similarity between indigenous and nonindigenous species; sensitivity to fishing using a published composite index based on the species' life-history; and sensitivity to climate change using species climatic affinity based on occurrence data. Using both a meta-analytical method and random forest analysis, we found that for shallow-water species the most important driver of population size changes is sensitivity to climate change. Species with an affinity to warm climates increased in relative abundance and species with an affinity to cold climates decreased suggesting a strong response to warming local sea temperatures over recent decades. This decrease in the abundance of cold-water-associated species at the trailing "warm" end of their distribution has been rarely documented. Despite the immense biomass of nonindigenous species and the presumed high fishing pressure, these two latter factors seem to have only a minor role in explaining abundance changes. The decline in abundance of indigenous species of cold-water origin indicates a future major restructuring of fish communities in the Mediterranean in response to the ongoing warming, with unknown impacts on ecosystem function. © 2017 John Wiley & Sons Ltd.

Heterogeneous Sensitivity of Tropical Precipitation Extremes during Growth and Mature Phases of Atmospheric Warming

NASA Astrophysics Data System (ADS)

Parhi, P.; Giannini, A.; Lall, U.; Gentine, P.

2016-12-01

Assessing and managing risks posed by climate variability and change is challenging in the tropics, from both a socio-economic and a scientific perspective. Most of the vulnerable countries with a limited climate adaptation capability are in the tropics. However, climate projections, particularly of extreme precipitation, are highly uncertain there. The CMIP5 (Coupled Model Inter- comparison Project - Phase 5) inter-model range of extreme precipitation sensitivity to the global temperature under climate change is much larger in the tropics as compared to the extra-tropics. It ranges from nearly 0% to greater than 30% across models (O'Gorman 2012). The uncertainty is also large in historical gauge or satellite based observational records. These large uncertainties in the sensitivity of tropical precipitation extremes highlight the need to better understand how tropical precipitation extremes respond to warming. We hypothesize that one of the factors explaining the large uncertainty is due to differing sensitivities during different phases of warming. We consider the `growth' and `mature' phases of warming under climate variability case- typically associated with an El Niño event. In the remote tropics (away from tropical Pacific Ocean), the response of the precipitation extremes during the two phases can be through different pathways: i) a direct and fast changing radiative forcing in an atmospheric column, acting top-down due to the tropospheric warming, and/or ii) an indirect effect via changes in surface temperatures, acting bottom-up through surface water and energy fluxes. We also speculate that the insights gained here might be useful in interpreting the large sensitivity under climate change scenarios, since the physical mechanisms during the two warming phases under climate variability case, have some correspondence with an increasing and stabilized green house gas emission scenarios.

Variability in soybean yield in Brazil stemming from the interaction of heterogeneous management and climate variability

NASA Astrophysics Data System (ADS)

Cohn, A.; Bragança, A.; Jeffries, G. R.

2017-12-01

An increasing share of global agricultural production can be found in the humid tropics. Therefore, an improved understanding of the mechanisms governing variability in the output of tropical agricultural systems is of increasing importance for food security including through climate change adaptation. Yet, the long window over which many tropical crops can be sown, the diversity of crop varieties and management practices combine to challenge inference into climate risk to cropping output in analyses of tropical crop-climate sensitivity employing administrative data. In this paper, we leverage a newly developed spatially explicit dataset of soybean yields in Brazil to combat this problem. The dataset was built by training a model of remotely-sensed vegetation index data and land cover classification data using a rich in situ dataset of soybean yield and management variables collected over the period 2006 to 2016. The dataset contains soybean yields by plant date, cropping frequency, and maturity group for each 5km grid cell in Brazil. We model variation in these yields using an approach enabling the estimation of the influence of management factors on the sensitivity of soybean yields to variability in: cumulative solar radiation, extreme degree days, growing degree days, flooding rain in the harvest period, and dry spells in the rainy season. We find strong variation in climate sensitivity by management class. Planting date and maturity group each explained a great deal more variation in yield sensitivity than did cropping frequency. Brazil collects comparatively fine spatial resolution yield data. But, our attempt to replicate our results using administrative soy yield data revealed substantially lesser crop-climate sensitivity; suggesting that previous analyses employing administrative data may have underestimated climate risk to tropical soy production.

Synchronous population dynamics in California butterflies explained by climatic forcing

PubMed Central

Shapiro, Arthur M.

2017-01-01

A long-standing challenge for population biology has been to understand why some species are characterized by populations that fluctuate in size independently, while populations of other species fluctuate synchronously across space. The effects of climatic variation and dispersal have been invoked to explain synchronous population dynamics, however an understanding of the relative influence of these drivers in natural populations is lacking. Here we compare support for dispersal- versus climate-driven models of interspecific variation in synchrony using 27 years of observations of 65 butterfly species at 10 sites spanning 2750 m of elevation in Northern California. The degree of spatial synchrony exhibited by each butterfly species was used as a response in a unique approach that allowed us to investigate whether interspecific variation in response to climate or dispersal propensity was most predictive of interspecific variation in synchrony. We report that variation in sensitivity to climate explained 50% of interspecific variation in synchrony, whereas variation in dispersal propensity explained 23%. Sensitivity to the El Niño Southern Oscillation, a primary driver of regional climate, was the best predictor of synchrony. Combining sensitivity to climate and dispersal propensity into a single model did not greatly increase model performance, confirming the primacy of climatic sensitivity for driving spatial synchrony in butterflies. Finally, we uncovered a relationship between spatial synchrony and population decline that is consistent with theory, but small in magnitude, which suggests that the degree to which populations fluctuate in synchrony is of limited use for understanding the ongoing decline of the Northern California butterfly fauna. PMID:28791146

Predicting potential global distributions of two Miscanthus grasses: implications for horticulture, biofuel production, and biological invasions.

PubMed

Hager, Heather A; Sinasac, Sarah E; Gedalof, Ze'ev; Newman, Jonathan A

2014-01-01

In many regions, large proportions of the naturalized and invasive non-native floras were originally introduced deliberately by humans. Pest risk assessments are now used in many jurisdictions to regulate the importation of species and usually include an estimation of the potential distribution in the import area. Two species of Asian grass (Miscanthus sacchariflorus and M. sinensis) that were originally introduced to North America as ornamental plants have since escaped cultivation. These species and their hybrid offspring are now receiving attention for large-scale production as biofuel crops in North America and elsewhere. We evaluated their potential global climate suitability for cultivation and potential invasion using the niche model CLIMEX and evaluated the models' sensitivity to the parameter values. We then compared the sensitivity of projections of future climatically suitable area under two climate models and two emissions scenarios. The models indicate that the species have been introduced to most of the potential global climatically suitable areas in the northern but not the southern hemisphere. The more narrowly distributed species (M. sacchariflorus) is more sensitive to changes in model parameters, which could have implications for modelling species of conservation concern. Climate projections indicate likely contractions in potential range in the south, but expansions in the north, particularly in introduced areas where biomass production trials are under way. Climate sensitivity analysis shows that projections differ more between the selected climate change models than between the selected emissions scenarios. Local-scale assessments are required to overlay suitable habitat with climate projections to estimate areas of cultivation potential and invasion risk.

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.

Metamodeling as a tool to size vegetative filter strips for surface runoff pollution control in European watersheds.

NASA Astrophysics Data System (ADS)

Lauvernet, Claire; Muñoz-Carpena, Rafael; Carluer, Nadia

2015-04-01

In Europe, a significant presence of contaminants is found in surface water, partly due to pesticide applications. Vegetative filter strips or buffer zones (VFS), often located along rivers, are a common best management practice (BMP) to reduce non point source pollution of water by reducing surface runoff. However, they need to be adapted to the agro-ecological and climatic conditions, both in terms of position and size, in order to be efficient. The TOPPS-PROWADIS project involves European experts and stakeholders to develop and recommend BMPs to reduce pesticide transfer by drift or runoff in several European countries. In this context, IRSTEA developed a guide accompanying the use of different tools, which allows designing site-specific VFS by simulating their efficiency to limit transfers using the mechanistic model VFSMOD. This method which is very complete assumes that the user provides detailed field knowledge and data, which are not always easily available. The aim of this study is to assist the buffer sizing by using a unique tool with a reduced set of parameters, adapted to the available information from the end-users. In order to fill in the lack of real data in many practical applications, a set of virtual scenarios was selected to encompass a large range of agro-pedo-climatic conditions in Europe, considering both the upslope agricultural field and the VFS characteristics. As a first step first, in this work we present scenarios based on North-West of France climate consisting of different rainfall intensities and durations, hillslope lengths and slopes, humidity conditions, a large set of field rainfall/runoff characteristics for the contributing area, and several shallow water table depths and soil types for the VFS. The sizing method based on the mechanistic model VFSMOD was applied for all these scenarios, and a global sensitivity analysis (GSA) of the VFS optimal length was performed for all the input parameters in order to understand their influence and interactions, and set priorities for data collecting and management. Based on GSA results, we compared several mathematical methods to compute the metamodel, and then validated it on an agricultural watershed with real data in the North-West of France. The analysis procedure allows for a robust and validated metamodel, before extending it on other climatic conditions in order to make the application on a large range of european watersheds possible. The tool will allow comparison of field scenarios, and to validate/improve actual existing placements and VFS sizing.

Analytic Closed-Form Solution of a Mixed Layer Model for Stratocumulus Clouds

NASA Astrophysics Data System (ADS)

Akyurek, Bengu Ozge

Stratocumulus clouds play an important role in climate cooling and are hard to predict using global climate and weather forecast models. Thus, previous studies in the literature use observations and numerical simulation tools, such as large-eddy simulation (LES), to solve the governing equations for the evolution of stratocumulus clouds. In contrast to the previous works, this work provides an analytic closed-form solution to the cloud thickness evolution of stratocumulus clouds in a mixed-layer model framework. With a focus on application over coastal lands, the diurnal cycle of cloud thickness and whether or not clouds dissipate are of particular interest. An analytic solution enables the sensitivity analysis of implicitly interdependent variables and extrema analysis of cloud variables that are hard to achieve using numerical solutions. In this work, the sensitivity of inversion height, cloud-base height, and cloud thickness with respect to initial and boundary conditions, such as Bowen ratio, subsidence, surface temperature, and initial inversion height, are studied. A critical initial cloud thickness value that can be dissipated pre- and post-sunrise is provided. Furthermore, an extrema analysis is provided to obtain the minima and maxima of the inversion height and cloud thickness within 24 h. The proposed solution is validated against LES results under the same initial and boundary conditions. Then, the proposed analytic framework is extended to incorporate multiple vertical columns that are coupled by advection through wind flow. This enables a bridge between the micro-scale and the mesoscale relations. The effect of advection on cloud evolution is studied and a sensitivity analysis is provided.

Influence of watershed topographic and socio-economic attributes on the climate sensitivity of global river water quality

NASA Astrophysics Data System (ADS)

Khan, Afed U.; Jiang, Jiping; Wang, Peng; Zheng, Yi

2017-10-01

Surface waters exhibit regionalization due to various climatic conditions and anthropogenic activities. Here we assess the impact of topographic and socio-economic factors on the climate sensitivity of surface water quality, estimated using an elasticity approach (climate elasticity of water quality (CEWQ)), and identify potential risks of instability in different regions and climatic conditions. Large global datasets were used for 12 main water quality parameters from 43 water quality monitoring stations located at large major rivers. The results demonstrated that precipitation elasticity shows higher sensitivity to topographic and socio-economic determinants as compared to temperature elasticity. In tropical climate class (A), gross domestic product (GDP) played an important role in stabilizing the CEWQ. In temperate climate class (C), GDP played the same role in stability, while the runoff coefficient, slope, and population density fuelled the risk of instability. The results implied that watersheds with lower runoff coefficient, thick population density, over fertilization and manure application face a higher risk of instability. We discuss the socio-economic and topographic factors that cause instability of CEWQ parameters and conclude with some suggestions for watershed managers to bring sustainability in freshwater bodies.

Late Holocene dinosterol hydrogen isotope variability in Lac Lalolalo and Lac Lanutavake on Wallis Island

NASA Astrophysics Data System (ADS)

Maloney, A. E.; Hing, S. N.; Richey, J. N.; Nelson, D. B.; Sachs, J. P.

2017-12-01

The South Pacific Convergence Zone (SPCZ) is the Southern Hemisphere's largest precipitation feature, yet little is known about the region's rainfall prior to the instrumental record. In the tropics, hydrogen isotopes of precipitation are controlled by the "amount effect" where higher mean annual rainfall rates result in 2H-depleted rain. In turn, hydrogen isotopes in tropical lakes are influenced by both rain water isotopes and evaporative enrichment. Molecular fossils preserved in lake sediments offer a promising tool for improving our understanding of the past SPCZ by tracking changes in lake water isotopes. Hydrogen isotope compositions (δ2H) of the algal lipid biomarker dinosterol were measured in duplicate sediment cores from lakes 2.75km apart on Wallis Island. The modern lakes differ in physical and chemical conditions but are both freshwater in the photic zone and experience identical climate conditions. They are an ideal setting to investigate the fidelity to which δ2Hdinosterol records climate. Duplicate records from Lac Lanutavake are in excellent agreement and reveal little change in during the past 1700 years with minor δ2Hdinosterol fluctuations between -280‰ and -290‰. Duplicate records from Lac Lalolalo also agree extremely well during the past 2,000 years. However, contrary to its neighbor, Lac Lalolalo has a highly variable δ2Hdinosterol history with 2H-depleted values of -300‰ during the youngest part of the record climbing to 2H-enriched values of -230‰ around 1000-2000 years ago. The large shift in Lac Lalolalo δ2Hdinosterol may be due to changes in lake biogeochemistry that impact growth conditions or shifts in dinoflagellate species composition. Alternatively, if the Lac Lalolalo record actually reflects changes in hydrology, large limnological changes must have occurred in Lac Lanutavke to mute the climate signal. This work emphasizes the importance of redundancy and duplication when investigating changes in past climate using molecular tools that are also sensitive to environmental parameters.

A Energy Balance Analysis of the Climate Sensitivity to Variations in the Rate of Upwelling in the World Oceans.

NASA Astrophysics Data System (ADS)

Morantine, Michael Creighton

The climate system of the Earth has been under investigation for many years, and the "Green-House Effect" has introduced a sense of urgency into the effort. The globally averaged temperature of the Earth undergoes what is commonly referred to as natural fluctuations in the climate signal. One effort of climate modellers is to isolate the responses of particular climate forcings in order to better understand each effect. The use of energy balance climate models (EBM's) has been one of the major tools in this respect. Studies conducted on the response of the environment to the "Green-House Effect" predict a warming trend. After experiencing such a trend in the early 1900's, however, the globally averaged temperature of the Earth began to decrease in the 1940's and continued this trend for approximately 20 years before resuming its trend of increase. It will be shown that a reduction of ~10% in the upwelling rate in the oceans could produce a decrease in the globally averaged temperature sufficient to explain this departure from the expected trend. The analysis of paleoclimatic indicators has produced strong evidence that the orbital forcing with periods of approximately 21000, 41000 and 93000 years predicted by the Milankovitch Theory is the primary cause of the glacial cycles known to have occurred on the Earth. However, there is a dynamic interaction between the environment and the ice caps that is not completely understood at this time. The paleoclimatic indicators available for the last deglaciation are abundant and well preserved (relative to the evidence of previous glacial periods), and analysis of the evidence indicates that during the most recent deglaciation a pulsation in the polar front occurred on such a small time scale that Milankovitch forcing is ruled out as a possible cause. It will be shown that an abrupt shutdown in the deep-water formation process which feeds the upwelling in the oceans could produce an influence of appropriate magnitude and time-scale to be the source of the dynamic interaction responsible for this abrupt climatic event. The process employed in the dimension reduction used in the formulation of lower-order EBM's will be illustrated through the development of the equations, pointing out the inherent assumptions which must be made when developing one- and two-dimensional models as they are required. One -, two- and three-dimensional energy balance models will be analyzed and the results of climate sensitivity to upwelling variations will be presented graphically for each case.

