International Land Model Benchmarking (ILAMB) Workshop Report, Technical Report DOE/SC-0186

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

Hoffman, Forrest M.; Koven, Charles D.; Kappel-Aleks, Gretchen

2016-11-01

As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

A new paradigm for predicting zonal-mean climate and climate change

NASA Astrophysics Data System (ADS)

Armour, K.; Roe, G.; Donohoe, A.; Siler, N.; Markle, B. R.; Liu, X.; Feldl, N.; Battisti, D. S.; Frierson, D. M.

2016-12-01

How will the pole-to-equator temperature gradient, or large-scale patterns of precipitation, change under global warming? Answering such questions typically involves numerical simulations with comprehensive general circulation models (GCMs) that represent the complexities of climate forcing, radiative feedbacks, and atmosphere and ocean dynamics. Yet, our understanding of these predictions hinges on our ability to explain them through the lens of simple models and physical theories. Here we present evidence that zonal-mean climate, and its changes, can be understood in terms of a moist energy balance model that represents atmospheric heat transport as a simple diffusion of latent and sensible heat (as a down-gradient transport of moist static energy, with a diffusivity coefficient that is nearly constant with latitude). We show that the theoretical underpinnings of this model derive from the principle of maximum entropy production; that its predictions are empirically supported by atmospheric reanalyses; and that it successfully predicts the behavior of a hierarchy of climate models - from a gray radiation aquaplanet moist GCM, to comprehensive GCMs participating in CMIP5. As an example of the power of this paradigm, we show that, given only patterns of local radiative feedbacks and climate forcing, the moist energy balance model accurately predicts the evolution of zonal-mean temperature and atmospheric heat transport as simulated by the CMIP5 ensemble. These results suggest that, despite all of its dynamical complexity, the atmosphere essentially responds to energy imbalances by simply diffusing latent and sensible heat down-gradient; this principle appears to explain zonal-mean climate and its changes under global warming.

A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

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

Fedorov, Alexey V.

2015-01-14

The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth systemmore » models, to the stability and variability of the AMOC in past climates.« less

Continuous Evaluation of Fast Processes in Climate Models Using ARM Measurements

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

Li, Zhijin; Sha, Feng; Liu, Yangang

2016-02-02

This five-year award supports the project “Continuous Evaluation of Fast Processes in Climate Models Using ARM Measurements (FASTER)”. The goal of this project is to produce accurate, consistent and comprehensive data sets for initializing both single column models (SCMs) and cloud resolving models (CRMs) using data assimilation. A multi-scale three-dimensional variational data assimilation scheme (MS-3DVAR) has been implemented. This MS-3DVAR system is built on top of WRF/GSI. The Community Gridpoint Statistical Interpolation (GSI) system is an operational data assimilation system at the National Centers for Environmental Prediction (NCEP) and has been implemented in the Weather Research and Forecast (WRF) model.more » This MS-3DVAR is further enhanced by the incorporation of a land surface 3DVAR scheme and a comprehensive aerosol 3DVAR scheme. The data assimilation implementation focuses in the ARM SGP region. ARM measurements are assimilated along with other available satellite and radar data. Reanalyses are then generated for a few selected period of time. This comprehensive data assimilation system has also been employed for other ARM-related applications.« less

C-LAMP Subproject Description:Climate Forcing by the Terrestrial Biosphere During the Second Half of the 20th Century

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

Covey, Curt; Hoffman, Forrest

2008-10-02

This project will quantify selected components of climate forcing due to changes in the terrestrial biosphere over the period 1948-2004, as simulated by the climate / carboncycle models participating in C-LAMP (the Carbon-Land Model Intercomparison Project; see http://www.climatemodeling.org/c-lamp). Unlike other C-LAMP projects that attempt to close the carbon budget, this project will focus on the contributions of individual biomes in terms of the resulting climate forcing. Bala et al. (2007) used a similar (though more comprehensive) model-based technique to assess and compare different components of biospheric climate forcing, but their focus was on potential future deforestation rather than the historicalmore » period.« less

Climate Change Impacts at Department of Defense

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

Kotamarthi, Rao; Wang, Jiali; Zoebel, Zach

This project is aimed at providing the U.S. Department of Defense (DoD) with a comprehensive analysis of the uncertainty associated with generating climate projections at the regional scale that can be used by stakeholders and decision makers to quantify and plan for the impacts of future climate change at specific locations. The merits and limitations of commonly used downscaling models, ranging from simple to complex, are compared, and their appropriateness for application at installation scales is evaluated. Downscaled climate projections are generated at selected DoD installations using dynamic and statistical methods with an emphasis on generating probability distributions of climatemore » variables and their associated uncertainties. The sites selection and selection of variables and parameters for downscaling was based on a comprehensive understanding of the current and projected roles that weather and climate play in operating, maintaining, and planning DoD facilities and installations.« less

Changes in the width of the tropical belt due to simple radiative forcing changes in the GeoMIP simulations

NASA Astrophysics Data System (ADS)

Davis, Nicholas A.; Seidel, Dian J.; Birner, Thomas; Davis, Sean M.; Tilmes, Simone

2016-08-01

Model simulations of future climates predict a poleward expansion of subtropical arid climates at the edges of Earth's tropical belt, which would have significant environmental and societal impacts. This expansion may be related to the poleward shift of the Hadley cell edges, where subsidence stabilizes the atmosphere and suppresses precipitation. Understanding the primary drivers of tropical expansion is hampered by the myriad forcing agents in most model projections of future climate. While many previous studies have examined the response of idealized models to simplified climate forcings and the response of comprehensive climate models to more complex climate forcings, few have examined how comprehensive climate models respond to simplified climate forcings. To shed light on robust processes associated with tropical expansion, here we examine how the tropical belt width, as measured by the Hadley cell edges, responds to simplified forcings in the Geoengineering Model Intercomparison Project (GeoMIP). The tropical belt expands in response to a quadrupling of atmospheric carbon dioxide concentrations and contracts in response to a reduction in the solar constant, with a range of a factor of 3 in the response among nine models. Models with more surface warming and an overall stronger temperature response to quadrupled carbon dioxide exhibit greater tropical expansion, a robust result in spite of inter-model differences in the mean Hadley cell width, parameterizations, and numerical schemes. Under a scenario where the solar constant is reduced to offset an instantaneous quadrupling of carbon dioxide, the Hadley cells remain at their preindustrial width, despite the residual stratospheric cooling associated with elevated carbon dioxide levels. Quadrupled carbon dioxide produces greater tropical belt expansion in the Southern Hemisphere than in the Northern Hemisphere. This expansion is strongest in austral summer and autumn. Ozone depletion has been argued to cause this pattern of changes in observations and model experiments, but the results here indicate that seasonally and hemispherically asymmetric tropical expansion can be a basic response of the general circulation to climate forcings.

The Power of the Spectrum: Combining Numerical Proxy System Models with Analytical Error Spectra to Better Understand Timescale Dependent Proxy Uncertainty

NASA Astrophysics Data System (ADS)

Dolman, A. M.; Laepple, T.; Kunz, T.

2017-12-01

Understanding the uncertainties associated with proxy-based reconstructions of past climate is critical if they are to be used to validate climate models and contribute to a comprehensive understanding of the climate system. Here we present two related and complementary approaches to quantifying proxy uncertainty. The proxy forward model (PFM) "sedproxy" bitbucket.org/ecus/sedproxy numerically simulates the creation, archiving and observation of marine sediment archived proxies such as Mg/Ca in foraminiferal shells and the alkenone unsaturation index UK'37. It includes the effects of bioturbation, bias due to seasonality in the rate of proxy creation, aliasing of the seasonal temperature cycle into lower frequencies, and error due to cleaning, processing and measurement of samples. Numerical PFMs have the advantage of being very flexible, allowing many processes to be modelled and assessed for their importance. However, as more and more proxy-climate data become available, their use in advanced data products necessitates rapid estimates of uncertainties for both the raw reconstructions, and their smoothed/derived products, where individual measurements have been aggregated to coarser time scales or time-slices. To address this, we derive closed-form expressions for power spectral density of the various error sources. The power spectra describe both the magnitude and autocorrelation structure of the error, allowing timescale dependent proxy uncertainty to be estimated from a small number of parameters describing the nature of the proxy, and some simple assumptions about the variance of the true climate signal. We demonstrate and compare both approaches for time-series of the last millennia, Holocene, and the deglaciation. While the numerical forward model can create pseudoproxy records driven by climate model simulations, the analytical model of proxy error allows for a comprehensive exploration of parameter space and mapping of climate signal re-constructability, conditional on the climate and sampling conditions.

2016 International Land Model Benchmarking (ILAMB) Workshop Report

NASA Technical Reports Server (NTRS)

Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen; Lawrence, David M.; Riley, William J.; Randerson, James T.; Ahlstrom, Anders; Abramowitz, Gabriel; Baldocchi, Dennis D.; Best, Martin J.;

Climate, Water and Renewable Energy in the Nordic Countries

NASA Astrophysics Data System (ADS)

Snorrason, A.; Jonsdottir, J. F.

2004-05-01

Climate and Energy (CE) is a new Nordic research project with funding from Nordic Energy Research (NEFP) and the Nordic energy sector. The project has the objective of a comprehensive assessment of the impact of climate variability and change on Nordic renewable energy resources including hydropower, wind power, bio-fuels and solar energy. This will include assessment of the power production of the hydropower dominated Nordic energy system and its sensitivity and vulnerability to climate change on both temporal and spatial scales; assessment of the impacts of extremes including floods, droughts, storms, seasonal patterns and variability. Within the CE project several thematic groups work on specific issues of climatic change and their impacts on renewable energy. A primary aim of the CE climate group is to supply a standard set of common scenarios of climate change in northern Europe and Greenland, based on recent global and regional climate change experiments. The snow and ice group has chosen glaciers from Greenland, Iceland, Norway and Sweden for an analysis of the response of glaciers to climate changes. Mass balance and dynamical changes, corresponding to the common scenario for climate changes, will be modelled and effects on glacier hydrology will be estimated. Preliminary work with dynamic modelling and climate scenarios shows a dramatic response of glacial runoff to increased temperature and precipitation. The statistical analysis group has reported on the status of time series analysis in the Nordic countries. The group has selected and quality controlled time series of stream flow to be included in the Nordic component of the database FRIEND. Also the group will collect information on time series for other variables and these series will be systematically analysed with respect to trend and other long-term changes. Preliminary work using multivariate analysis on stream flow and climate variables shows strong linkages with the long term atmospheric circulation in the North Atlantic. The hydrological modelling group has already reported on "Climate change impacts on water resources in the Nordic countries - State of the art and discussion of principles". The group will compare different approaches of transferring the climate change signal into hydrological models and discuss uncertainties in models and climate scenarios. Furthermore, comprehensive assessment and mapping of impact of climate change will be produced for the whole Nordic region based on the scenarios from the CE-climate group.

Economic mitigation challenges: how further delay closes the door for achieving climate targets

NASA Astrophysics Data System (ADS)

Luderer, Gunnar; Pietzcker, Robert C.; Bertram, Christoph; Kriegler, Elmar; Meinshausen, Malte; Edenhofer, Ottmar

2013-09-01

While the international community aims to limit global warming to below 2 ° C to prevent dangerous climate change, little progress has been made towards a global climate agreement to implement the emissions reductions required to reach this target. We use an integrated energy-economy-climate modeling system to examine how a further delay of cooperative action and technology availability affect climate mitigation challenges. With comprehensive emissions reductions starting after 2015 and full technology availability we estimate that maximum 21st century warming may still be limited below 2 ° C with a likely probability and at moderate economic impacts. Achievable temperature targets rise by up to ˜0.4 ° C if the implementation of comprehensive climate policies is delayed by another 15 years, chiefly because of transitional economic impacts. If carbon capture and storage (CCS) is unavailable, the lower limit of achievable targets rises by up to ˜0.3 ° C. Our results show that progress in international climate negotiations within this decade is imperative to keep the 2 ° C target within reach.