Climatological temperature senstivity of soil carbon turnover: Observations, simple scaling models, and ESMs

NASA Astrophysics Data System (ADS)

Koven, C. D.; Hugelius, G.; Lawrence, D. M.; Wieder, W. R.

2016-12-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models. To assess the likely long-term response of soils to climate change, spatial gradients in soil carbon turnover times can identify broad-scale and long-term controls on the rate of carbon cycling as a function of climate and other factors. Here we show that the climatological temperature control on carbon turnover in the top meter of global soils is more sensitive in cold climates than in warm ones. We present a simplified model that explains the high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Critically, current Earth system models (ESMs) fail to capture this pattern, however it emerges from an ESM that explicitly resolves vertical gradients in soil climate and turnover. The weak tropical temperature sensitivity emerges from a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong future carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behavior.

Climate threats on growth of rear-edge European beech peripheral populations in Spain.

PubMed

Dorado-Liñán, I; Akhmetzyanov, L; Menzel, A

2017-12-01

European beech (Fagus sylvatica L.) forests in the Iberian Peninsula are a clear example of a temperate forest tree species at the rear edge of its large distribution area in Europe. The expected drier and warmer climate may alter tree growth and species distribution. Consequently, the peripheral populations will most likely be the most threatened ones. Four peripheral beech forests in the Iberian Peninsula were studied in order to assess the climate factors influencing tree growth for the last six decades. The analyses included an individual tree approach in order to detect not only the changes in the sensitivity to climate but also the potential size-mediated sensitivity to climate. Our results revealed a dominant influence of previous and current year summer on tree growth during the last six decades, although the analysis in two equally long periods unveiled changes and shifts in tree sensitivity to climate. The individual tree approach showed that those changes in tree response to climate are not size dependent in most of the cases. We observed a reduced negative effect of warmer winter temperatures at some sites and a generalized increased influence of previous year climatic conditions on current year tree growth. These results highlight the crucial role played by carryover effects and stored carbohydrates for future tree growth and species persistence.

Climate threats on growth of rear-edge European beech peripheral populations in Spain

NASA Astrophysics Data System (ADS)

Dorado-Liñán, I.; Akhmetzyanov, L.; Menzel, A.

2017-12-01

European beech ( Fagus sylvatica L.) forests in the Iberian Peninsula are a clear example of a temperate forest tree species at the rear edge of its large distribution area in Europe. The expected drier and warmer climate may alter tree growth and species distribution. Consequently, the peripheral populations will most likely be the most threatened ones. Four peripheral beech forests in the Iberian Peninsula were studied in order to assess the climate factors influencing tree growth for the last six decades. The analyses included an individual tree approach in order to detect not only the changes in the sensitivity to climate but also the potential size-mediated sensitivity to climate. Our results revealed a dominant influence of previous and current year summer on tree growth during the last six decades, although the analysis in two equally long periods unveiled changes and shifts in tree sensitivity to climate. The individual tree approach showed that those changes in tree response to climate are not size dependent in most of the cases. We observed a reduced negative effect of warmer winter temperatures at some sites and a generalized increased influence of previous year climatic conditions on current year tree growth. These results highlight the crucial role played by carryover effects and stored carbohydrates for future tree growth and species persistence.

CLIMATE CHANGE IN THAILAND AND ITS POTENTIAL IMPACT ON RICE YIELD

EPA Science Inventory

Because of the uncertainties surrounding prediction of climate change, it is common to employ climate scenarios to estimate its impacts on a system. Climate scenarios are sets of climatic perturbations used with models to test system sensitivity to projected changes. In this stud...

Incorporation of surface albedo-temperature feedback in a one-dimensional radiative-connective climate model

NASA Technical Reports Server (NTRS)

Wang, W. C.; Stone, P. H.

1979-01-01

The feedback between ice snow albedo and temperature is included in a one dimensional radiative convective climate model. The effect of this feedback on sensitivity to changes in solar constant is studied for the current values of the solar constant and cloud characteristics. The ice snow albedo feedback amplifies global climate sensitivity by 33% and 50%, respectively, for assumptions of constant cloud altitude and constant cloud temperature.

[Study on sensitivity of climatic factors on influenza A (H1N1) based on classification and regression tree and wavelet analysis].

PubMed

Xiao, Hong; Lin, Xiao-ling; Dai, Xiang-yu; Gao, Li-dong; Chen, Bi-yun; Zhang, Xi-xing; Zhu, Pei-juan; Tian, Huai-yu

2012-05-01

To analyze the periodicity of pandemic influenza A (H1N1) in Changsha in year 2009 and its correlation with sensitive climatic factors. The information of 5439 cases of influenza A (H1N1) and synchronous meteorological data during the period between May 22th and December 31st in year 2009 (223 days in total) in Changsha city were collected. The classification and regression tree (CART) was employed to screen the sensitive climatic factors on influenza A (H1N1); meanwhile, cross wavelet transform and wavelet coherence analysis were applied to assess and compare the periodicity of the pandemic disease and its association with the time-lag phase features of the sensitive climatic factors. The results of CART indicated that the daily minimum temperature and daily absolute humidity were the sensitive climatic factors for the popularity of influenza A (H1N1) in Changsha. The peak of the incidence of influenza A (H1N1) was in the period between October and December (Median (M) = 44.00 cases per day), simultaneously the daily minimum temperature (M = 13°C) and daily absolute humidity (M = 6.69 g/m(3)) were relatively low. The results of wavelet analysis demonstrated that a period of 16 days was found in the epidemic threshold in Changsha, while the daily minimum temperature and daily absolute humidity were the relatively sensitive climatic factors. The number of daily reported patients was statistically relevant to the daily minimum temperature and daily absolute humidity. The frequency domain was mostly in the period of (16 ± 2) days. In the initial stage of the disease (from August 9th and September 8th), a 6-day lag was found between the incidence and the daily minimum temperature. In the peak period of the disease, the daily minimum temperature and daily absolute humidity were negatively relevant to the incidence of the disease. In the pandemic period, the incidence of influenza A (H1N1) showed periodic features; and the sensitive climatic factors did have a "driving effect" on the incidence of influenza A (H1N1).

Effect of ice-albedo feedback on global sensitivity in a one-dimensional radiative-convective climate model

NASA Technical Reports Server (NTRS)

Wang, W.-C.; Stone, P. H.

1980-01-01

The feedback between the ice albedo and temperature is included in a one-dimensional radiative-convective climate model. The effect of this feedback on global sensitivity to changes in solar constant is studied for the current climate conditions. This ice-albedo feedback amplifies global sensitivity by 26 and 39%, respectively, for assumptions of fixed cloud altitude and fixed cloud temperature. The global sensitivity is not affected significantly if the latitudinal variations of mean solar zenith angle and cloud cover are included in the global model. The differences in global sensitivity between one-dimensional radiative-convective models and energy balance models are examined. It is shown that the models are in close agreement when the same feedback mechanisms are included. The one-dimensional radiative-convective model with ice-albedo feedback included is used to compute the equilibrium ice line as a function of solar constant.

Fine scale climatic and soil variability effects on plant species cover along the Front Range of Colorado, USA

NASA Astrophysics Data System (ADS)

Cumming, William Frank Preston

Fine scale studies are rarely performed to address landscape level responses to microclimatic variability. Is it the timing, distribution, and magnitude of soil temperature and moisture that affects what species emerge each season and, in turn, their resilience to fluctuations in microclimate. For this dissertation research, I evaluated the response of vegetation change to microclimatic variability within two communities over a three year period (2009-2012) utilizing 25 meter transects at two locations along the Front Range of Colorado near Boulder, CO and Golden, CO respectively. To assess microclimatic variability, spatial and temporal autocorrelation analyses were performed with soil temperature and moisture. Species cover was assessed along several line transects and correlated with microclimatic variability. Spatial and temporal autocorrelograms are useful tools in identifying the degree of dependency of soil temperature and moisture on the distance and time between pairs of measurements. With this analysis I found that a meter spatial resolution and two-hour measurements are sufficient to capture the fine scale variability in soil properties throughout the year. By comparing this to in situ measurements of soil properties and species percent cover I found that there are several plant functional types and/or species origin in particular that are more sensitive to variations in temperature and moisture than others. When all seasons, locations, correlations, and regional climate are looked at, it is the month of March that stands out in terms of significance. Additionally, of all of the vegetation types represented at these two sites C4, C3, native, non-native, and forb species seem to be the most sensitive to fluctuations in soil temperature, moisture, and regional climate in the spring season. The steady decline in percent species cover the study period and subsequent decrease in percent species cover and size at both locations may indicate that certain are unable to respond to continually higher temperatures and lower moisture availability that is inevitable with future climatic variability.

BASINs 4.0 Climate Assessment Tool (CAT): Supporting Documentation and User's Manual (Final Report)

EPA Science Inventory

EPA announced the availability of the report, BASINS 4.0 Climate Assessment Tool (CAT): Supporting Documentation and User's Manual. This report was prepared by the EPA's Global Change Research Program (GCRP), an assessment-oriented program, that sits within the Office of R...

Adaptive population divergence and directional gene flow across steep elevational gradients in a climate‐sensitive mammal

USGS Publications Warehouse

Waterhouse, Matthew D.; Erb, Liesl P.; Beever, Erik; Russello, Michael A.

2018-01-01

The American pika is a thermally sensitive, alpine lagomorph species. Recent climate-associated population extirpations and genetic signatures of reduced population sizes range-wide indicate the viability of this species is sensitive to climate change. To test for potential adaptive responses to climate stress, we sampled pikas along two elevational gradients (each ~470 to 1640 m) and employed three outlier detection methods, BAYESCAN, LFMM, and BAYPASS, to scan for genotype-environment associations in samples genotyped at 30,763 SNP loci. We resolved 173 loci with robust evidence of natural selection detected by either two independent analyses or replicated in both transects. A BLASTN search of these outlier loci revealed several genes associated with metabolic function and oxygen transport, indicating natural selection from thermal stress and hypoxia. We also found evidence of directional gene flow primarily downslope from large high-elevation populations and reduced gene flow at outlier loci, a pattern suggesting potential impediments to the upward elevational movement of adaptive alleles in response to contemporary climate change. Finally, we documented evidence of reduced genetic diversity associated the south-facing transect and an increase in corticosterone stress levels associated with inbreeding. This study suggests the American pika is already undergoing climate-associated natural selection at multiple genomic regions. Further analysis is needed to determine if the rate of climate adaptation in the American pika and other thermally sensitive species will be able to keep pace with rapidly changing climate conditions.

Central Sensitization and Perceived Indoor Climate among Workers with Chronic Upper-Limb Pain: Cross-Sectional Study

PubMed Central

Jakobsen, Markus D.; Jay, Kenneth; Persson, Roger; Andersen, Lars L.

2015-01-01

Monitoring of indoor climate is an essential part of occupational health and safety. While questionnaires are commonly used for surveillance, not all workers may perceive an identical indoor climate similarly. The aim of this study was to evaluate perceived indoor climate among workers with chronic pain compared with pain-free colleagues and to determine the influence of central sensitization on this perception. Eighty-two male slaughterhouse workers, 49 with upper-limb chronic pain and 33 pain-free controls, replied to a questionnaire with 13 items of indoor climate complaints. Pressure pain threshold (PPT) was measured in muscles of the arm, shoulder, and lower leg. Cross-sectional associations were determined using general linear models controlled for age, smoking, and job position. The number of indoor climate complaints was twice as high among workers with chronic pain compared with pain-free controls (1.8 [95% CI: 1.3–2.3] versus 0.9 [0.4–1.5], resp.). PPT of the nonpainful leg muscle was negatively associated with the number of complaints. Workers with chronic pain reported more indoor climate complaints than pain-free controls despite similar actual indoor climate. Previous studies that did not account for musculoskeletal pain in questionnaire assessment of indoor climate may be biased. Central sensitization likely explains the present findings. PMID:26425368

Glacier Sensitivity Across the Andes

NASA Astrophysics Data System (ADS)

Sagredo, E. A.; Lowell, T. V.; Rupper, S.

2010-12-01

Most of the research on causes driving former glacial fluctuations, and the climatic signals involved, has focused on the comparisons of sequences of glacial events in separate regions of the world and their temporal-phasing relationship with terrestrial or extraterrestrial climate-forcing mechanisms. Nevertheless the climatic signals related with these glacial advances are still under debate. This impossibility to resolve these questions satisfactorily have been generally attributed to the insufficiently precise chronologies and unevenly distributed records. However, behind these ideas lies the implicit assumption that glaciers situated in different climate regimes respond uniformly to similar climatic perturbations. This ongoing research is aimed to explore the climate-glacier relationship at regional scale, through the analysis of the spatial variability of glacier sensitivity to climatic change. By applying a Surface Energy Mass Balance model (SEMB) developed by Rupper and Roe (2008) to glaciers located in different climatic regimes, we analyzed the spatial variability of mass balance changes under different baseline conditions and under different scenarios of climatic change. For the sake of this research, the analysis is being focused on the Andes, which in its 9,000 km along the western margin of South America offers an unparalleled climatic diversity. Preliminary results suggest that above some threshold of climate change (a hypothetical uniform perturbation), all the glaciers across the Andes would respond in the “same direction” (advancing or retreating). Below that threshold, glaciers located in some climatic regimes may be insensitive to the specific perturbation. On the other hand, glaciers located in different climatic regimes may exhibit a “different magnitude” of change under a uniform climatic perturbation. Thus, glaciers located in the dry Andes of Perú, Chile and Argentina are more sensitive to precipitation changes than variations in temperatures, while glaciers located in the wet Patagonian Andes seem to exhibit an opposite behavior. In an intermediate position are those glaciers located in the Tropical Andes, and Tierra del Fuego, which even though still more sensitive to temperature, they can be affected by temperature changes as well. With this regional approach towards the comprehension of climate-glacial dynamic interaction, we expect to contribute to the understanding the causes and mechanism driving former episodes of glacial fluctuations, and in turn, to the development of future scenarios of climate change.

Sea Level Rise Decision Support Tools for Adaptation Planning in Vulnerable Coastal Communities

NASA Astrophysics Data System (ADS)

Rozum, J. S.; Marcy, D.

2015-12-01

NOAA is involved in a myriad of climate related research and projects that help decision makers and the public understand climate science as well as climate change impacts. The NOAA Office for Coastal Management (OCM) provides data, tools, trainings and technical assistance to coastal resource managers. Beginning in 2011, NOAA OCM began developing a sea level rise and coastal flooding impacts viewer which provides nationally consistent data sets and analyses to help communities with coastal management goals such as: understanding and communicating coastal flood hazards, performing vulnerability assessments and increasing coastal resilience, and prioritizing actions for different inundation/flooding scenarios. The Viewer is available on NOAA's Digital Coast platform: (coast.noaa.gov/ditgitalcoast/tools/slr). In this presentation we will share the lessons learned from our work with coastal decision-makers on the role of coastal flood risk data and tools in helping to shape future land use decisions and policies. We will also focus on a recent effort in California to help users understand the similarities and differences of a growing array of sea level rise decision support tools. NOAA staff and other partners convened a workshop entitled, "Lifting the Fog: Bringing Clarity to Sea Level Rise and Shoreline Change Models and Tools," which was attended by tool develops, science translators and coastal managers with the goal to create a collaborative communication framework to help California coastal decision-makers navigate the range of available sea level rise planning tools, and to inform tool developers of future planning needs. A sea level rise tools comparison matrix will be demonstrated. This matrix was developed as part of this effort and has been expanded to many other states via a partnership with NOAA, Climate Central, and The Nature Conservancy.