Effects of Comprehensive School Reform on Student Achievement and School Change: A Longitudinal Multi-Site Study

ERIC Educational Resources Information Center

Sterbinsky, Allan; Ross, Steven M.; Redfield, Doris

2006-01-01

The longitudinal impacts on school change and student achievement of implementing varied Comprehensive School Reform (CSR) models was investigated in 12 elementary schools in diverse geographic locations. Each school was individually matched and compared to a demographically similar control school on measures of school climate, teacher…

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

Treesearch

Seth J. Wenger; Nicholas A. Som; Daniel C. Dauwalter; Daniel J. Isaak; Helen M. Neville; Charles H. Luce; Jason B. Dunham; Michael K. Young; Kurt D. Fausch; Bruce E. Rieman

2013-01-01

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing...

High skill in low-frequency climate response through fluctuation dissipation theorems despite structural instability.

PubMed

Majda, Andrew J; Abramov, Rafail; Gershgorin, Boris

2010-01-12

Climate change science focuses on predicting the coarse-grained, planetary-scale, longtime changes in the climate system due to either changes in external forcing or internal variability, such as the impact of increased carbon dioxide. The predictions of climate change science are carried out through comprehensive, computational atmospheric, and oceanic simulation models, which necessarily parameterize physical features such as clouds, sea ice cover, etc. Recently, it has been suggested that there is irreducible imprecision in such climate models that manifests itself as structural instability in climate statistics and which can significantly hamper the skill of computer models for climate change. A systematic approach to deal with this irreducible imprecision is advocated through algorithms based on the Fluctuation Dissipation Theorem (FDT). There are important practical and computational advantages for climate change science when a skillful FDT algorithm is established. The FDT response operator can be utilized directly for multiple climate change scenarios, multiple changes in forcing, and other parameters, such as damping and inverse modelling directly without the need of running the complex climate model in each individual case. The high skill of FDT in predicting climate change, despite structural instability, is developed in an unambiguous fashion using mathematical theory as guidelines in three different test models: a generic class of analytical models mimicking the dynamical core of the computer climate models, reduced stochastic models for low-frequency variability, and models with a significant new type of irreducible imprecision involving many fast, unstable modes.

The computational future for climate and Earth system models: on the path to petaflop and beyond.

PubMed

Washington, Warren M; Buja, Lawrence; Craig, Anthony

2009-03-13

The development of the climate and Earth system models has had a long history, starting with the building of individual atmospheric, ocean, sea ice, land vegetation, biogeochemical, glacial and ecological model components. The early researchers were much aware of the long-term goal of building the Earth system models that would go beyond what is usually included in the climate models by adding interactive biogeochemical interactions. In the early days, the progress was limited by computer capability, as well as by our knowledge of the physical and chemical processes. Over the last few decades, there has been much improved knowledge, better observations for validation and more powerful supercomputer systems that are increasingly meeting the new challenges of comprehensive models. Some of the climate model history will be presented, along with some of the successes and difficulties encountered with present-day supercomputer systems.

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

DOE PAGES

Calvin, Kate; Fisher-Vanden, Karen

2017-10-27

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparisonmore » between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between - 12% and + 15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.« less

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

NASA Astrophysics Data System (ADS)

Calvin, Kate; Fisher-Vanden, Karen

2017-11-01

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparison between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between -12% and +15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

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

Calvin, Kate; Fisher-Vanden, Karen

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparisonmore » between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between - 12% and + 15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.« less

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.

Carbon Management In the Post-Cap-and-Trade Carbon Economy-Part II

NASA Astrophysics Data System (ADS)

DeGroff, F. A.

2014-12-01

This is the second installment in our search for a comprehensive economic model to mitigate climate change due to anthropogenic activity. Last year we presented how the unique features of our economic model measure changes in carbon flux due to anthropogenic activity, referred to as carbon quality or CQ, and how the model is used to value such changes in the climate system. This year, our paper focuses on how carbon quality can be implemented to capture the effect of economic activity and international trade on the climate system, thus allowing us to calculate a Return on Climate System (RoCS) for all economic assets and activity. The result is that the RoCS for each public and private economic activity and entity can be calculated by summing up the RoCS for each individual economic asset and activity in which an entity is engaged. Such a macro-level scale is used to rank public and private entities including corporations, governments, and even entire nations, as well as human adaptation and carbon storage activities, providing status and trending insights to evaluate policies on both a micro- and macro-economic level. With international trade, RoCS measures the embodied effects on climate change that will be needed to assess border fees to insure carbon parity on all imports and exports. At the core of our vision is a comprehensive, 'open-source' construct of which our carbon quality metric is the first element. One goal is to recognize each country's endemic resources and infrastructure that affect their ability to manage carbon, while preventing spatial and temporal shifting of carbon emissions that reduce or reverse efforts to mitigate climate change. The standards for calculating the RoCS can be promulgated as part of the Generally Accepted Accounted Principles (GAAP) and the International Financial Reporting Standards (IFRS) to ensure standard and consistent reporting. The value of such insights on the climate system at all levels will be crucial to managing anthropogenic activity in order to minimize the effect on the climate system. Without the insights provided by a comprehensive, standardized and verifiable RoCS, managing anthropogenic activity will be elusive and difficult to achieve, at best. Such a model may also be useful to manage the effect of anthropogenic activity on the nitrogen and phosphorous cycles.

Comparison between Two Methods for agricultural drought disaster risk in southwestern China

NASA Astrophysics Data System (ADS)

han, lanying; zhang, qiang

2016-04-01

The drought is a natural disaster, which lead huge loss to agricultural yield in the world. The drought risk has become increasingly prominent because of the climatic warming during the past century, and which is also one of the main meteorological disasters and serious problem in southwestern China, where drought risk exceeds the national average. Climate change is likely to exacerbate the problem, thereby endangering Chinaʹs food security. In this paper, drought disaster in the southwestern China (where there are serious drought risk and the comprehensive loss accounted for 3.9% of national drought area) were selected to show the drought change under climate change, and two methods were used to assess the drought disaster risk, drought risk assessment model and comprehensive drought risk index. Firstly, we used the analytic hierarchy process and meteorological, geographic, soil, and remote-sensing data to develop a drought risk assessment model (defined using a comprehensive drought disaster risk index, R) based on the drought hazard, environmental vulnerability, sensitivity and exposure of the values at risk, and capacity to prevent or mitigate the problem. Second, we built the comprehensive drought risk index (defined using a comprehensive drought disaster loss, L) based on statistical drought disaster data, including crop yields, drought-induced areas, drought-occurred areas, no harvest areas caused by drought and planting areas. Using the model, we assessed the drought risk. The results showed that spatial distribution of two drought disaster risks were coherent, and revealed complex zonality in southwestern China. The results also showed the drought risk is becoming more and more serious and frequent in the country under the global climatic warming background. The eastern part of the study area had an extremely high risk, and risk was generally greater in the north than in the south, and increased from southwest to northeast. The drought disaster risk or loss was highest in Sichuan Province and Chongqing Municipality. It was lowest in Yunnan province. The comprehensive drought disaster loss were uptrend in nearly 60 years, and the trend of drought occurrence in nearly 60 years was overall upward in every province of Xinan region. Drought risk of all provinces has certain relationship with the regional climate change, such as temperature and precipitation, soil moisture and vegetation coverage. The contribution of the risk factors to R was highest for the capacity for prevention and mitigation, followed by the drought hazard, sensitivity and exposure, and environmental vulnerability.

Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.

PubMed

Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J

2018-01-01

Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

ISMIP6: Ice Sheet Model Intercomparison Project for CMIP6

NASA Technical Reports Server (NTRS)

Nowicki, S.

2015-01-01

ISMIP6 (Ice Sheet Model Intercomparison Project for CMIP6) targets the Cryosphere in a Changing Climate and the Future Sea Level Grand Challenges of the WCRP (World Climate Research Program). Primary goal is to provide future sea level contribution from the Greenland and Antarctic ice sheets, along with associated uncertainty. Secondary goal is to investigate feedback due to dynamic ice sheet models. Experiment design uses and augment the existing CMIP6 (Coupled Model Intercomparison Project Phase 6) DECK (Diagnosis, Evaluation, and Characterization of Klima) experiments. Additonal MIP (Model Intercomparison Project)- specific experiments will be designed for ISM (Ice Sheet Model). Effort builds on the Ice2sea, SeaRISE (Sea-level Response to Ice Sheet Evolution) and COMBINE (Comprehensive Modelling of the Earth System for Better Climate Prediction and Projection) efforts.

Integrated Research on the Development of Global Climate Risk Management Strategies - Framework and Initial Results of the Research Project ICA-RUS

NASA Astrophysics Data System (ADS)

Emori, Seita; Takahashi, Kiyoshi; Yamagata, Yoshiki; Oki, Taikan; Mori, Shunsuke; Fujigaki, Yuko

2013-04-01

With the aim of proposing strategies of global climate risk management, we have launched a five-year research project called ICA-RUS (Integrated Climate Assessment - Risks, Uncertainties and Society). In this project with the phrase "risk management" in its title, we aspire for a comprehensive assessment of climate change risks, explicit consideration of uncertainties, utilization of best available information, and consideration of every possible conditions and options. We also regard the problem as one of decision-making at the human level, which involves social value judgments and adapts to future changes in circumstances. The ICA-RUS project consists of the following five themes: 1) Synthesis of global climate risk management strategies, 2) Optimization of land, water and ecosystem uses for climate risk management, 3) Identification and analysis of critical climate risks, 4) Evaluation of climate risk management options under technological, social and economic uncertainties and 5) Interactions between scientific and social rationalities in climate risk management (see also: http://www.nies.go.jp/ica-rus/en/). For the integration of quantitative knowledge of climate change risks and responses, we apply a tool named AIM/Impact [Policy], which consists of an energy-economic model, a simplified climate model and impact projection modules. At the same time, in order to make use of qualitative knowledge as well, we hold monthly project meetings for the discussion of risk management strategies and publish annual reports based on the quantitative and qualitative information. To enhance the comprehensiveness of the analyses, we maintain an inventory of risks and risk management options. The inventory is revised iteratively through interactive meetings with stakeholders such as policymakers, government officials and industrial representatives.

Recognizing and exploring the right questions with climate data: An example of better understanding ENSO in climate projections

NASA Astrophysics Data System (ADS)

Ammann, C. M.; Brown, B.; Kalb, C. P.; Bullock, R.; Buja, L.; Gutowski, W. J., Jr.; Halley-Gotway, J.; Kaatz, L.; Yates, D. N.

2017-12-01

Coordinated, multi-model climate change projection archives have already led to a flourishing of new climate impact applications. Collections and online tools for the computation of derived indicators have attracted many non-specialist users and decision-makers and facilitated for them the exploration of potential future weather and climate changes on their systems. Guided by a set of standardized steps and analyses, many can now use model output and determine basic model-based changes. But because each application and decision-context is different, the question remains if such a small collection of standardized tools can faithfully and comprehensively represent the critical physical context of change? We use the example of the El Niño - Southern Oscillation, the largest and most broadly recognized mode of variability in the climate system, to explore the difference in impact contexts between a quasi-blind, protocol-bound and a flexible, scientifically guided use of climate information. More use oriented diagnostics of the model-data as well as different strategies for getting data into decision environments are explored.

Regional climate models reduce biases of global models and project smaller European summer warming

NASA Astrophysics Data System (ADS)

Soerland, S.; Schar, C.; Lüthi, D.; Kjellstrom, E.

2017-12-01

The assessment of regional climate change and the associated planning of adaptation and response strategies are often based on complex model chains. Typically, these model chains employ global and regional climate models (GCMs and RCMs), as well as one or several impact models. It is a common belief that the errors in such model chains behave approximately additive, thus the uncertainty should increase with each modeling step. If this hypothesis were true, the application of RCMs would not lead to any intrinsic improvement (beyond higher-resolution detail) of the GCM results. Here, we investigate the bias patterns (offset during the historical period against observations) and climate change signals of two RCMs that have downscaled a comprehensive set of GCMs following the EURO-CORDEX framework. The two RCMs reduce the biases of the driving GCMs, reduce the spread and modify the amplitude of the GCM projected climate change signal. The GCM projected summer warming at the end of the century is substantially reduced by both RCMs. These results are important, as the projected summer warming and its likely impact on the water cycle are among the most serious concerns regarding European climate change.

The CESM Large Ensemble Project: Inspiring New Ideas and Understanding

NASA Astrophysics Data System (ADS)

Kay, J. E.; Deser, C.