A hydrogeologic framework for characterizing summer streamflow sensitivity to climate warming in the Pacific Northwest, USA

NASA Astrophysics Data System (ADS)

Safeeq, M.; Grant, G. E.; Lewis, S. L.; Kramer, M. G.; Staab, B.

2014-09-01

Summer streamflows in the Pacific Northwest are largely derived from melting snow and groundwater discharge. As the climate warms, diminishing snowpack and earlier snowmelt will cause reductions in summer streamflow. Most regional-scale assessments of climate change impacts on streamflow use downscaled temperature and precipitation projections from general circulation models (GCMs) coupled with large-scale hydrologic models. Here we develop and apply an analytical hydrogeologic framework for characterizing summer streamflow sensitivity to a change in the timing and magnitude of recharge in a spatially explicit fashion. In particular, we incorporate the role of deep groundwater, which large-scale hydrologic models generally fail to capture, into streamflow sensitivity assessments. We validate our analytical streamflow sensitivities against two empirical measures of sensitivity derived using historical observations of temperature, precipitation, and streamflow from 217 watersheds. In general, empirically and analytically derived streamflow sensitivity values correspond. Although the selected watersheds cover a range of hydrologic regimes (e.g., rain-dominated, mixture of rain and snow, and snow-dominated), sensitivity validation was primarily driven by the snow-dominated watersheds, which are subjected to a wider range of change in recharge timing and magnitude as a result of increased temperature. Overall, two patterns emerge from this analysis: first, areas with high streamflow sensitivity also have higher summer streamflows as compared to low-sensitivity areas. Second, the level of sensitivity and spatial extent of highly sensitive areas diminishes over time as the summer progresses. Results of this analysis point to a robust, practical, and scalable approach that can help assess risk at the landscape scale, complement the downscaling approach, be applied to any climate scenario of interest, and provide a framework to assist land and water managers in adapting to an uncertain and potentially challenging future.

Ecoclimatic indicators to study climate suitability of areas for the cultivation of specific crops

NASA Astrophysics Data System (ADS)

Caubel, J.; Garcia de Cortazar Atauri, I.; Cufi, J.; Huard, F.; Launay, M.; Ripoche, D.; Graux, A.; deNoblet, N.

2013-12-01

Climatic conditions play a fundamental role in the suitability of geographical areas for cropping. In the context of climate change, we could expect changes in overall climatic conditions and so, on the suitability for cropping. Therefore, assessing the future climate suitability of areas for cropping is decisive for anticipating agriculture in a given area. Moreover, it is crucial to have access to the split up information concerning the effect of climate on the achievement of the main ecophysiological processes and cultural practices taking place during the crop cycle. In this way, stakeholders can envisage land use adaptations under climate change conditions, such as changes in cultural practices or development of new varieties for example. We proposed an aggregation tool of ecoclimatic indicators to design evaluation trees of climate suitability of areas for cropping, GETARI (Generic Evaluation Tool of Ecoclimatic Indicators). It calculates an overall climate suitability index at the annual scale, from a designed evaluation tree. This aggregation tool allows to characterize climate suitability according to crop ecophysiology, grain/fruit quality or crop management. GETARI proposes the major ecophysiological processes and cultural practices taking place during phenological periods, together with the climatic effects that are known to affect their achievement. The climatic effects on the ecophysiological processes (or cultural practices) during phenological periods are captured by the ecoclimatic indicators, which are agroclimatic indicators calculated over phenological periods. They give information about crop response to climate through ecophysiological or agronomic thresholds. Those indices of suitability are normalized and aggregated according to aggregation rules in order to compute an overall climate index. In order to illustrate how GETARI can be used, we designed evaluation trees in order to study the climate suitability for maize cropping regarding ecophysiology, for wheat cropping regarding its management and for grape cropping regarding its quality. The designed evaluation trees were developed in accordance with expert assessment and were applied in some past climatic conditions in France to verify their consistence. To conclude, the use of indicators does not replace models but represent additional tools for understanding and spatializing some results obtained by models. Their use can provide information about suitability of geographical areas for cropping in future climatic conditions and can enable to minimize the risk of crop failure. This work is carried out under the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe).

Characterizing Flow and Suspended Sediment Trends in the Sacramento River Basin, CA Using Hydrologic Simulation Program - FORTRAN (HSPF)

NASA Astrophysics Data System (ADS)

Stern, M. A.; Flint, L. E.; Flint, A. L.; Wright, S. A.; Minear, J. T.

2014-12-01

A watershed model of the Sacramento River Basin, CA was developed to simulate streamflow and suspended sediment transport to the San Francisco Bay Delta (SFBD) for fifty years (1958-2008) using the Hydrological Simulation Program - FORTRAN (HSPF). To compensate for the large model domain and sparse data, rigorous meteorological development and characterization of hydraulic geometry were employed to spatially distribute climate and hydrologic processes in unmeasured locations. Parameterization techniques sought to include known spatial information for tributaries such as soil information and slope, and then parameters were scaled up or down during calibration to retain the spatial characteristics of the land surface in un-gaged areas. Accuracy was assessed by comparing model calibration to measured streamflow. Calibration and validation of the Sacramento River ranged from "good" to "very good" performance based upon a "goodness-of-fit" statistical guideline. Model calibration to measured sediment loads were underestimated on average by 39% for the Sacramento River, and model calibration to suspended sediment concentrations were underestimated on average by 22% for the Sacramento River. Sediment loads showed a slight decreasing trend from 1958-2008 and was significant (p < 0.0025) in the lower 50% of stream flows. Hypothetical climate change scenarios were developed using the Climate Assessment Tool (CAT). Several wet and dry scenarios coupled with temperature increases were imposed on the historical base conditions to evaluate sensitivity of streamflow and sediment on potential changes in climate. Wet scenarios showed an increase of 9.7 - 17.5% in streamflow, a 7.6 - 17.5% increase in runoff, and a 30 - 93% increase in sediment loads. The dry scenarios showed a roughly 5% decrease in flow and runoff, and a 16 - 18% decrease in sediment loads. The base hydrology was most sensitive to a temperature increase of 1.5 degrees Celsius and an increase in storm intensity and frequency. The complete calibrated HSPF model will use future climate scenarios to make projections of potential hydrologic and sediment trends to the SFBD from 2000-2100.

Sensitivity of health sector indicators' response to climate change in Ghana.

PubMed

Dovie, Delali B K; Dzodzomenyo, Mawuli; Ogunseitan, Oladele A

2017-01-01

There is accumulating evidence that the emerging burden of global climate change threatens the fidelity of routine indicators for disease detection and management of risks to public health. The threat partially reflects the conservative character of the health sector and the reluctance to adopt new indicators, despite the growing awareness that existing environmental health indicators were developed to respond to risks that may no longer be relevant, and are too simplistic to also act as indicators for newer global-scale risk factors. This study sought to understand the scope of existing health indicators, while aiming to discover new indicators for building resilience against three climate sensitive diseases (cerebro spinal meningitis, malaria and diarrhea). Therefore, new potential indicators derived from human and biophysical origins were developed to complement existing health indicators, thereby creating climate-sensitive battery of robust composite indices of resilience in health planning. Using Ghana's health sector as a case study systematic international literature review, national expert consultation, and focus group outcomes yielded insights into the relevance, sensitivity and impacts of 45 indicators in 11 categories in responding to climate change. In total, 65% of the indicators were sensitive to health impacts of climate change; 24% acted directly; 31% synergistically; and 45% indirectly, with indicator relevance strongly associated with type of health response. Epidemiological indicators (e.g. morbidity) and health demographic indicators (e.g. population structure) require adjustments with external indicators (e.g. biophysical, policy) to be resilient to climate change. Therefore, selective integration of social and ecological indicators with existing public health indicators improves the fidelity of the health sector to adopt more robust planning of interdependent systems to build resilience. The study highlights growing uncertainties in translating research into protective policies when new indicators associated with non-health sources are needed to complement existing health indicators that are expected to respond to climate change. Copyright © 2016 Elsevier B.V. All rights reserved.

Climate Science Centers: An "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas

NASA Astrophysics Data System (ADS)

Moore, B., III

2014-12-01

Climate Science Centers: An "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas. Berrien Moore III (University of Oklahoma) The South Central Climate Science Center (CSC) is one of eight regional centers established by the Department of the Interior (DoI) under Secretarial Order 3289 to address the impacts of climate change on America's water, land, and other natural and cultural resources. Under DoI leadership and funding, these CSCs will provide scientific information tools and techniques to study impacts of climate change synthesize and integrate climate change impact data develop tools that the DoI managers and partners can use when managing the DOI's land, water, fish and wildlife, and cultural heritage resources (emphasis added) The network of Climate Science Centers will provide decision makers with the science, tools, and information they need to address the impacts of climate variability and change on their areas of responsibility. Note from Webster, a tool is a device for doing work; it makes outcomes more realizable and more cost effective, and, in a word, better. Prior to the existence of CSCs, the university and federal scientific world certainly contained a large "set" of scientists with considerable strength in the physical, biological, natural, and social sciences to address the complexities and interdisciplinary nature of the challenges in the areas of climate variability, change, impacts, and adaptation. However, this set of scientists were hardly an integrated community let alone a focused team, but rather a collection of distinguished researchers, educators, and practitioners that were working with disparate though at times linked objectives, and they were rarely aligning themselves formally to an overarching strategic pathway. In addition, data, models, research results, tools, and products were generally somewhat "disconnected" from the broad range of stakeholders. I should note also that NOAA's Regional Integrated Sciences and Assessments ( RISA) program is an earlier "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas. This contribution will discuss the important cultural shift that has flowed from Secretarial Order 3289.

Nonlinear climatic sensitivity to greenhouse gases over past 4 glacial/interglacial cycles.

PubMed

Lo, Li; Chang, Sheng-Pu; Wei, Kuo-Yen; Lee, Shih-Yu; Ou, Tsong-Hua; Chen, Yi-Chi; Chuang, Chih-Kai; Mii, Horng-Sheng; Burr, George S; Chen, Min-Te; Tung, Ying-Hung; Tsai, Meng-Chieh; Hodell, David A; Shen, Chuan-Chou

2017-07-04

The paleoclimatic sensitivity to atmospheric greenhouse gases (GHGs) has recently been suggested to be nonlinear, however a GHG threshold value associated with deglaciation remains uncertain. Here, we combine a new sea surface temperature record spanning the last 360,000 years from the southern Western Pacific Warm Pool with records from five previous studies in the equatorial Pacific to document the nonlinear relationship between climatic sensitivity and GHG levels over the past four glacial/interglacial cycles. The sensitivity of the responses to GHG concentrations rises dramatically by a factor of 2-4 at atmospheric CO 2 levels of >220 ppm. Our results suggest that the equatorial Pacific acts as a nonlinear amplifier that allows global climate to transition from deglacial to full interglacial conditions once atmospheric CO 2 levels reach threshold levels.

Direct and inverse modelling for environmental risk assessment and emission control

NASA Astrophysics Data System (ADS)

Penenko, V.; Baklanov, A.; Tsvetova, E.; Mahura, A.

2009-04-01

A concept of environmental modelling and its applications for Siberian regions are presented. The regions are considered both as sources and receptors of pollution as elements of the global climatic system. A methodology has been developed to build the combined methods of forward and inverse modelling for the problems of the air quality, environmental risk assessment and control. It is based on variational principles and methods of adjoint sensitivity theory. This allows obtaining the optimal numerical schemes and universal algorithm of the forward-inverse modelling. Following the concept, the functionals (describing the generalised characteristics of the processes, data, and models) are considered together with the basic model components. To combine all these elements in the frames of forward and inverse relations, we suppose that each of them may contain uncertainty. In this case, it is naturally to formulate a weak-constraint variational principle for the augmented functional which contains the model description in the form of integral identity and the cost functional including the total measure of all uncertainties. The stationary conditions for the augmented functional with respect to the variations its functional arguments define the mutually agreed structure of numerical schemes for forward and adjoint problems, and sensitivity relations. For quantitative risk assessment the following characteristics are useful: (i) values of goal functionals and their variations in a form of sensitivity relations; (ii) risk and sensitivity functions to the variations of the sources. It is convenient to take the risk function multiplied by the source function as a distributed risk measure. The variational technique provides the backward propagation of information, contained in the target functionals, to parameters and sources of the models through the sensitivity and uncertainty functions. This gives a base for realisation of the feedback algorithms and methods of control theory, which are necessary for formulation of multi-criteria optimisation accounting different constraints of ecological, economical, and social essence while solving environmental problems such as air pollution control, placement design for new industrial units, etc. The problems of the long-term environmental forecasting demand revealing the dynamical active zones and the areas of increased sensitivity to the variations of forcings (model parameters). The proposed methodology of accounting the climatic data into environmental studies is suitable for studying such problems. Analysis of the long-term behaviour of the global climatic system and orthogonal decomposition of the multivariate series of meteorological data with respect to the scales of processes allows identifying the activity centers and using this information for construction of scenarios for assessment of risk/vulnerability for sources/receptors. Such analysis for Siberian regions showed that Siberia is situated in areas which separate circulation systems of high energy activity. For winter, they are the Pacific and Atlantic energy-active zones, whereas the Arctic and South-Asian zones withstand in Siberia in summer. These facts allow an interpretation of climatic instability inherent in the region. During the autumn-winter season, the instability expresses as sharp alteration of weather cycles. The formation of Altai-Sayan cyclogenesis (which is of the same intensity as the Mediterranean) is observed for the warm seasons in the southern Siberia. In climatology it is referred as a lee-type cyclogenesis. This is the large scale phenomenon in the climatic system of the central part of Eurasia. Such specific hydrodynamic background defines environment quality in Siberia. From the point of view of system analysis, the methods of sensitivity theory, risk assessment and control along with scenario approach offer a tool which allows bringing the results of the global atmospheric and climatic studies onto the regional level. Namely, this level puts the concrete questions on the environment quality and its changes such as a choice of plausible strategy for sources control and mitigation of the man-induced impact on environment. Some environmental problems for Siberian regions are discussed, and a number of forward, adjoint and inverse problems for different risk sites and goal functionals are presented.

How Philadelphia is Integrating Climate Science and Policy: Changing Capital Planning Processes and Developing Flood-Depth Tools

NASA Astrophysics Data System (ADS)

Bhat, C.; Dix, B.; Choate, A.; Wong, A.; Asam, S.; Schultz, P. A.

2016-12-01

Policy makers can implement more effective climate change adaptation programs if they are provided with two tools: accessible information on the impacts that they need to prepare for, and clear guidance on how to integrate climate change considerations into their work. This presentation will highlight recent and ongoing efforts at the City of Philadelphia to integrate climate science into their decision-making. These efforts include developing a climate change information visualization tool, climate change risk assessments across the city, and processes to integrate climate change into routine planning and budgeting practices. The goal of these efforts is to make climate change science highly targeted to decision maker needs, non-political, easily accessible, and actionable. While sea level rise inundation maps have been available to communities for years, the maps do not effectively communicate how the design of a building or a piece of infrastructure would need to be modified to protect it. The Philadelphia Flood Risk Viewer is an interactive planning tool that allows Philadelphia to identify projected depths of flooding for any location within the City, for a variety of sea level rise and storm surge scenarios. Users can also determine whether a location is located in a FEMA floodplain. By having access to information on the projected depth of flooding at a given location, the City can determine what flood protection measures may be effective, or even inform the long-term viability of developing a particular area. With an understanding of climate vulnerabilities, cities have the opportunity to make smart, climate-resilient investments with their capital budgets that will yield multiple benefits for years to come. Few, however, have established protocols for doing so. Philadelphia, with support from ICF, developed a guidance document that identifies recommendations for integrating climate change considerations throughout the Capital Program and capital budgeting process. For each recommendation, the guidance also provides supplemental resources and information to make the recommendations actionable. Philadelphia is applying the guidance in their FY 2017 capital planning activities and taking advantage of opportunities to grow stronger in the face of climate change.