2016-12-01

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

Selecting climate change scenarios for regional hydrologic impact studies based on climate extremes indices

NASA Astrophysics Data System (ADS)

Seo, Seung Beom; Kim, Young-Oh; Kim, Youngil; Eum, Hyung-Il

2018-04-01

When selecting a subset of climate change scenarios (GCM models), the priority is to ensure that the subset reflects the comprehensive range of possible model results for all variables concerned. Though many studies have attempted to improve the scenario selection, there is a lack of studies that discuss methods to ensure that the results from a subset of climate models contain the same range of uncertainty in hydrologic variables as when all models are considered. We applied the Katsavounidis-Kuo-Zhang (KKZ) algorithm to select a subset of climate change scenarios and demonstrated its ability to reduce the number of GCM models in an ensemble, while the ranges of multiple climate extremes indices were preserved. First, we analyzed the role of 27 ETCCDI climate extremes indices for scenario selection and selected the representative climate extreme indices. Before the selection of a subset, we excluded a few deficient GCM models that could not represent the observed climate regime. Subsequently, we discovered that a subset of GCM models selected by the KKZ algorithm with the representative climate extreme indices could not capture the full potential range of changes in hydrologic extremes (e.g., 3-day peak flow and 7-day low flow) in some regional case studies. However, the application of the KKZ algorithm with a different set of climate indices, which are correlated to the hydrologic extremes, enabled the overcoming of this limitation. Key climate indices, dependent on the hydrologic extremes to be projected, must therefore be determined prior to the selection of a subset of GCM models.

Adapting to Health Impacts of Climate Change in the Department of Defense.

PubMed

Chrétien, Jean-Paul

2016-01-01

The Department of Defense (DoD) recognizes climate change as a threat to its mission and recently issued policy to implement climate change adaptation measures. However, the DoD has not conducted a comprehensive assessment of health-related climate change effects. To catalyze the needed assessment--a first step toward a comprehensive DoD climate change adaptation plan for health--this article discusses the DoD relevance of 3 selected climate change impacts: heat injuries, vector-borne diseases, and extreme weather that could lead to natural disasters. The author uses these examples to propose a comprehensive approach to planning for health-related climate change impacts in the DoD.

A comprehensive surface-groundwater flow model

NASA Astrophysics Data System (ADS)

Arnold, Jeffrey G.; Allen, Peter M.; Bernhardt, Gilbert

1993-02-01

In this study, a simple groundwater flow and height model was added to an existing basin-scale surface water model. The linked model is: (1) watershed scale, allowing the basin to be subdivided; (2) designed to accept readily available inputs to allow general use over large regions; (3) continuous in time to allow simulation of land management, including such factors as climate and vegetation changes, pond and reservoir management, groundwater withdrawals, and stream and reservoir withdrawals. The model is described, and is validated on a 471 km 2 watershed near Waco, Texas. This linked model should provide a comprehensive tool for water resource managers in development and planning.

Developing a Toolkit for Model Evaluation Using Speleothem Isotope Data

NASA Astrophysics Data System (ADS)

Comas-Bru, L.; Deininger, M.; Harrison, S.

2017-12-01

Speleothems can provide high-resolution records of changes in both climate and atmospheric composition. These records have the potential to be used to document regional changes in mean climate and climate variability on annual to centennial timescales. They can also be used to refine our understanding of regional changes in climate forcings, such as dust and volcanic aerosols, through time. Many climate models now explicitly include isotopic tracers, and thus the isotopic records from speleothems can be used for model evaluation. Previous attempts to compile speleothem data have not provided a globally-comprehensive synthesis, nor have they provided assessments of measurement, chronological or interpretation uncertainties. SISAL (Speleothem Isotopes Synthesis and Analysis) is a new community-based working groupsponsored by Past Global Changes (PAGES) to synthesise the 500+speleothem isotopic records available globallyand develop a public-accessdatabase, that can be used both to explore past climate changes and in model evaluation. This presentation will showcase preliminary syntheses for the Last Glacial Maximum (21 ka), the mid-Holocene (6 ka) and the Last Millennium (850-1850 CE).

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

NASA Astrophysics Data System (ADS)

Lee, H.

2016-12-01

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

Comprehension of climate change and environmental attitudes across the lifespan.

PubMed

Degen, C; Kettner, S E; Fischer, H; Lohse, J; Funke, J; Schwieren, C; Goeschl, T; Schröder, J

2014-08-01

Given the coincidence of the demographic change and climate change in the upcoming decades the aging voter gains increasing importance in climate change mitigation and adaptation processes. It is generally assumed that information status and comprehension of complex processes underlying climate change are prerequisites for adopting pro-environmental attitudes and taking pro-environmental actions. In a cross-sectional study, we investigated in how far (1) environmental knowledge and comprehension of feedback processes underlying climate change and (2) pro-environmental attitudes change as a function of age. Our sample consisted of 92 participants aged 25-75 years (mean age 49.4 years, SD 17.0). Age was negatively related to comprehension of system structures inherent to climate change, but positively associated with level of fear of consequences and anxiousness towards climate change. No significant relations were found between environmental knowledge and pro-environmental attitude. These results indicate that, albeit understanding of relevant structures of the climate system is less present in older age, age is not a limiting factor for being engaged in the complex dilemma of climate change. Results bear implications for the communication of climate change and pro-environmental actions in aging societies.

Measuring school climate in high schools: a focus on safety, engagement, and the environment.

PubMed

Bradshaw, Catherine P; Waasdorp, Tracy E; Debnam, Katrina J; Johnson, Sarah Lindstrom

2014-09-01

School climate has been linked to multiple student behavioral, academic, health, and social-emotional outcomes. The US Department of Education (USDOE) developed a 3-factor model of school climate comprised of safety, engagement, and environment. This article examines the factor structure and measurement invariance of the USDOE model. Drawing upon 2 consecutive waves of data from over 25,000 high school students (46% minority), a series of exploratory and confirmatory factor analyses examined the fit of the Maryland Safe and Supportive Schools Climate Survey with the USDOE model. The results indicated adequate model fit with the theorized 3-factor model of school climate, which included 13 subdomains: safety (perceived safety, bullying and aggression, and drug use); engagement (connection to teachers, student connectedness, academic engagement, school connectedness, equity, and parent engagement); environment (rules and consequences, physical comfort, and support, disorder). We also found consistent measurement invariance with regard to student sex, grade level, and ethnicity. School-level interclass correlation coefficients ranged from 0.04 to .10 for the scales. Findings supported the USDOE 3-factor model of school climate and suggest measurement invariance and high internal consistency of the 3 scales and 13 subdomains. These results suggest the 56-item measure may be a potentially efficient, yet comprehensive measure of school climate. © 2014, American School Health Association.

Tempo and mode of climatic niche evolution in Primates.

PubMed

Duran, Andressa; Pie, Marcio R

2015-09-01

Climatic niches have increasingly become a nexus in our understanding of a variety of ecological and evolutionary phenomena, from species distributions to latitudinal diversity gradients. Despite the increasing availability of comprehensive datasets on species ranges, phylogenetic histories, and georeferenced environmental conditions, studies on the evolution of climate niches have only begun to understand how niches evolve over evolutionary timescales. Here, using primates as a model system, we integrate recently developed phylogenetic comparative methods, species distribution patterns, and climatic data to explore primate climatic niche evolution, both among clades and over time. In general, we found that simple, constant-rate models provide a poor representation of how climatic niches evolve. For instance, there have been shifts in the rate of climatic niche evolution in several independent clades, particularly in response to the increasingly cooler climates of the past 10 My. Interestingly, rate accelerations greatly outnumbered rate decelerations. These results highlight the importance of considering more realistic evolutionary models that allow for the detection of heterogeneity in the tempo and mode of climatic niche evolution, as well as to infer possible constraining factors for species distributions in geographical space. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Impact of climate change on river discharge in the Teteriv River basin (Ukraine)

NASA Astrophysics Data System (ADS)

Didovets, Iulii; Lobanova, Anastasia; Krysanova, Valentina; Snizhko, Sergiy; Bronstert, Axel

2016-04-01

The problem of water resources availability in the climate change context arises now in many countries. Ukraine is characterized by a relatively low availability of water resources compared to other countries. It is the 111th among 152 countries by the amount of domestic water resources available per capita. To ensure socio-economic development of the region and to adapt to climate change, a comprehensive assessment of potential changes in qualitative and quantitative characteristics of water resources in the region is needed. The focus of our study is the Teteriv River basin located in northern Ukraine within three administrative districts covering the area of 15,300 km2. The Teteriv is the right largest tributary of the Dnipro River, which is the fourth longest river in Europe. The water resources in the region are intensively used in industry, communal infrastructure, and agriculture. This is evidenced by a large number of dams and industrial objects which have been constructed from the early 20th century. For success of the study, it was necessary to apply a comprehensive hydrological model, tested in similar natural conditions. Therefore, an eco-hydrological model SWIM with the daily time step was applied, as this model was used previously for climate impact assessment in many similar river basins on the European territory. The model was set up, calibrated and validated for the gauge Ivankiv located close to the outlet of the Teteriv River. The Nash-Sutcliffe efficiency coefficient for the calibration period is 0.79 (0.86), and percent bias is 4,9% (-3.6%) with the daily (monthly) time step. The future climate scenarios were selected from the IMPRESSIONS (Impacts and Risks from High-End Scenarios: Strategies for Innovative Solutions, www.impressions-project.eu) project, which developed 7 climate scenarios under RCP4.5 and RCP8.5 based on GCMs and downscaled using RCMs. The results of climate impact assessment for the Teteriv River basin will be presented.

Interactive, process-oriented climate modeling with CLIMLAB

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2016-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The Jupyter Notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields.

Stochastic Parameterization: Toward a New View of Weather and Climate Models

DOE PAGES

Berner, Judith; Achatz, Ulrich; Batté, Lauriane; ...

2017-03-31

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

Stochastic Parameterization: Toward a New View of Weather and Climate Models

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

Berner, Judith; Achatz, Ulrich; Batté, Lauriane

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

Assessment of the Impacts of Climate Change on Stream Discharge and Water Quality in an Arid, Urbanized Watershed

NASA Astrophysics Data System (ADS)

Ranatunga, T.; Tong, S.; Yang, J.

2011-12-01

Hydrologic and water quality models can provide a general framework to conceptualize and investigate the relationships between climate and water resources. Under a hot and dry climate, highly urbanized watersheds are more vulnerable to changes in climate, such as excess heat and drought. In this study, a comprehensive watershed model, Hydrological Simulation Program FORTRAN (HSPF), is used to assess the impacts of future climate change on the stream discharge and water quality in Las Vegas Wash in Nevada, the only surface water body that drains from the Las Vegas Valley (an area with rapid population growth and urbanization) to Lake Mead. In this presentation, the process of model building, calibration and validation, the generation of climate change scenarios, and the assessment of future climate change effects on stream hydrology and quality are demonstrated. The hydrologic and water quality model is developed based on the data from current national databases and existing major land use categories of the watershed. The model is calibrated for stream discharge, nutrients (nitrogen and phosphorus) and sediment yield. The climate change scenarios are derived from the outputs of the Global Climate Models (GCM) and Regional Climate Models (RCM) simulations, and from the recent assessment reports from the Intergovernmental Panel on Climate Change (IPCC). The Climate Assessment Tool from US EPA's BASINS is used to assess the effects of likely future climate scenarios on the water quantity and quality in Las Vegas Wash. Also the presentation discusses the consequences of these hydrologic changes, including the deficit supplies of clean water during peak seasons of water demand, increased eutrophication potentials, wetland deterioration, and impacts on wild life habitats.

A large ozone-circulation feedback and its implications for global warming assessments.