Developing rural community health risk assessments for climate change: a Tasmanian pilot study.

PubMed

Bell, Erica J; Turner, Paul; Meinke, Holger; Holbrook, Neil J

2015-01-01

This article examines the development and pilot implementation of an approach to support local community decision-makers to plan health adaptation responses to climate change. The approach involves health and wellbeing risk assessment supported through the use of an electronic tool. While climate change is a major foreseeable public health threat, the extent to which health services are prepared for, or able to adequately respond to, climate change impact-related risks remains unclear. Building health decision-support mechanisms in order to involve and empower local stakeholders to help create the basis for agreement on these adaptive actions is an important first step. The primary research question was 'What can be learned from pilot implementation of a community health and well-being risk assessment (CHWRA) information technology-based tool designed to support understanding of, and decision-making on, local community challenges and opportunities associated with health risks posed by climate change? The article examines the complexity of climate change science to adaptation translational processes, with reference to existing research literature on community development. This is done in the context of addressing human health risks for rural and remote communities in Tasmania, Australia. This process is further examined through the pilot implementation of an electronic tool designed to support the translation of physically based climate change impact information into community-level assessments of health risks and adaptation priorities. The procedural and technical nature of the CHWRA tool is described, and the implications of the data gathered from stakeholder workshops held at three rural Tasmanian local government sites are considered and discussed. Bushfire, depression and waterborne diseases were identified by community stakeholders as being potentially 'catastrophic' health effects 'likely' to 'almost certain' to occur at one or more Tasmanian rural sites - based on an Intergovernmental Panel on Climate Change style of assessment. Consensus statements from stakeholders also suggested concern with health sector adaptation capacity and community resilience, and what community stakeholders defined as 'last straw' climate effects in already stressed communities. Preventative action and community engagement were also seen as important, especially with regard to managing the ways that climate change can multiply socioeconomic and health outcome inequality. Above all, stakeholder responses emphasised the importance of an applied, complexity-oriented understanding of how climate and climate change impacts affect local communities and local services to compromise the overall quality of human health in these communities. Complex community-level assessments about climate change and related health risks and responses can be captured electronically in ways that offer potentially actionable information about priorities for health sector adaptation, as a first step in planning. What is valuable about these community judgements is the creation of shared values and commitments. Future iteration of the IT tool could include decision-support modules to support best practice health sector adaptation scenarios, providing participants with opportunities to develop their know-how about health sector adaptation to climate change. If managed carefully, such tools could work within a balanced portfolio of measures to help reduce the rising health burden from climate change.

Modeling Climate Change Impacts on Landscape Evolution, Fire, and Hydrology

NASA Astrophysics Data System (ADS)

Sheppard, B. S.; O Connor, C.; Falk, D. A.; Garfin, G. M.

2015-12-01

Landscape disturbances such as wildfire interact with climate variability to influence hydrologic regimes. We coupled landscape, fire, and hydrologic models and forced them using projected climate to demonstrate climate change impacts anticipated at Fort Huachuca in southeastern Arizona, USA. The US Department of Defense (DoD) recognizes climate change as a trend that has implications for military installations, national security and global instability. The goal of this DoD Strategic Environmental Research and Development Program (SERDP) project (RC-2232) is to provide decision making tools for military installations in the southwestern US to help them adapt to the operational realities associated with climate change. For this study we coupled the spatially explicit fire and vegetation dynamics model FireBGCv2 with the Automated Geospatial Watershed Assessment tool (AGWA) to evaluate landscape vegetation change, fire disturbance, and surface runoff in response to projected climate forcing. A projected climate stream for the years 2005-2055 was developed from the Multivariate Adaptive Constructed Analogs (MACA) 4 km statistical downscaling of the CanESM2 GCM using Representative Concentration Pathway (RCP) 8.5. AGWA, an ArcGIS add-in tool, was used to automate the parameterization and execution of the Soil Water Assessment Tool (SWAT) and the KINematic runoff and EROSion2 (KINEROS2) models based on GIS layers. Landscape raster data generated by FireBGCv2 project an increase in fire and drought associated tree mortality and a decrease in vegetative basal area over the years of simulation. Preliminary results from SWAT modeling efforts show an increase to surface runoff during years following a fire, and for future winter rainy seasons. Initial results from KINEROS2 model runs show that peak runoff rates are expected to increase 10-100 fold as a result of intense rainfall falling on burned areas.

Climate services to improve public health.

PubMed

Jancloes, Michel; Thomson, Madeleine; Costa, María Mánez; Hewitt, Chris; Corvalan, Carlos; Dinku, Tufa; Lowe, Rachel; Hayden, Mary

2014-04-25

A high level expert panel discussed how climate and health services could best collaborate to improve public health. This was on the agenda of the recent Third International Climate Services Conference, held in Montego Bay, Jamaica, 4-6 December 2013. Issues and challenges concerning a demand led approach to serve the health sector needs, were identified and analysed. Important recommendations emerged to ensure that innovative collaboration between climate and health services assist decision-making processes and the management of climate-sensitive health risk. Key recommendations included: a move from risk assessment towards risk management; the engagement of the public health community with both the climate sector and development sectors, whose decisions impact on health, particularly the most vulnerable; to increase operational research on the use of policy-relevant climate information to manage climate- sensitive health risks; and to develop in-country capacities to improve local knowledge (including collection of epidemiological, climate and socio-economic data), along with institutional interaction with policy makers.

Forest disturbances under climate change

NASA Astrophysics Data System (ADS)

Seidl, Rupert; Thom, Dominik; Kautz, Markus; Martin-Benito, Dario; Peltoniemi, Mikko; Vacchiano, Giorgio; Wild, Jan; Ascoli, Davide; Petr, Michal; Honkaniemi, Juha; Lexer, Manfred J.; Trotsiuk, Volodymyr; Mairota, Paola; Svoboda, Miroslav; Fabrika, Marek; Nagel, Thomas A.; Reyer, Christopher P. O.

2017-06-01

Forest disturbances are sensitive to climate. However, our understanding of disturbance dynamics in response to climatic changes remains incomplete, particularly regarding large-scale patterns, interaction effects and dampening feedbacks. Here we provide a global synthesis of climate change effects on important abiotic (fire, drought, wind, snow and ice) and biotic (insects and pathogens) disturbance agents. Warmer and drier conditions particularly facilitate fire, drought and insect disturbances, while warmer and wetter conditions increase disturbances from wind and pathogens. Widespread interactions between agents are likely to amplify disturbances, while indirect climate effects such as vegetation changes can dampen long-term disturbance sensitivities to climate. Future changes in disturbance are likely to be most pronounced in coniferous forests and the boreal biome. We conclude that both ecosystems and society should be prepared for an increasingly disturbed future of forests.

Forest disturbances under climate change

PubMed Central

Seidl, Rupert; Thom, Dominik; Kautz, Markus; Martin-Benito, Dario; Peltoniemi, Mikko; Vacchiano, Giorgio; Wild, Jan; Ascoli, Davide; Petr, Michal; Honkaniemi, Juha; Lexer, Manfred J.; Trotsiuk, Volodymyr; Mairota, Paola; Svoboda, Miroslav; Fabrika, Marek; Nagel, Thomas A.; Reyer, Christopher P. O.

2017-01-01

Forest disturbances are sensitive to climate. However, our understanding of disturbance dynamics in response to climatic changes remains incomplete, particularly regarding large-scale patterns, interaction effects and dampening feedbacks. Here we provide a global synthesis of climate change effects on important abiotic (fire, drought, wind, snow and ice) and biotic (insects and pathogens) disturbance agents. Warmer and drier conditions particularly facilitate fire, drought and insect disturbances, while warmer and wetter conditions increase disturbances from wind and pathogens. Widespread interactions between agents are likely to amplify disturbances, while indirect climate effects such as vegetation changes can dampen long-term disturbance sensitivities to climate. Future changes in disturbance are likely to be most pronounced in coniferous forests and the boreal biome. We conclude that both ecosystems and society should be prepared for an increasingly disturbed future of forests. PMID:28861124

A Bayesian Ensemble Approach for Epidemiological Projections

PubMed Central

Lindström, Tom; Tildesley, Michael; Webb, Colleen

2015-01-01

Mathematical models are powerful tools for epidemiology and can be used to compare control actions. However, different models and model parameterizations may provide different prediction of outcomes. In other fields of research, ensemble modeling has been used to combine multiple projections. We explore the possibility of applying such methods to epidemiology by adapting Bayesian techniques developed for climate forecasting. We exemplify the implementation with single model ensembles based on different parameterizations of the Warwick model run for the 2001 United Kingdom foot and mouth disease outbreak and compare the efficacy of different control actions. This allows us to investigate the effect that discrepancy among projections based on different modeling assumptions has on the ensemble prediction. A sensitivity analysis showed that the choice of prior can have a pronounced effect on the posterior estimates of quantities of interest, in particular for ensembles with large discrepancy among projections. However, by using a hierarchical extension of the method we show that prior sensitivity can be circumvented. We further extend the method to include a priori beliefs about different modeling assumptions and demonstrate that the effect of this can have different consequences depending on the discrepancy among projections. We propose that the method is a promising analytical tool for ensemble modeling of disease outbreaks. PMID:25927892

Pleistocene tropical Pacific temperature sensitivity to radiative greenhouse gas forcing

NASA Astrophysics Data System (ADS)

Dyck, K. A.; Ravelo, A. C.

2011-12-01

How high will Earth's global average surface temperature ultimately rise as greenhouse gas concentrations increase in the future? One way to tackle this question is to compare contemporaneous temperature and greenhouse gas concentration data from paleoclimate records, while considering that other radiative forcing mechanisms (e.g. changes in the amount and distribution of incoming solar radiation associated with changes in the Earth's orbital configuration) also contribute to surface temperature change. Since the sensitivity of surface temperature varies with location and latitude, here we choose a central location representative of the west Pacific warm pool, far from upwelling regions or surface temperature gradients in order to minimize climate feedbacks associated with high-latitude regions or oceanic dynamics. The 'steady-state' or long-term temperature change associated with greenhouse gas radiative forcing is often labeled as equilibrium (or 'Earth system') climate sensitivity to the doubling of atmospheric greenhouse gas concentration. Climate models suggest that Earth system sensitivity does not change dramatically over times when CO2 was lower or higher than the modern atmospheric value. Thus, in our investigation of the changes in tropical SST, from the glacial to interglacial states when greenhouse gas forcing nearly doubled, we use Late Pleistocene paleoclimate records to constrain earth system sensitivity for the tropics. Here we use Mg/Ca-paleothermometry using the foraminifera G. ruber from ODP Site 871 from the past 500 kyr in the western Pacific warm pool to estimate tropical Pacific equilibrium climate sensitivity to a doubling of greenhouse gas concentrations to be ~4°C. This tropical SST sensitivity to greenhouse gas forcing is ~1-2°C higher than that predicted by climate models of past glacial periods or future warming for the tropical Pacific. Equatorial Pacific SST sensitivity may be higher than predicted by models for a number of reasons. First, models may not be adequately representing long-term deep ocean feedbacks. Second, models may incorrectly parameterize tropical cloud (or other short-term) feedback processes. Lastly, either paleo-temperature or radiative forcing may have been incorrectly estimated (e.g. through calibration of paleoclimate evidence for temperature change). Since theory suggests that surface temperature in the high latitudes is more sensitive to radiative forcing changes than surface temperature in the tropics, the results of this study also imply that globally averaged Earth system sensitivity to greenhouse gas concentrations may be higher than most climate models predict.

Assessing the sensitivity of avian species abundance to land cover and climate

Treesearch

Jaymi J. LeBrun; Wayne E. Thogmartin; Frank R. Thompson; William D. Dijak; Joshua J. Millspaugh

2016-01-01

Climate projections for the Midwestern United States predict southerly climates to shift northward. These shifts in climate could alter distributions of species across North America through changes in climate (i.e., temperature and precipitation), or through climate-induced changes on land cover. Our objective was to determine the relative impacts of land cover and...

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...

ClimateWizard: A Framework and Easy-to-Use Web-Mapping Tool for Global, Regional, and Local Climate-Change Analysis

NASA Astrophysics Data System (ADS)

Girvetz, E. H.; Zganjar, C.; Raber, G. T.; Hoekstra, J.; Lawler, J. J.; Kareiva, P.

2008-12-01

Now that there is overwhelming evidence of global climate change, scientists, managers and planners (i.e. practitioners) need to assess the potential impacts of climate change on particular ecological systems, within specific geographic areas, and at spatial scales they care about, in order to make better land management, planning, and policy decisions. Unfortunately, this application of climate science to real world decisions and planning has proceeded too slowly because we lack tools for translating cutting-edge climate science and climate-model outputs into something managers and planners can work with at local or regional scales (CCSP 2008). To help increase the accessibility of climate information, we have developed a freely-available, easy-to-use, web-based climate-change analysis toolbox, called ClimateWizard, for assessing how climate has and is projected to change at specific geographic locations throughout the world. The ClimateWizard uses geographic information systems (GIS), web-services (SOAP/XML), statistical analysis platforms (e.g. R- project), and web-based mapping services (e.g. Google Earth/Maps, KML/GML) to provide a variety of different analyses (e.g. trends and departures) and outputs (e.g. maps, graphs, tables, GIS layers). Because ClimateWizard analyzes large climate datasets stored remotely on powerful computers, users of the tool do not need to have fast computers or expensive software, but simply need access to the internet. The analysis results are then provided to users in a Google Maps webpage tailored to the specific climate-change question being asked. The ClimateWizard is not a static product, but rather a framework to be built upon and modified to suit the purposes of specific scientific, management, and policy questions. For example, it can be expanded to include bioclimatic variables (e.g. evapotranspiration) and marine data (e.g. sea surface temperature), as well as improved future climate projections, and climate-change impact analyses involving hydrology, vegetation, wildfire, disease, and food security. By harnessing the power of computer and web- based technologies, the ClimateWizard puts local, regional, and global climate-change analyses in the hands of a wider array of managers, planners, and scientists.

Simplified tools for evaluating domestic ventilation systems

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

Maansson, L.G.; Orme, M.

1999-07-01

Within an International Energy Agency (IEA) project, Annex 27, experts from 8 countries (Canada, France, Italy, Japan, The Netherlands, Sweden, UK and USA) have developed simplified tools for evaluating domestic ventilation systems during the heating season. Tools for building and user aspects, thermal comfort, noise, energy, life cycle cost, reliability and indoor air quality (IAQ) have been devised. The results can be used both for dwellings at the design stage and after construction. The tools lead to immediate answers and indications about the consequences of different choices that may arise during discussion with clients. This paper presents an introduction tomore » these tools. Examples applications of the indoor air quality and energy simplified tools are also provided. The IAQ tool accounts for constant emission sources, CO{sub 2}, cooking products, tobacco smoke, condensation risks, humidity levels (i.e., for judging the risk for mould and house dust mites), and pressure difference (for identifying the risk for radon or land fill spillage entering the dwelling or problems with indoor combustion appliances). An elaborated set of design parameters were worked out that resulted in about 17,000 combinations. By using multi-variate analysis it was possible to reduce this to 174 combinations for IAQ. In addition, a sensitivity analysis was made using 990 combinations. The results from all the runs were used to develop a simplified tool, as well as quantifying equations relying on the design parameters. A computerized energy tool has also been developed within this project, which takes into account air tightness, climate, window airing pattern, outdoor air flow rate and heat exchange efficiency.« less

New Tools for Sea Ice Data Analysis and Visualization: NSIDC's Arctic Sea Ice News and Analysis

NASA Astrophysics Data System (ADS)

Vizcarra, N.; Stroeve, J.; Beam, K.; Beitler, J.; Brandt, M.; Kovarik, J.; Savoie, M. H.; Skaug, M.; Stafford, T.

2017-12-01

Arctic sea ice has long been recognized as a sensitive climate indicator and has undergone a dramatic decline over the past thirty years. Antarctic sea ice continues to be an intriguing and active field of research. The National Snow and Ice Data Center's Arctic Sea Ice News & Analysis (ASINA) offers researchers and the public a transparent view of sea ice data and analysis. We have released a new set of tools for sea ice analysis and visualization. In addition to Charctic, our interactive sea ice extent graph, the new Sea Ice Data and Analysis Tools page provides access to Arctic and Antarctic sea ice data organized in seven different data workbooks, updated daily or monthly. An interactive tool lets scientists, or the public, quickly compare changes in ice extent and location. Another tool allows users to map trends, anomalies, and means for user-defined time periods. Animations of September Arctic and Antarctic monthly average sea ice extent and concentration may also be accessed from this page. Our tools help the NSIDC scientists monitor and understand sea ice conditions in near real time. They also allow the public to easily interact with and explore sea ice data. Technical innovations in our data center helped NSIDC quickly build these tools and more easily maintain them. The tools were made publicly accessible to meet the desire from the public and members of the media to access the numbers and calculations that power our visualizations and analysis. This poster explores these tools and how other researchers, the media, and the general public are using them.

Why Hasn't Earth Warmed as Much as Expected?

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

High intra-specific variation in avian body condition responses to climate limits generalisation across species

PubMed Central

van der Jeugd, Henk P.; van de Pol, Martijn

2018-01-01

It is generally assumed that populations of a species will have similar responses to climate change, and thereby that a single value of sensitivity will reflect species-specific responses. However, this assumption is rarely systematically tested. High intraspecific variation will have consequences for identifying species- or population-level traits that can predict differences in sensitivity, which in turn can affect the reliability of projections of future climate change impacts. We investigate avian body condition responses to changes in six climatic variables and how consistent and generalisable these responses are both across and within species, using 21 years of data from 46 common passerines across 80 Dutch sites. We show that body condition decreases with warmer spring/early summer temperatures and increases with higher humidity, but other climate variables do not show consistent trends across species. In the future, body condition is projected to decrease by 2050, mainly driven by temperature effects. Strikingly, populations of the same species generally responded just as differently as populations of different species implying that a single species signal is not meaningful. Consequently, species-level traits did not explain interspecific differences in sensitivities, rather population-level traits were more important. The absence of a clear species signal in body condition responses implies that generalisation and identifying species for conservation prioritisation is problematic, which sharply contrasts conclusions of previous studies on the climate sensitivity of phenology. PMID:29466460

Climate sensitivity of thinleaf alder growth on an interior Alaska floodplain

Treesearch

Dana R. Nossov; Roger W. Ruess; Teresa N. Hollingsworth

2010-01-01

This study examined the climate sensitivity of the growth of riparian Alnus incana ssp. tenuifolia (thinleaf alder), a keystone nitrogen-fixer, on the Tanana River floodplain of interior Alaska. We investigated correlations between alder radial growth and inter-annual variation in monthly meteorology and hydrology, spatial...

Enhancement of Local Climate Analysis Tool

NASA Astrophysics Data System (ADS)

Horsfall, F. M.; Timofeyeva, M. M.; Dutton, J.

2012-12-01

The National Oceanographic and Atmospheric Administration (NOAA) National Weather Service (NWS) will enhance its Local Climate Analysis Tool (LCAT) to incorporate specific capabilities to meet the needs of various users including energy, health, and other communities. LCAT is an online interactive tool that provides quick and easy access to climate data and allows users to conduct analyses at the local level such as time series analysis, trend analysis, compositing, correlation and regression techniques, with others to be incorporated as needed. LCAT uses principles of Artificial Intelligence in connecting human and computer perceptions on application of data and scientific techniques in multiprocessing simultaneous users' tasks. Future development includes expanding the type of data currently imported by LCAT (historical data at stations and climate divisions) to gridded reanalysis and General Circulation Model (GCM) data, which are available on global grids and thus will allow for climate studies to be conducted at international locations. We will describe ongoing activities to incorporate NOAA Climate Forecast System (CFS) reanalysis data (CFSR), NOAA model output data, including output from the National Multi Model Ensemble Prediction System (NMME) and longer term projection models, and plans to integrate LCAT into the Earth System Grid Federation (ESGF) and its protocols for accessing model output and observational data to ensure there is no redundancy in development of tools that facilitate scientific advancements and use of climate model information in applications. Validation and inter-comparison of forecast models will be included as part of the enhancement to LCAT. To ensure sustained development, we will investigate options for open sourcing LCAT development, in particular, through the University Corporation for Atmospheric Research (UCAR).

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

2012-01-01

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

The Earth Gravitational Model 1996: The NCCS: Resource for Development, Resource for the Future

NASA Technical Reports Server (NTRS)

2002-01-01

For centuries, men have attempted to understand the climate system through observations obtained from Earth's surface. These observations yielded preliminary understanding of the ocean currents, tides, and prevailing winds using visual observation and simple mechanical tools as their instruments. Today's sensitive, downward-looking radar systems, called altimeters, onboard satellites can measure globally the precise height of the ocean surface. This surface is largely that of the equipotential gravity surface, called the geoid - the level surface to which the oceans would conform if there were no forces acting on them apart from gravity, as well as having a significant 1-2- meter-level signal arising from the motion of the ocean's currents.

Sensitivity of Precipitation in Coupled Land-Atmosphere Models

NASA Technical Reports Server (NTRS)

Neelin, David; Zeng, N.; Suarez, M.; Koster, R.

2004-01-01

The project objective was to understand mechanisms by which atmosphere-land-ocean processes impact precipitation in the mean climate and interannual variations, focusing on tropical and subtropical regions. A combination of modeling tools was used: an intermediate complexity land-atmosphere model developed at UCLA known as the QTCM and the NASA Seasonal-to-Interannual Prediction Program general circulation model (NSIPP GCM). The intermediate complexity model was used to develop hypotheses regarding the physical mechanisms and theory for the interplay of large-scale dynamics, convective heating, cloud radiative effects and land surface feedbacks. The theoretical developments were to be confronted with diagnostics from the more complex GCM to validate or modify the theory.

The impact of climatic variations on the reproductive success of Gentiana lutea L. in a Mediterranean mountain area.

PubMed

Cuena-Lombraña, Alba; Fois, Mauro; Fenu, Giuseppe; Cogoni, Donatella; Bacchetta, Gianluigi

2018-03-30

Increases in temperature have been predicted and reported for the Mediterranean mountain ranges due to global warming and this phenomenon is expected to have profound consequences on biodiversity and ecosystem functioning. We hereby present the case of Gentiana lutea L. subsp. lutea, a rhizomatous long-lived plant living in Central-Southern Europe, which is at the edge of its ecological and distributional range in Sardinia. Concretely, we analysed the reproductive success experienced during three phenological cycles (2013/2014, 2014/2015 and 2015/2016) in four representative populations, with particular attention to the phenological cycle of 2014/2015, which has been recorded as one of the warmest periods of the last decades. The Smirnov-Grubbs test was used to evaluate differences in temperature and precipitation regimes among historical data and the analysed years, while the Kruskal-Wallis followed by the Wilcoxon test was used to measure differences between anthesis and reproductive performances among cycles and populations. In addition, generalised linear models were carried out to check relationships between climate variables and reproductive performance. Significant differences among climate variables and analysed cycles were highlighted, especially for maximum and mean temperatures. Such variations determined a non-flowering stage in two of the four analysed populations in 2014/2015 and significant differences of further five reproductive traits among cycles. These results confirmed that in current unstable climatic conditions, which are particularly evident in seasonal climates, reproductive success can be a sensitive and easily observable indicator of climatic anomalies. Considering the importance of this issue and the ease and cost-effectiveness of reproductive success monitoring, we argue that research in this sense can be a supporting tool for the enhancement of future crucial targets such as biodiversity conservation and the mitigation of global warming effects.

Predicting Impacts of Increased CO2 and Climate Change on the Water Cycle and Water Quality in the Semiarid James River Basin of the Midwestern USA

USGS Publications Warehouse

Wu, Yiping; Liu, Shu-Guang; Gallant, Alisa L.

2012-01-01

Emissions of greenhouse gases and aerosols from human activities continue to alter the climate and likely will have significant impacts on the terrestrial hydrological cycle and water quality, especially in arid and semiarid regions. We applied an improved Soil and Water Assessment Tool (SWAT) to evaluate impacts of increased atmospheric CO2 concentration and potential climate change on the water cycle and nitrogen loads in the semiarid James River Basin (JRB) in the Midwestern United States. We assessed responses of water yield, soil water content, groundwater recharge, and nitrate nitrogen (NO3–N) load under hypothetical climate-sensitivity scenarios in terms of CO2, precipitation, and air temperature. We extended our predictions of the dynamics of these hydrological variables into the mid-21st century with downscaled climate projections integrated across output from six General Circulation Models. Our simulation results compared against the baseline period 1980 to 2009 suggest the JRB hydrological system is highly responsive to rising levels of CO2 concentration and potential climate change. Under our scenarios, substantial decrease in precipitation and increase in air temperature by the mid-21st century could result in significant reduction in water yield, soil water content, and groundwater recharge. Our model also estimated decreased NO3–N load to streams, which could be beneficial, but a concomitant increase in NO3–N concentration due to a decrease in streamflow likely would degrade stream water and threaten aquatic ecosystems. These results highlight possible risks of drought, water supply shortage, and water quality degradation in this basin.

Hydrological effects of the increased CO2 and climate change in the Upper Mississippi River Basin using a modified SWAT

USGS Publications Warehouse

Wu, Y.; Liu, S.; Abdul-Aziz, O. I.

2012-01-01

Increased atmospheric CO2 concentration and climate change may significantly impact the hydrological and meteorological processes of a watershed system. Quantifying and understanding hydrological responses to elevated ambient CO2 and climate change is, therefore, critical for formulating adaptive strategies for an appropriate management of water resources. In this study, the Soil and Water Assessment Tool (SWAT) model was applied to assess the effects of increased CO2 concentration and climate change in the Upper Mississippi River Basin (UMRB). The standard SWAT model was modified to represent more mechanistic vegetation type specific responses of stomatal conductance reduction and leaf area increase to elevated CO2 based on physiological studies. For estimating the historical impacts of increased CO2 in the recent past decades, the incremental (i.e., dynamic) rises of CO2 concentration at a monthly time-scale were also introduced into the model. Our study results indicated that about 1–4% of the streamflow in the UMRB during 1986 through 2008 could be attributed to the elevated CO2 concentration. In addition to evaluating a range of future climate sensitivity scenarios, the climate projections by four General Circulation Models (GCMs) under different greenhouse gas emission scenarios were used to predict the hydrological effects in the late twenty-first century (2071–2100). Our simulations demonstrated that the water yield would increase in spring and substantially decrease in summer, while soil moisture would rise in spring and decline in summer. Such an uneven distribution of water with higher variability compared to the baseline level (1961–1990) may cause an increased risk of both flooding and drought events in the basin.

Quantitative Holocene climatic reconstructions for the lower Yangtze region of China

NASA Astrophysics Data System (ADS)

Li, Jianyong; Dodson, John; Yan, Hong; Wang, Weiming; Innes, James B.; Zong, Yongqiang; Zhang, Xiaojian; Xu, Qinghai; Ni, Jian; Lu, Fengyan

2018-02-01

Quantitative proxy-based and high-resolution palaeoclimatic datasets are scarce for the lower reaches of the Yangtze River (LYR) basin. This region is in a transitional vegetation zone which is climatologically sensitive; and as a birthplace for prehistorical civilization in China, it is important to understand how palaeoclimatic dynamics played a role in affecting cultural development in the region. We present a pollen-based and regionally-averaged Holocene climatic twin-dataset for mean total annual precipitation (PANN) and mean annual temperature (TANN) covering the last 10,000 years for the LYR region. This is based on the technique of weighted averaging-partial least squares regression to establish robust calibration models for obtaining reliable climatic inferences. The pollen-based reconstructions generally show an early Holocene climatic optimum with both abundant monsoonal rainfall and warm thermal conditions, and a declining pattern of both PANN and TANN values in the middle to late Holocene. The main driving forces behind the Holocene climatic changes in the LYR area are likely summer solar insolation associated with tropical or subtropical macro-scale climatic circulations such as the Intertropical Convergence Zone (ITCZ), Western Pacific Subtropical High (WPSH), and El Niño/Southern Oscillation (ENSO). Regional multi-proxy comparisons indicate that the Holocene variations in precipitation and temperature for the LYR region display an in-phase relationship with other related proxy records from southern monsoonal China and the Indian monsoon-influenced regions, but are inconsistent with the Holocene moisture or temperature records from northern monsoonal China and the westerly-dominated region in northwestern China. Overall, our comprehensive palaeoclimatic dataset and models may be significant tools for understanding the Holocene Asian monsoonal evolution and for anticipating its future dynamics in eastern Asia.

The impact of climatic variations on the reproductive success of Gentiana lutea L. in a Mediterranean mountain area

NASA Astrophysics Data System (ADS)

Cuena-Lombraña, Alba; Fois, Mauro; Fenu, Giuseppe; Cogoni, Donatella; Bacchetta, Gianluigi

2018-03-01

Increases in temperature have been predicted and reported for the Mediterranean mountain ranges due to global warming and this phenomenon is expected to have profound consequences on biodiversity and ecosystem functioning. We hereby present the case of Gentiana lutea L. subsp. lutea, a rhizomatous long-lived plant living in Central-Southern Europe, which is at the edge of its ecological and distributional range in Sardinia. Concretely, we analysed the reproductive success experienced during three phenological cycles (2013/2014, 2014/2015 and 2015/2016) in four representative populations, with particular attention to the phenological cycle of 2014/2015, which has been recorded as one of the warmest periods of the last decades. The Smirnov-Grubbs test was used to evaluate differences in temperature and precipitation regimes among historical data and the analysed years, while the Kruskal-Wallis followed by the Wilcoxon test was used to measure differences between anthesis and reproductive performances among cycles and populations. In addition, generalised linear models were carried out to check relationships between climate variables and reproductive performance. Significant differences among climate variables and analysed cycles were highlighted, especially for maximum and mean temperatures. Such variations determined a non-flowering stage in two of the four analysed populations in 2014/2015 and significant differences of further five reproductive traits among cycles. These results confirmed that in current unstable climatic conditions, which are particularly evident in seasonal climates, reproductive success can be a sensitive and easily observable indicator of climatic anomalies. Considering the importance of this issue and the ease and cost-effectiveness of reproductive success monitoring, we argue that research in this sense can be a supporting tool for the enhancement of future crucial targets such as biodiversity conservation and the mitigation of global warming effects.