PubMed

Nowack, Peer J; Abraham, N Luke; Maycock, Amanda C; Braesicke, Peter; Gregory, Jonathan M; Joshi, Manoj M; Osprey, Annette; Pyle, John A

2015-01-01

State-of-the-art climate models now include more climate processes which are simulated at higher spatial resolution than ever 1 . Nevertheless, some processes, such as atmospheric chemical feedbacks, are still computationally expensive and are often ignored in climate simulations 1,2 . Here we present evidence that how stratospheric ozone is represented in climate models can have a first order impact on estimates of effective climate sensitivity. Using a comprehensive atmosphere-ocean chemistry-climate model, we find an increase in global mean surface warming of around 1°C (~20%) after 75 years when ozone is prescribed at pre-industrial levels compared with when it is allowed to evolve self-consistently in response to an abrupt 4×CO 2 forcing. The difference is primarily attributed to changes in longwave radiative feedbacks associated with circulation-driven decreases in tropical lower stratospheric ozone and related stratospheric water vapour and cirrus cloud changes. This has important implications for global model intercomparison studies 1,2 in which participating models often use simplified treatments of atmospheric composition changes that are neither consistent with the specified greenhouse gas forcing scenario nor with the associated atmospheric circulation feedbacks 3-5 .

Quantifying the probability of record-setting heat events in the historical record and at different levels of climate forcing

NASA Astrophysics Data System (ADS)

Diffenbaugh, N. S.

2017-12-01

Severe heat provides one of the most direct, acute, and rapidly changing impacts of climate on people and ecostystems. Theory, historical observations, and climate model simulations all suggest that global warming should increase the probability of hot events that fall outside of our historical experience. Given the acutre impacts of extreme heat, quantifying the probability of historically unprecedented hot events at different levels of climate forcing is critical for climate adaptation and mitigation decisions. However, in practice that quantification presents a number of methodological challenges. This presentation will review those methodological challenges, including the limitations of the observational record and of climate model fidelity. The presentation will detail a comprehensive approach to addressing these challenges. It will then demonstrate the application of that approach to quantifying uncertainty in the probability of record-setting hot events in the current climate, as well as periods with lower and higher greenhouse gas concentrations than the present.

Participatory data collection and monitoring of agricultural pest dynamics for climate-resilient coffee production using Tiko'n, a generic tool to develop agroecological food web models

NASA Astrophysics Data System (ADS)

Rojas, M.; Malard, J. J.; Adamowski, J. F.; Tuy, H.

2016-12-01

Climate variability impacts agricultural processes through many mechanisms. For example, the proliferation of pests and diseases increases with warmer climate and alternated wind patterns, as longer growing seasons allow pest species to complete more reproductive cycles and changes in the weather patterns alter the stages and rates of development of pests and pathogens. Several studies suggest that enhancing plant diversity and complexity in farming systems, such as in agroforestry systems, reduces the vulnerability of farms to extreme climatic events. On the other hand, other authors have argued that vegetation diversity does not necessarily reduce the incidence of pests and diseases, highlighting the importance of understanding how, where and when it is recommendable to diversify vegetation to improve pest and disease control, and emphasising the need for tools to develop, monitor and evaluate agroecosystems. In order to understand how biodiversity can enhance ecosystem services provided by the agroecosystem in the context of climatic variability, it is important to develop comprehensive models that include the role of trophic chains in the regulation of pests, which can be achieved by integrating crop models with pest-predator models, also known as agroecosystem network (AEN) models. Here we present a methodology for the participatory data collection and monitoring necessary for running Tiko'n, an AEN model that can also be coupled to a crop model such as DSSAT. This methodology aims to combine the local and practical knowledge of farmers with the scientific knowledge of entomologists and agronomists, allowing for the simplification of complex ecological networks of plant and insect interactions. This also increases the acceptability, credibility, and comprehension of the model by farmers, allowing them to understand their relationship with the local agroecosystem and their potential to use key agroecosystem principles such as functional diversity to mitigate climate variability impacts. Preliminary results of a study currently being conducted in a coffee agroforestry system in El Quebracho, Guatemala, will be presented, where the data was directly collected by farmers during eight consecutive months. Finally, future recommendations from lessons learnt during this study will be discussed.

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.

The Signature of Southern Hemisphere Atmospheric Circulation Patterns in Antarctic Precipitation

PubMed Central

Thompson, David W. J.; van den Broeke, Michiel R.

2017-01-01

Abstract We provide the first comprehensive analysis of the relationships between large‐scale patterns of Southern Hemisphere climate variability and the detailed structure of Antarctic precipitation. We examine linkages between the high spatial resolution precipitation from a regional atmospheric model and four patterns of large‐scale Southern Hemisphere climate variability: the southern baroclinic annular mode, the southern annular mode, and the two Pacific‐South American teleconnection patterns. Variations in all four patterns influence the spatial configuration of precipitation over Antarctica, consistent with their signatures in high‐latitude meridional moisture fluxes. They impact not only the mean but also the incidence of extreme precipitation events. Current coupled‐climate models are able to reproduce all four patterns of atmospheric variability but struggle to correctly replicate their regional impacts on Antarctic climate. Thus, linking these patterns directly to Antarctic precipitation variability may allow a better estimate of future changes in precipitation than using model output alone. PMID:29398735

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

USGS Publications Warehouse

Wenger, Seth J.; Som, Nicholas A.; Dauwalter, Daniel C.; Isaak, Daniel J.; Neville, Helen M.; Luce, Charles H.; Dunham, Jason B.; Young, Michael K.; Fausch, Kurt D.; Rieman, Bruce E.

2013-01-01

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site-specific frequency distributions of occurrence probabilities across a species’ range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1–42.5 thousand km; this was predicted to decline to 0.5–7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.

Representation of deforestation impacts on climate, water, and nutrient cycles in the ACME earth system model

NASA Astrophysics Data System (ADS)

Cai, X.; Riley, W. J.; Zhu, Q.

2017-12-01

Deforestation causes a series of changes to the climate, water, and nutrient cycles. Employing a state-of-the-art earth system model—ACME (Accelerated Climate Modeling for Energy), we comprehensively investigate the impacts of deforestation on these processes. We first assess the performance of the ACME Land Model (ALM) in simulating runoff, evapotranspiration, albedo, and plant productivity at 42 FLUXNET sites. The single column mode of ACME is then used to examine climate effects (temperature cooling/warming) and responses of runoff, evapotranspiration, and nutrient fluxes to deforestation. This approach separates local effects of deforestation from global circulation effects. To better understand the deforestation effects in a global context, we use the coupled (atmosphere, land, and slab ocean) mode of ACME to demonstrate the impacts of deforestation on global climate, water, and nutrient fluxes. Preliminary results showed that the land component of ACME has advantages in simulating these processes and that local deforestation has potentially large impacts on runoff and atmospheric processes.