Predicting impacts of increased CO₂ and climate change on the water cycle and water quality in the semiarid James River Basin of the Midwestern USA.

PubMed

Wu, Yiping; Liu, Shuguang; Gallant, Alisa L

2012-07-15

Emissions of greenhouse gases and aerosols from human activities continue to alter the climate and likely will have significant impacts on the terrestrial hydrological cycle and water quality, especially in arid and semiarid regions. We applied an improved Soil and Water Assessment Tool (SWAT) to evaluate impacts of increased atmospheric CO(2) concentration and potential climate change on the water cycle and nitrogen loads in the semiarid James River Basin (JRB) in the Midwestern United States. We assessed responses of water yield, soil water content, groundwater recharge, and nitrate nitrogen (NO(3)-N) load under hypothetical climate-sensitivity scenarios in terms of CO(2), precipitation, and air temperature. We extended our predictions of the dynamics of these hydrological variables into the mid-21st century with downscaled climate projections integrated across output from six General Circulation Models. Our simulation results compared against the baseline period 1980 to 2009 suggest the JRB hydrological system is highly responsive to rising levels of CO(2) concentration and potential climate change. Under our scenarios, substantial decrease in precipitation and increase in air temperature by the mid-21st century could result in significant reduction in water yield, soil water content, and groundwater recharge. Our model also estimated decreased NO(3)-N load to streams, which could be beneficial, but a concomitant increase in NO(3)-N concentration due to a decrease in streamflow likely would degrade stream water and threaten aquatic ecosystems. These results highlight possible risks of drought, water supply shortage, and water quality degradation in this basin. Published by Elsevier B.V.

Climate change and vector-borne diseases: what are the implications for public health research and policy?

PubMed

Campbell-Lendrum, Diarmid; Manga, Lucien; Bagayoko, Magaran; Sommerfeld, Johannes

2015-04-05

Vector-borne diseases continue to contribute significantly to the global burden of disease, and cause epidemics that disrupt health security and cause wider socioeconomic impacts around the world. All are sensitive in different ways to weather and climate conditions, so that the ongoing trends of increasing temperature and more variable weather threaten to undermine recent global progress against these diseases. Here, we review the current state of the global public health effort to address this challenge, and outline related initiatives by the World Health Organization (WHO) and its partners. Much of the debate to date has centred on attribution of past changes in disease rates to climate change, and the use of scenario-based models to project future changes in risk for specific diseases. While these can give useful indications, the unavoidable uncertainty in such analyses, and contingency on other socioeconomic and public health determinants in the past or future, limit their utility as decision-support tools. For operational health agencies, the most pressing need is the strengthening of current disease control efforts to bring down current disease rates and manage short-term climate risks, which will, in turn, increase resilience to long-term climate change. The WHO and partner agencies are working through a range of programmes to (i) ensure political support and financial investment in preventive and curative interventions to bring down current disease burdens; (ii) promote a comprehensive approach to climate risk management; (iii) support applied research, through definition of global and regional research agendas, and targeted research initiatives on priority diseases and population groups. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

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.

Visualizing and communicating climate change using the ClimateWizard: decision support and education through web-based analysis and mapping

NASA Astrophysics Data System (ADS)

Girvetz, E. H.; Zganjar, C.; Raber, G. T.; Maurer, E. P.; Duffy, P.

2009-12-01

Virtually all fields of study and parts of society—from ecological science and nature conservation, to global development, multinational corporations, and government bodies—need to know how climate change has and may impact specific locations of interest. Our ability to respond to climate change depends on having convenient tools that make past and projected climate trends available to planners, managers, scientists and the general public, at scales ranging from global to local scales. Web-mapping applications provide an effective platform for communicating climate change impacts in specific geographic areas of interest to the public. Here, we present one such application, the ClimateWizard, that allows users to analyze, visualize and explore climate change maps for specific geographic areas of interest throughout the world (http://ClimateWizard.org). Built on Web 2.0 web-services (SOAP), Google Maps mash-up, and cloud computing technologies, the ClimateWizard analyzes large databases of climate information located on remote servers to create synthesized information and useful products tailored to geographic areas of interest (e.g. maps, graphs, tables, GIS layers). We demonstrate how the ClimateWizard can be used to assess projected changes to temperature and precipitation across all states in the contiguous United States and all countries of the world using statistically downscaled general circulation models from the CMIP3 dataset. We then go on to show how ClimateWizard can be used to analyze changes to other climate related variables, such as moisture stress and water production. Finally, we discuss how this tool can be adapted to develop a wide range of web-based tools that are targeted at informing specific audiences—from scientific research and natural resource management, to K-12 and higher education—about how climate change may affect different aspects of human and natural systems.

Using a new high resolution regional model for malaria that accounts for population density and surface hydrology to determine sensitivity of malaria risk to climate drivers

NASA Astrophysics Data System (ADS)

Tompkins, Adrian; Ermert, Volker; Di Giuseppe, Francesca

2013-04-01

In order to better address the role of population dynamics and surface hydrology in the assessment of malaria risk, a new dynamical disease model been developed at ICTP, known as VECTRI: VECtor borne disease community model of ICTP, TRIeste (VECTRI). The model accounts for the temperature impact on the larvae, parasite and adult vector populations. Local host population density affects the transmission intensity, and the model thus reproduces the differences between peri-urban and rural transmission noted in Africa. A new simple pond model framework represents surface hydrology. The model can be used on with spatial resolutions finer than 10km to resolve individual health districts and thus can be used as a planning tool. Results of the models representation of interannual variability and longer term projections of malaria transmission will be shown for Africa. These will show that the model represents the seasonality and spatial variations of malaria transmission well matching a wide range of survey data of parasite rate and entomological inoculation rate (EIR) from across West and East Africa taken in the period prior to large-scale interventions. The model is used to determine the sensitivity of malaria risk to climate variations, both in rainfall and temperature, and then its use in a prototype forecasting system coupled with ECMWF forecasts will be demonstrated.

Commonalities between Disaster and Climate Change Risks for Health: A Theoretical Framework.

PubMed

Banwell, Nicola; Rutherford, Shannon; Mackey, Brendan; Street, Roger; Chu, Cordia

2018-03-16

Disasters and climate change have significant implications for human health worldwide. Both climate change and the climate-sensitive hazards that result in disasters, are discussed in terms of direct and indirect impacts on health. A growing body of literature has argued for the need to link disaster risk reduction and climate change adaptation. However, there is limited articulation of the commonalities between these health impacts. Understanding the shared risk pathways is an important starting point for developing joint strategies for adapting to, and reducing, health risks. Therefore, this article discusses the common aspects of direct and indirect health risks of climate change and climate-sensitive disasters. Based on this discussion a theoretical framework is presented for understanding these commonalities. As such, this article hopes to extend the current health impact frameworks and provide a platform for further research exploring opportunities for linked adaptation and risk reduction strategies.

Commonalities between Disaster and Climate Change Risks for Health: A Theoretical Framework

PubMed Central

Banwell, Nicola; Rutherford, Shannon; Mackey, Brendan; Street, Roger; Chu, Cordia

2018-01-01

Disasters and climate change have significant implications for human health worldwide. Both climate change and the climate-sensitive hazards that result in disasters, are discussed in terms of direct and indirect impacts on health. A growing body of literature has argued for the need to link disaster risk reduction and climate change adaptation. However, there is limited articulation of the commonalities between these health impacts. Understanding the shared risk pathways is an important starting point for developing joint strategies for adapting to, and reducing, health risks. Therefore, this article discusses the common aspects of direct and indirect health risks of climate change and climate-sensitive disasters. Based on this discussion a theoretical framework is presented for understanding these commonalities. As such, this article hopes to extend the current health impact frameworks and provide a platform for further research exploring opportunities for linked adaptation and risk reduction strategies. PMID:29547592

Using Weather Types to Understand and Communicate Weather and Climate Impacts

NASA Astrophysics Data System (ADS)

Prein, A. F.; Hale, B.; Holland, G. J.; Bruyere, C. L.; Done, J.; Mearns, L.

2017-12-01

A common challenge in atmospheric research is the translation of scientific advancements and breakthroughs to decision relevant and actionable information. This challenge is central to the mission of NCAR's Capacity Center for Climate and Weather Extremes (C3WE, www.c3we.ucar.edu). C3WE advances our understanding of weather and climate impacts and integrates these advances with distributed information technology to create tools that promote a global culture of resilience to weather and climate extremes. Here we will present an interactive web-based tool that connects historic U.S. losses and fatalities from extreme weather and climate events to 12 large-scale weather types. Weather types are dominant weather situations such as winter high-pressure systems over the U.S. leading to very cold temperatures or summertime moist humid air masses over the central U.S. leading to severe thunderstorms. Each weather type has a specific fingerprint of economic losses and fatalities in a region that is quantified. Therefore, weather types enable a direct connection of observed or forecasted weather situation to loss of life and property. The presented tool allows the user to explore these connections, raise awareness of existing vulnerabilities, and build resilience to weather and climate extremes.

Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability.

PubMed

Cox, Peter M; Pearson, David; Booth, Ben B; Friedlingstein, Pierre; Huntingford, Chris; Jones, Chris D; Luke, Catherine M

2013-02-21

The release of carbon from tropical forests may exacerbate future climate change, but the magnitude of the effect in climate models remains uncertain. Coupled climate-carbon-cycle models generally agree that carbon storage on land will increase as a result of the simultaneous enhancement of plant photosynthesis and water use efficiency under higher atmospheric CO(2) concentrations, but will decrease owing to higher soil and plant respiration rates associated with warming temperatures. At present, the balance between these effects varies markedly among coupled climate-carbon-cycle models, leading to a range of 330 gigatonnes in the projected change in the amount of carbon stored on tropical land by 2100. Explanations for this large uncertainty include differences in the predicted change in rainfall in Amazonia and variations in the responses of alternative vegetation models to warming. Here we identify an emergent linear relationship, across an ensemble of models, between the sensitivity of tropical land carbon storage to warming and the sensitivity of the annual growth rate of atmospheric CO(2) to tropical temperature anomalies. Combined with contemporary observations of atmospheric CO(2) concentration and tropical temperature, this relationship provides a tight constraint on the sensitivity of tropical land carbon to climate change. We estimate that over tropical land from latitude 30° north to 30° south, warming alone will release 53 ± 17 gigatonnes of carbon per kelvin. Compared with the unconstrained ensemble of climate-carbon-cycle projections, this indicates a much lower risk of Amazon forest dieback under CO(2)-induced climate change if CO(2) fertilization effects are as large as suggested by current models. Our study, however, also implies greater certainty that carbon will be lost from tropical land if warming arises from reductions in aerosols or increases in other greenhouse gases.

Quantifying Tropical Glacier Mass Balance Sensitivity to Climate Change Through Regional-Scale Modeling and The Randolph Glacier Inventory

NASA Astrophysics Data System (ADS)

Malone, A.

2017-12-01

Quantifying mass balance sensitivity to climate change is essential for forecasting glacier evolution and deciphering climate signals embedded in archives of past glacier changes. Ideally, these quantifications result from decades of field measurement, remote sensing, and a hierarchy modeling approach, but in data-sparse regions, such as the Himalayas and tropical Andes, regional-scale modeling rooted in first principles provides a first-order picture. Previous regional-scaling modeling studies have applied a surface energy and mass balance approach in order to quantify equilibrium line altitude sensitivity to climate change. In this study, an expanded regional-scale surface energy and mass balance model is implemented to quantify glacier-wide mass balance sensitivity to climate change for tropical Andean glaciers. Data from the Randolph Glacier Inventory are incorporated, and additional physical processes are included, such as a dynamic albedo and cloud-dependent atmospheric emissivity. The model output agrees well with the limited mass balance records for tropical Andean glaciers. The dominant climate variables driving interannual mass balance variability differ depending on the climate setting. For wet tropical glaciers (annual precipitation >0.75 m y-1), temperature is the dominant climate variable. Different hypotheses for the processes linking wet tropical glacier mass balance variability to temperature are evaluated. The results support the hypothesis that glacier-wide mass balance on wet tropical glaciers is largely dominated by processes at the lowest elevation where temperature plays a leading role in energy exchanges. This research also highlights the transient nature of wet tropical glaciers - the vast majority of tropical glaciers and a vital regional water resource - in an anthropogenic warming world.

Climate and carbon-cycle response to astronomical forcing over the last 35 Ma.

NASA Astrophysics Data System (ADS)

De Vleeschouwer, D.; Palike, H.; Vahlenkamp, M.; Crucifix, M.

2017-12-01

On a million-year time scale, the characteristics of insolation forcing caused by cyclical variations in the astronomical parameters of the Earth remain stable. Nevertheless, Earth's climate responded very differently to this forcing during different parts of the Cenozoic. The recently-published ∂18Obenthic megasplice (De Vleeschouwer et al., 2017) allowed for a clear visualization of these changes in global climate response to astronomical forcing. However, many open questions remain regarding how carbon-cycle dynamics influence Earth's climate sensitivity to astronomical climate forcing. To provide insight into the interaction between the carbon cycle and astronomical insolation forcing, we built a benthic carbon isotope (∂13Cbenthic) megasplice for the last 35 Ma, employing the same technique used to build the ∂18Obenthic megasplice. The ∂13Cbenthic megasplice exhibits a strong imprint of the 405 and 100-kyr eccentricity cycles throughout the last 35 Ma. This is intriguing, as the oxygen isotope megasplice looses its eccentricity imprint after the mid-Miocene climatic transition (MMCT; see Fig. 1 in De Vleeschouwer et al., 2017). In other words, the carbon cycle responded completely differently to astronomical forcing, compared to global climate during the late Miocene. We visualize this difference in response by the application of a Gaussian process, which renders the dependence of one variable (here ∂18Obenthic or ∂13Cbenthic) in a multidimensional space (here precession, obliquity and eccentricity). Together, the ∂13Cbenthic and ∂18Obenthic megasplices thus provide a unique tool for paleoclimatology, allowing for the quantification and visualization of the changing paleoclimate and carbon-cycle response to astronomical forcing throughout geologic time. References De Vleeschouwer, D., Vahlenkamp, M., Crucifix, M., Pälike, H., 2017. Alternating Southern and Northern Hemisphere climate response to astronomical forcing during the past 35 m.y. Geology 45, 375-378.

Projected changes in distributions of Australian tropical savanna birds under climate change using three dispersal scenarios

PubMed Central

Reside, April E; VanDerWal, Jeremy; Kutt, Alex S

2012-01-01

Identifying the species most vulnerable to extinction as a result of climate change is a necessary first step in mitigating biodiversity decline. Species distribution modeling (SDM) is a commonly used tool to assess potential climate change impacts on distributions of species. We use SDMs to predict geographic ranges for 243 birds of Australian tropical savannas, and to project changes in species richness and ranges under a future climate scenario between 1990 and 2080. Realistic predictions require recognition of the variability in species capacity to track climatically suitable environments. Here we assess the effect of dispersal on model results by using three approaches: full dispersal, no dispersal and a partial-dispersal scenario permitting species to track climate change at a rate of 30 km per decade. As expected, the projected distributions and richness patterns are highly sensitive to the dispersal scenario. Projected future range sizes decreased for 66% of species if full dispersal was assumed, but for 89% of species when no dispersal was assumed. However, realistic future predictions should not assume a single dispersal scenario for all species and as such, we assigned each species to the most appropriate dispersal category based on individual mobility and habitat specificity; this permitted the best estimates of where species will be in the future. Under this “realistic” dispersal scenario, projected ranges sizes decreased for 67% of species but showed that migratory and tropical-endemic birds are predicted to benefit from climate change with increasing distributional area. Richness hotspots of tropical savanna birds are expected to move, increasing in southern savannas and southward along the east coast of Australia, but decreasing in the arid zone. Understanding the complexity of effects of climate change on species’ range sizes by incorporating dispersal capacities is a crucial step toward developing adaptation policies for the conservation of vulnerable species. PMID:22837819

Climate Risk Management and Decision Support Tools for the Agriculture Sector in Lao PDR, Bangladesh, and Indonesia

NASA Astrophysics Data System (ADS)

Allis, E. C.; Greene, A. M.; Cousin, R.

2014-12-01

We describe a comprehensive project for developing climate information and decision support / climate risk management tools in Lao PDR, Bangladesh and Indonesia. Mechanisms are developed for bringing the benefits of these tools to both policy makers and poor rural farmers, with the goal of enabling better management, at the farm level, of the risks associated with climate variability and change. The project comprises several interwoven threads, differentially applied in the different study regions. These include data management and quality control, development of seasonal forecast capabilities, use of dynamic cropping calendars and climate advisories, the development of longer-term climate information for both past and future and a weather index insurance component. Stakeholder engagement and capacity building served as reinforcing and complementary elements to all components. In this talk we will provide a project overview, show how the various components fit together and describe some lessons learned in this attempt to promote the uptake of actionable climate information from farmer to policy level. The applied research project was led by the International Research Institute for Climate and Society (IRI) at Columbia University with funding from the International Fund for Agriculture Development (IFAD) and in close collaboration with our regional partners at the Centre for Climate Risk and Opportunity Management in Southeast Asia Pacific (at Bogor Agricultural University in Indonesia), Indonesia's National Agency for Meteorology, Climatology and Geophysics (BMKG), Lao PDR's National Agriculture and Forestry Research Institute (NAFRI), Laotian Department of Meteorology and Hydrology (DMH), WorldFish Center, Bangladesh Meteorology Department (BMD), and CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).

Health-sector responses to address the impacts of climate change in Nepal.

PubMed

Dhimal, Meghnath; Dhimal, Mandira Lamichhane; Pote-Shrestha, Raja Ram; Groneberg, David A; Kuch, Ulrich

2017-09-01

Nepal is highly vulnerable to global climate change, despite its negligible emission of global greenhouse gases. The vulnerable climate-sensitive sectors identified in Nepal's National Adaptation Programme of Action (NAPA) to Climate Change 2010 include agriculture, forestry, water, energy, public health, urbanization and infrastructure, and climate-induced disasters. In addition, analyses carried out as part of the NAPA process have indicated that the impacts of climate change in Nepal are not gender neutral. Vector-borne diseases, diarrhoeal diseases including cholera, malnutrition, cardiorespiratory diseases, psychological stress, and health effects and injuries related to extreme weather are major climate-sensitive health risks in the country. In recent years, research has been done in Nepal in order to understand the changing epidemiology of diseases and generate evidence for decision-making. Based on this evidence, the experience of programme managers, and regular surveillance data, the Government of Nepal has mainstreamed issues related to climate change in development plans, policies and programmes. In particular, the Government of Nepal has addressed climate-sensitive health risks. In addition to the NAPA report, several policy documents have been launched, including the Climate Change Policy 2011; the Nepal Health Sector Programme - Implementation Plan II (NHSP-IP 2) 2010-2015; the National Health Policy 2014; the National Health Sector Strategy 2015-2020 and its implementation plan (2016-2021); and the Health National Adaptation Plan (H-NAP): climate change and health strategy and action plan (2016-2020). However, the translation of these policies and plans of action into tangible action on the ground is still in its infancy in Nepal. Despite this, the health sector's response to addressing the impact of climate change in Nepal may be taken as a good example for other low- and middle-income countries.

A climate sensitive model of carbon transfer through atmosphere, vegetation and soil in managed forest ecosystems

NASA Astrophysics Data System (ADS)

Loustau, D.; Moreaux, V.; Bosc, A.; Trichet, P.; Kumari, J.; Rabemanantsoa, T.; Balesdent, J.; Jolivet, C.; Medlyn, B. E.; Cavaignac, S.; Nguyen-The, N.

2012-12-01

For predicting the future of the forest carbon cycle in forest ecosystems, it is necessary to account for both the climate and management impacts. Climate effects are significant not only at a short time scale but also at the temporal horizon of a forest life cycle e.g. through shift in atmospheric CO2 concentration, temperature and precipitation regimes induced by the enhanced greenhouse effect. Intensification of forest management concerns an increasing fraction of temperate and tropical forests and untouched forests represents only one third of the present forest area. Predicting tools are therefore needed to project climate and management impacts over the forest life cycle and understand the consequence of management on the forest ecosystem carbon cycle. This communication summarizes the structure, main components and properties of a carbon transfer model that describes the processes controlling the carbon cycle of managed forest ecosystems. The model, GO+, links three main components, (i) a module describing the vegetation-atmosphere mass and energy exchanges in 3D, (ii) a plant growth module and a (iii) soil carbon dynamics module in a consistent carbon scheme of transfer from atmosphere back into the atmosphere. It was calibrated and evaluated using observed data collected on coniferous and broadleaved forest stands. The model predicts the soil, water and energy balance of entire rotations of managed stands from the plantation to the final cut and according to a range of management alternatives. It accounts for the main soil and vegetation management operations such as soil preparation, understorey removal, thinnings and clearcutting. Including the available knowledge on the climatic sensitivity of biophysical and biogeochemical processes involved in atmospheric exchanges and carbon cycle of forest ecosystems, GO+ can produce long-term backward or forward simulations of forest carbon and water cycles under a range of climate and management scenarios. This model applications to the prediction and analysis of climate scenarios impacts on southwestern European forests underlines the role of management alternatives, precipitation regime, CO2 concentration and atmospheric humidity .Frequency of soil preparation operations and understorey management play a major role in controlling the net carbon flux into the atmosphere at the juvenile stage ( 0 to 10 y-old) whereas climate and rotation duration control the functioning of adult phase. The model predicts that a drier and warmer climate will reduce the forest productivity and deplete soil and carbon stocks in managed forest from Southwestern Europe within decades, such effects being amplified for most intensive management alternatives. This work was part of the European research project GHG-Europe (EU contract No. 244122) and the French national project FAST co-funded by the Ecology, Agriculture and Forestry Ministries and the Region Aquitaine.

Tools for enhancing motivation in teaching climate change and impacts for students in forest- and environmental engineering

NASA Astrophysics Data System (ADS)

Gálos, Borbála

2017-04-01

Climate change is observed to have severe impacts on forest ecosystems. Ongoing research projects are dealing with the complex analysis of the causes of the health status decline and mortality of the vulnerable tree species. In the Carpathian Basin, recurrent long lasting drought periods and heatwaves of the last decades initiated the sequence of abiotic and biotic impacts in the beech and oak forests. Threatening extreme events are very likely to occur more frequent under changing climate conditions until the end of the 21st century. Therefore adaptation strategies and renewed regulations of the tree species selection are necessary. Learning material of forest education needs to be continuously updated with the new aspects and results of recent research and forest management planning. Therefore ideas and tools have been developed for teaching climate change impacts for students in forest- and environmental engineering. Using examples from world sport championships (e.g. losers and winners of climate change) these tools are applied to communicate the basic research questions in an easily understandable way as well as to motivate students and raise their awareness for the complex processes of forest - climate interactions. By the application of the developed examples for motivation, the key competences and learning outcomes can be the following: • students get an insight into the observed and projected tendencies of climate extremes; • they get an impression on the complexity of the climate change related damage chains; • they will be able to identify the climatic drivers of forest decline and mortality; • with the skill of critical thinking they will be able to evaluate the ecological role of forests that are already affected and that could be affected by the consequences of changing climate conditions; • they recognize the importance and urgency of the appropriate decisions in forestry and nature conservation. Keywords: climate change impacts, forest education, teaching tools for motivation The research is supported by the ÚNKP-16-4-3 New National Excellence Program of the Ministry of Human Capacities.

Temperature and rainfall strongly drive temporal growth variation in Asian tropical forest trees.

PubMed

Vlam, Mart; Baker, Patrick J; Bunyavejchewin, Sarayudh; Zuidema, Pieter A

2014-04-01

Climate change effects on growth rates of tropical trees may lead to alterations in carbon cycling of carbon-rich tropical forests. However, climate sensitivity of broad-leaved lowland tropical trees is poorly understood. Dendrochronology (tree-ring analysis) provides a powerful tool to study the relationship between tropical tree growth and annual climate variability. We aimed to establish climate-growth relationships for five annual-ring forming tree species, using ring-width data from 459 canopy and understory trees from a seasonal tropical forest in western Thailand. Based on 183/459 trees, chronologies with total lengths between 29 and 62 years were produced for four out of five species. Bootstrapped correlation analysis revealed that climate-growth responses were similar among these four species. Growth was significantly negatively correlated with current-year maximum and minimum temperatures, and positively correlated with dry-season precipitation levels. Negative correlations between growth and temperature may be attributed to a positive relationship between temperature and autotrophic respiration rates. The positive relationship between growth and dry-season precipitation levels likely reflects the strong water demand during leaf flush. Mixed-effect models yielded results that were consistent across species: a negative effect of current wet-season maximum temperatures on growth, but also additive positive effects of, for example, prior dry-season maximum temperatures. Our analyses showed that annual growth variability in tropical trees is determined by a combination of both temperature and precipitation variability. With rising temperature, the predominantly negative relationship between temperature and growth may imply decreasing growth rates of tropical trees as a result of global warming.

Ecosystems Vulnerability Challenge and Prize Competition

NASA Astrophysics Data System (ADS)

Smith, J. H.; Frame, M. T.; Ferriter, O.; Recker, J.

2014-12-01

Stimulating innovation and private sector entrepreneurship is an important way to advance the preparedness of communities, businesses and individuals for the impacts of climate change on certain aspects of ecosystems, such as: fire regimes; water availability; carbon sequestration; biodiversity conservation; weather-related hazards, and the spread of invasive species. The creation of tools is critical to help communities and natural resource managers better understand the impacts of climate change on ecosystems and the potential resulting implications for ecosystem services and conservation efforts. The Department of the Interior is leading an interagency effort to develop the Ecosystems Vulnerability theme as part of the President's Climate Action Plan. This effort will provide seamless access to relevant datasets that can help address such issues as: risk of wildfires to local communities and federal lands; water sensitivity to climate change; and understanding the role of ecosystems in a changing climate. This session will provide an overview of the proposed Ecosystem Vulnerability Challenge and Prize Competition, outlining the intended audience, scope, goals, and overall timeline. The session will provide an opportunity for participants to offer new ideas. Through the Challenge, access will be made available to critical datasets for software developers, engineers, scientists, students, and researchers to develop and submit applications addressing critical science issues facing our Nation today. Application submission criteria and guidelines will also be discussed. The Challenge will be open to all sectors and organizations (i.e. federal, non-federal, private sector, non-profits, and universities) within the United States. It is anticipated the Challenge will run from early January 2015 until spring of 2015.

The theory, direction, and magnitude of ecosystem fire probability as constrained by precipitation and temperature.

PubMed

Guyette, Richard; Stambaugh, Michael C; Dey, Daniel; Muzika, Rose Marie

2017-01-01

The effects of climate on wildland fire confronts society across a range of different ecosystems. Water and temperature affect the combustion dynamics, irrespective of whether those are associated with carbon fueled motors or ecosystems, but through different chemical, physical, and biological processes. We use an ecosystem combustion equation developed with the physical chemistry of atmospheric variables to estimate and simulate fire probability and mean fire interval (MFI). The calibration of ecosystem fire probability with basic combustion chemistry and physics offers a quantitative method to address wildland fire in addition to the well-studied forcing factors such as topography, ignition, and vegetation. We develop a graphic analysis tool for estimating climate forced fire probability with temperature and precipitation based on an empirical assessment of combustion theory and fire prediction in ecosystems. Climate-affected fire probability for any period, past or future, is estimated with given temperature and precipitation. A graphic analyses of wildland fire dynamics driven by climate supports a dialectic in hydrologic processes that affect ecosystem combustion: 1) the water needed by plants to produce carbon bonds (fuel) and 2) the inhibition of successful reactant collisions by water molecules (humidity and fuel moisture). These two postulates enable a classification scheme for ecosystems into three or more climate categories using their position relative to change points defined by precipitation in combustion dynamics equations. Three classifications of combustion dynamics in ecosystems fire probability include: 1) precipitation insensitive, 2) precipitation unstable, and 3) precipitation sensitive. All three classifications interact in different ways with variable levels of temperature.

Alpine biodiversity and assisted migration: The case of the American pika (Ochotona princeps)

USGS Publications Warehouse

Wilkening, Jennifer L.; Ray, Chris; Ramsay, Nathan G.; Klingler, Kelly

2015-01-01

Alpine mammals are predicted to be among the species most threatened by climate change, due to the projected loss and further fragmentation of alpine habitats. As temperature or precipitation regimes change, alpine mammals may also be faced with insurmountable barriers to dispersal. The slow rate or inability to adjust to rapidly shifting environmental conditions may cause isolated alpine species to become locally extirpated, resulting in reduced biodiversity. One proposed method for mitigating the impacts of alpine species loss is assisted migration. This method, which involves translocating a species to an area with more favourable climate and habitat characteristics, has become the subject of debate and controversy in the conservation community. The uncertainty associated with climate change projections, coupled with the thermal sensitivity of many alpine mammals, makes it difficult to a priori assess the efficacy of this technique as a conservation management tool. Here we present the American pika (Ochotona princeps) as a case study. American pikas inhabit rocky areas throughout the western US, and populations in some mountainous areas have become locally extirpated in recent years. We review known climatic and habitat requirements for this species, and also propose protocols designed to reliably identify favourable relocation areas. We present data related to the physiological constraints of this species and outline specific requirements which must be addressed for translocation of viable populations, including wildlife disease and genetic considerations. Finally, we discuss potential impacts on other alpine species and alpine communities, and overall implications for conserving alpine biodiversity in a changing climate.

Estimating thermal regimes of bull trout and assessing the potential effects of climate warming on critical habitats

USGS Publications Warehouse

Jones, Leslie A.; Muhlfeld, Clint C.; Marshall, Lucy A.; McGlynn, Brian L.; Kershner, Jeffrey L.

2013-01-01

Understanding the vulnerability of aquatic species and habitats under climate change is critical for conservation and management of freshwater systems. Climate warming is predicted to increase water temperatures in freshwater ecosystems worldwide, yet few studies have developed spatially explicit modelling tools for understanding the potential impacts. We parameterized a nonspatial model, a spatial flow-routed model, and a spatial hierarchical model to predict August stream temperatures (22-m resolution) throughout the Flathead River Basin, USA and Canada. Model comparisons showed that the spatial models performed significantly better than the nonspatial model, explaining the spatial autocorrelation found between sites. The spatial hierarchical model explained 82% of the variation in summer mean (August) stream temperatures and was used to estimate thermal regimes for threatened bull trout (Salvelinus confluentus) habitats, one of the most thermally sensitive coldwater species in western North America. The model estimated summer thermal regimes of spawning and rearing habitats at <13 C° and foraging, migrating, and overwintering habitats at <14 C°. To illustrate the useful application of such a model, we simulated climate warming scenarios to quantify potential loss of critical habitats under forecasted climatic conditions. As air and water temperatures continue to increase, our model simulations show that lower portions of the Flathead River Basin drainage (foraging, migrating, and overwintering habitat) may become thermally unsuitable and headwater streams (spawning and rearing) may become isolated because of increasing thermal fragmentation during summer. Model results can be used to focus conservation and management efforts on populations of concern, by identifying critical habitats and assessing thermal changes at a local scale.

Climate change-related temperature impacts on warm season heat mortality: a proof-of-concept methodology using BenMAP.

PubMed

Voorhees, A Scott; Fann, Neal; Fulcher, Charles; Dolwick, Patrick; Hubbell, Bryan; Bierwagen, Britta; Morefield, Philip

2011-02-15

Climate change is anticipated to raise overall temperatures and is likely to increase heat-related human health morbidity and mortality risks. The objective of this work was to develop a proof-of-concept approach for estimating excess heat-related premature deaths in the continental United States resulting from potential changes in future temperature using the BenMAP model. In this approach we adapt the methods and tools that the US Environmental Protection Agency uses to assess air pollution health impacts by incorporating temperature modeling and heat mortality health impact functions. This new method demonstrates the ability to apply the existing temperature-health literature to quantify prospective changes in climate-sensitive heat-related mortality. We compared estimates of future temperature with and without climate change and applied heat-mortality health functions to estimate relative changes in heat-related premature mortality. Using the A1B emissions scenario, we applied the GISS-II global circulation model downscaled to 36-km using MM5 and formatted using the Meteorology-Chemistry Interface Processor. For averaged temperatures derived from the 5 years 2048-2052 relative to 1999-2003 we estimated for the warm season May-September a national U.S. estimate of annual incidence of heat-related mortality to be 3700-3800 from all causes, 3500 from cardiovascular disease, and 21 000-27 000 from nonaccidental death, applying various health impact functions. Our estimates of mortality, produced to validate the application of a new methodology, suggest the importance of quantifying heat impacts in economic assessments of climate change.

A modelling study of long term green roof retention performance.

PubMed

Stovin, Virginia; Poë, Simon; Berretta, Christian

2013-12-15

This paper outlines the development of a conceptual hydrological flux model for the long term continuous simulation of runoff and drought risk for green roof systems. A green roof's retention capacity depends upon its physical configuration, but it is also strongly influenced by local climatic controls, including the rainfall characteristics and the restoration of retention capacity associated with evapotranspiration during dry weather periods. The model includes a function that links evapotranspiration rates to substrate moisture content, and is validated against observed runoff data. The model's application to typical extensive green roof configurations is demonstrated with reference to four UK locations characterised by contrasting climatic regimes, using 30-year rainfall time-series inputs at hourly simulation time steps. It is shown that retention performance is dependent upon local climatic conditions. Volumetric retention ranges from 0.19 (cool, wet climate) to 0.59 (warm, dry climate). Per event retention is also considered, and it is demonstrated that retention performance decreases significantly when high return period events are considered in isolation. For example, in Sheffield the median per-event retention is 1.00 (many small events), but the median retention for events exceeding a 1 in 1 yr return period threshold is only 0.10. The simulation tool also provides useful information about the likelihood of drought periods, for which irrigation may be required. A sensitivity study suggests that green roofs with reduced moisture-holding capacity and/or low evapotranspiration rates will tend to offer reduced levels of retention, whilst high moisture-holding capacity and low evapotranspiration rates offer the strongest drought resistance. Copyright © 2013 Elsevier Ltd. All rights reserved.

The theory, direction, and magnitude of ecosystem fire probability as constrained by precipitation and temperature

PubMed Central

Guyette, Richard; Stambaugh, Michael C.; Dey, Daniel

2017-01-01

The effects of climate on wildland fire confronts society across a range of different ecosystems. Water and temperature affect the combustion dynamics, irrespective of whether those are associated with carbon fueled motors or ecosystems, but through different chemical, physical, and biological processes. We use an ecosystem combustion equation developed with the physical chemistry of atmospheric variables to estimate and simulate fire probability and mean fire interval (MFI). The calibration of ecosystem fire probability with basic combustion chemistry and physics offers a quantitative method to address wildland fire in addition to the well-studied forcing factors such as topography, ignition, and vegetation. We develop a graphic analysis tool for estimating climate forced fire probability with temperature and precipitation based on an empirical assessment of combustion theory and fire prediction in ecosystems. Climate-affected fire probability for any period, past or future, is estimated with given temperature and precipitation. A graphic analyses of wildland fire dynamics driven by climate supports a dialectic in hydrologic processes that affect ecosystem combustion: 1) the water needed by plants to produce carbon bonds (fuel) and 2) the inhibition of successful reactant collisions by water molecules (humidity and fuel moisture). These two postulates enable a classification scheme for ecosystems into three or more climate categories using their position relative to change points defined by precipitation in combustion dynamics equations. Three classifications of combustion dynamics in ecosystems fire probability include: 1) precipitation insensitive, 2) precipitation unstable, and 3) precipitation sensitive. All three classifications interact in different ways with variable levels of temperature. PMID:28704457

Useful to Usable (U2U): Transforming Climate Variability and Change Information for Cereal Crop Producers

NASA Astrophysics Data System (ADS)

Niyogi, D.; Andresen, J.

2011-12-01

Corn and soybean production contributes over $100 billion annually to the U.S. economy, most of which comes from the intensely cultivated corn-belt region of the Midwest. Successful crop production in this region is highly dependent on favorable temperatures and appropriate precipitation patters, making this industry vulnerable to changes in climate patterns. Though predictive models are constantly improving, there are gaps in our understanding of how different management practices can be used to help farmers adapt to changes in climate while maintaining economic viability. Furthermore, currently available tools and models are not meeting producers' needs, and little is known about the types of information they would like to access. Useful to Usable (U2U): Transforming Climate Variability and Change Information for Cereal Crop Producers is an integrated research and extension project that seeks to improve the resilience and profitability of farms in the North Central Region amid variable climate change through the development and dissemination of improved decision support tools, resource materials, and training. The goal is to work closely with producers to help them make better long-term plans on what, when and where to plant, and also how to manage crops for maximum yields and minimum environmental damage. The U2U team is composed of a uniquely qualified group of climatologists, crop modelers, agronomists, economists, and social scientists from 10 partner universities across the Midwest. Over the span of 5 years, collaborators will complete tasks associated with 5 objectives that will enhance the usability of climate information for the agricultural community and lead to more sustainable farming operations. First the team will produce research on the biophysical and economic impacts of different climate scenarios on corn and soybean yields in the North Central Region (objective 1) and conduct complementary research to understand how producers and advisors are likely to use this information (objective 2). Based on these findings, decision support tools (DSTs) and training materials will be developed to effectively deliver climate information to stakeholders (objective 3). Next, DSTs will be piloted in a four-state region (Indiana, Iowa, Nebraska, and Michigan) to help improve tools and evaluate effectiveness (objective 4). After several iterations with stakeholders to ensure the usability and utility of the tools, the program will be extended to all twelve states in the region (objective 5). Decision support tools, along with training products, surveys, feedback mechanisms and collaborative social tools, will be supported using the NSF-funded and Purdue University developed HUBzero web-based technology.

A web-tool to find spatially explicit climate-smart solutions for the sector agriculture

NASA Astrophysics Data System (ADS)

Verzandvoort, Simone; Kuikman, Peter; Walvoort, Dennis

2017-04-01

Europe faces the challenge to produce more food and more biomass for the bio-economy, to adapt its agricultural sector to negative consequences of climate change, and to reduce greenhouse gas emissions from agriculture. Climate-smart agriculture (CSA) solutions and technologies improve agriculture's productivity and provide economic growth and stability, increase resilience, and help to reduce GHG emissions from agricultural activities. The Climate Smart Agriculture Booster (CSAb) (http://csabooster.climate-kic.org/) is a Flagship Program under Climate-KIC, aiming to facilitate the adoption of CSA solutions and technologies in the European agro-food sector. This adoption requires spatially explicit, contextual information on farming activities and risks and opportunities related to climate change in regions across Europe. Other spatial information supporting adoption includes Information on where successful implementations were already done, on where CSA would profit from enabling policy conditions, and where markets or business opportunities for selling or purchasing technology and knowledge are located or emerging. The Spatial Solution Finder is a web-based spatial tool aiming to help agri-food companies (supply and processing), authorities or agricultural organisations find CSA solutions and technologies that fit local farmers and regions, and to demonstrate examples of successful implementations as well as expected impact at the farm and regional level. The tool is based on state of the art (geo)datasets of environmental and socio-economic conditions (partly open access, partly derived from previous research) and open source web-technology. The philosophy of the tool is that combining existing datasets with contextual information on the region of interest with personalized information entered by the user provides a suitable basis for offering a basket of options for CSA solutions and technologies. Solutions and technologies are recommended to the user based on similarity matrices assigning scores based on criteria relating to the technology (applicability, benefits, costs) and set by the user. The tool is being developed as part of the CSA Booster Flagship Programme in 2017. The design enables embedding the tool in the Open Innovation Platform of the CSAb and in other European platforms, communities and market places on the Internet related to natural capital and innovations. Continuous updating with new functionality and additional datasets during its lifetime is possible and secures that the tool remains up to date.

A New Tool for Climatic Analysis Using the Koppen Climate Classification

ERIC Educational Resources Information Center

Larson, Paul R.; Lohrengel, C. Frederick, II

2011-01-01

The purpose of climate classification is to help make order of the seemingly endless spatial distribution of climates. The Koppen classification system in a modified format is the most widely applied system in use today. This system may not be the best nor most complete climate classification that can be conceived, but it has gained widespread…

Extreme Events and Energy Providers: Science and Innovation

NASA Astrophysics Data System (ADS)

Yiou, P.; Vautard, R.

2012-04-01

Most socio-economic regulations related to the resilience to climate extremes, from infrastructure or network design to insurance premiums, are based on a present-day climate with an assumption of stationarity. Climate extremes (heat waves, cold spells, droughts, storms and wind stilling) affect in particular energy production, supply, demand and security in several ways. While national, European or international projects have generated vast amounts of climate projections for the 21st century, their practical use in long-term planning remains limited. Estimating probabilistic diagnostics of energy user relevant variables from those multi-model projections will help the energy sector to elaborate medium to long-term plans, and will allow the assessment of climate risks associated to those plans. The project "Extreme Events for Energy Providers" (E3P) aims at filling a gap between climate science and its practical use in the energy sector and creating in turn favourable conditions for new business opportunities. The value chain ranges from addressing research questions directly related to energy-significant climate extremes to providing innovative tools of information and decision making (including methodologies, best practices and software) and climate science training for the energy sector, with a focus on extreme events. Those tools will integrate the scientific knowledge that is developed by scientific communities, and translate it into a usable probabilistic framework. The project will deliver projection tools assessing the probabilities of future energy-relevant climate extremes at a range of spatial scales varying from pan-European to local scales. The E3P project is funded by the Knowledge and Innovation Community (KIC Climate). We will present the mechanisms of interactions between academic partners, SMEs and industrial partners for this project. Those mechanisms are elementary bricks of a climate service.

Cal-Adapt: California's Climate Data Resource and Interactive Toolkit

NASA Astrophysics Data System (ADS)

Thomas, N.; Mukhtyar, S.; Wilhelm, S.; Galey, B.; Lehmer, E.

2016-12-01

Cal-Adapt is a web-based application that provides an interactive toolkit and information clearinghouse to help agencies, communities, local planners, resource managers, and the public understand climate change risks and impacts at the local level. The website offers interactive, visually compelling, and useful data visualization tools that show how climate change might affect California using downscaled continental climate data. Cal-Adapt is supporting California's Fourth Climate Change Assessment through providing access to the wealth of modeled and observed data and adaption-related information produced by California's scientific community. The site has been developed by UC Berkeley's Geospatial Innovation Facility (GIF) in collaboration with the California Energy Commission's (CEC) Research Program. The Cal-Adapt website allows decision makers, scientists and residents of California to turn research results and climate projections into effective adaptation decisions and policies. Since its release to the public in June 2011, Cal-Adapt has been visited by more than 94,000 unique visitors from over 180 countries, all 50 U.S. states, and 689 California localities. We will present several key visualizations that have been employed by Cal-Adapt's users to support their efforts to understand local impacts of climate change, indicate the breadth of data available, and delineate specific use cases. Recently, CEC and GIF have been developing and releasing Cal-Adapt 2.0, which includes updates and enhancements that are increasing its ease of use, information value, visualization tools, and data accessibility. We showcase how Cal-Adapt is evolving in response to feedback from a variety of sources to present finer-resolution downscaled data, and offer an open API that allows other organization to access Cal-Adapt climate data and build domain specific visualization and planning tools. Through a combination of locally relevant information, visualization tools, and access to primary data, Cal-Adapt allows users to investigate how the climate is projected to change in their areas of interest.

Shrub growth response to climate across the North Slope of Alaska

NASA Astrophysics Data System (ADS)

Ackerman, D.; Griffin, D.; Finlay, J. C.; Hobbie, S. E.

2016-12-01

Warmer temperatures at high latitudes are driving the expansion of woody shrubs in arctic tundra, yielding feedbacks to regional carbon cycling. Accounting for these feedbacks in global climate models will require accurate predictions of the spatial extent of shrub expansion within arctic tundra. While dendroecological approaches have proven useful in understanding how shrubs respond to climate, empirical studies to date are limited in spatial extent, often to just one or two sites within a landscape. A recent meta-analysis of such dendroecological studies hypothesizes that soil moisture is a key variable in determining climate sensitivity of arctic shrub growth. We present the first regional-scale empirical test of this hypothesis by analyzing inter-annual radial growth of deciduous shrubs across soil moisture gradients throughout the North Slope of Alaska. Contrary to expectation, riparian shrubs in high-moisture environments showed no climate sensitivity, while shrubs growing in drier upland sites showed a strong positive growth response to summer temperature. These results proved robust to a variety of detrending functions ranging from conservative (negative exponential) to data adaptive (20-year cubic smoothing spline). These findings call into question the role of soil moisture in determining the climate sensitivity of arctic shrubs and further highlight the importance of unified, regional-scale sampling strategies in understanding climate-vegetation links.

Climate simulations and projections with a super-parameterized climate model

DOE PAGES

Stan, Cristiana; Xu, Li

2014-07-01

The mean climate and its variability are analyzed in a suite of numerical experiments with a fully coupled general circulation model in which subgrid-scale moist convection is explicitly represented through embedded 2D cloud-system resolving models. Control simulations forced by the present day, fixed atmospheric carbon dioxide concentration are conducted using two horizontal resolutions and validated against observations and reanalyses. The mean state simulated by the higher resolution configuration has smaller biases. Climate variability also shows some sensitivity to resolution but not as uniform as in the case of mean state. The interannual and seasonal variability are better represented in themore » simulation at lower resolution whereas the subseasonal variability is more accurate in the higher resolution simulation. The equilibrium climate sensitivity of the model is estimated from a simulation forced by an abrupt quadrupling of the atmospheric carbon dioxide concentration. The equilibrium climate sensitivity temperature of the model is 2.77 °C, and this value is slightly smaller than the mean value (3.37 °C) of contemporary models using conventional representation of cloud processes. As a result, the climate change simulation forced by the representative concentration pathway 8.5 scenario projects an increase in the frequency of severe droughts over most of the North America.« less

The effects of ground hydrology on climate sensitivity to solar constant variations

NASA Technical Reports Server (NTRS)

Chou, S. H.; Curran, R. J.; Ohring, G.

1979-01-01

The effects of two different evaporation parameterizations on the climate sensitivity to solar constant variations are investigated by using a zonally averaged climate model. The model is based on a two-level quasi-geostrophic zonally averaged annual mean model. One of the evaporation parameterizations tested is a nonlinear formulation with the Bowen ratio determined by the predicted vertical temperature and humidity gradients near the earth's surface. The other is the linear formulation with the Bowen ratio essentially determined by the prescribed linear coefficient.