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

ERIC Educational Resources Information Center

Maier, Christopher J.

2017-01-01

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

Simulation Modeling of Lakes in Undergraduate and Graduate Classrooms Increases Comprehension of Climate Change Concepts and Experience with Computational Tools

ERIC Educational Resources Information Center

Carey, Cayelan C.; Gougis, Rebekka Darner

2017-01-01

Ecosystem modeling is a critically important tool for environmental scientists, yet is rarely taught in undergraduate and graduate classrooms. To address this gap, we developed a teaching module that exposes students to a suite of modeling skills and tools (including computer programming, numerical simulation modeling, and distributed computing)…

Projecting the Global Distribution of the Emerging Amphibian Fungal Pathogen, Batrachochytrium dendrobatidis, Based on IPCC Climate Futures.

PubMed

Xie, Gisselle Yang; Olson, Deanna H; Blaustein, Andrew R

2016-01-01

Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest) with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary), including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific) and also separately per region (region-specific). One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas, especially for sensitive species and those vulnerable to multiple threats.

From biota to chemistry and climate: towards a comprehensive description of trace gas exchange between the biosphere and atmosphere

NASA Astrophysics Data System (ADS)

Arneth, A.; Sitch, S.; Bondeau, A.; Butterbach-Bahl, K.; Foster, P.; Gedney, N.; de Noblet-Ducoudré, N.; Prentice, I. C.; Sanderson, M.; Thonicke, K.; Wania, R.; Zaehle, S.

2010-01-01

Exchange of non-CO2 trace gases between the land surface and the atmosphere plays an important role in atmospheric chemistry and climate. Recent studies have highlighted its importance for interpretation of glacial-interglacial ice-core records, the simulation of the pre-industrial and present atmosphere, and the potential for large climate-chemistry and climate-aerosol feedbacks in the coming century. However, spatial and temporal variations in trace gas emissions and the magnitude of future feedbacks are a major source of uncertainty in atmospheric chemistry, air quality and climate science. To reduce such uncertainties Dynamic Global Vegetation Models (DGVMs) are currently being expanded to mechanistically represent processes relevant to non-CO2 trace gas exchange between land biota and the atmosphere. In this paper we present a review of important non-CO2 trace gas emissions, the state-of-the-art in DGVM modelling of processes regulating these emissions, identify key uncertainties for global scale model applications, and discuss a methodology for model integration and evaluation.

From biota to chemistry and climate: towards a comprehensive description of trace gas exchange between the biosphere and atmosphere

NASA Astrophysics Data System (ADS)

Arneth, A.; Sitch, S.; Bondeau, A.; Butterbach-Bahl, K.; Foster, P.; Gedney, N.; de Noblet-Ducoudré, N.; Prentice, I. C.; Sanderson, M.; Thonicke, K.; Wania, R.; Zaehle, S.

2009-07-01

Exchange of non-CO2 trace gases between the land surface and the atmosphere plays an important role in atmospheric chemistry and climate. Recent studies have highlighted its importance for interpretation of glacial-interglacial ice-core records, the simulation of the pre-industrial and present atmosphere, and the potential for large climate-chemistry and climate-aerosol feedbacks in the coming century. However, spatial and temporal variations in trace gas emissions and the magnitude of future feedbacks are a major source of uncertainty in atmospheric chemistry, air quality and climate science. To reduce such uncertainties Dynamic Global Vegetation Models (DGVMs) are currently being expanded to mechanistically represent processes relevant to non-CO2 trace gas exchange between land biota and the atmosphere. In this paper we present a review of important non-CO2 trace gas emissions, the state-of-the-art in DGVM modelling of processes regulating these emissions, identify key uncertainties for global scale model applications, and discuss a methodology for model integration and evaluation.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-06-01

The Indian summer monsoon shapes the livelihood of a large share of the world's population. About 80% of annual precipitation over India occurs during the monsoon season from June through September. Next to its seasonal mean rainfall, the day-to-day variability is crucial for the risk of flooding, national water supply, and agricultural productivity. Here we show that the latest ensemble of climate model simulations, prepared for the AR-5 of the Intergovernmental Panel on Climate Change, consistently projects significant increases in day-to-day rainfall variability under unmitigated climate change. The relative increase by the period 2071-2100 with respect to the control period 1871-1900 ranges from 13% to 50% under the strongest scenario (Representative Concentration Pathways, RCP-8.5), in the 10 models with the most realistic monsoon climatology; and 13% to 85% when all the 20 models are considered. The spread across models reduces when variability increase per degree of global warming is considered, which is independent of the scenario in most models, and is 8% ± 4%/K on average. This consistent projection across 20 comprehensive climate models provides confidence in the results and suggests the necessity of profound adaptation measures in the case of unmitigated climate change.

Missing link in the service profit chain: a meta-analytic review of the antecedents, consequences, and moderators of service climate.

PubMed

Hong, Ying; Liao, Hui; Hu, Jia; Jiang, Kaifeng

2013-03-01

Service climate captures employees' consensual perceptions of organizations' emphasis on service quality. Although many studies have examined the foundation issues and outcomes of service climate, there is a lack of a comprehensive model explicating the antecedents, outcomes, and moderators of service climate. The current study fills this void in the literature. By conducting a meta-analysis of 58 independent samples (N = 9,363), we found support for service climate as a critical linkage between internal and external service parameters. In addition, we found differential effects of service-oriented versus general human resource practices and leadership on service climate, as well as disparate impacts of service climate contingent on types of service, measures of service climate, and sources of rating. Research and practical implications are discussed.

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

[Climate suitability for tea growing in Zhejiang Province].

PubMed

Jin, Zhi-Feng; Ye, Jian-Gang; Yang, Zai-Qiang; Sun, Rui; Hu, Bo; Li, Ren-Zhong

2014-04-01

It is important to quantitatively assess the climate suitability of tea and its response to climate change. Based on meteorological indices of tea growth and daily meteorological data from 1971 to 2010 in Zhejiang Province, three climate suitability models for single climate factors, including temperature, precipitation and sunshine, were established at a 10-day scale by using the fuzzy mathematics method, and a comprehensive climate suitability model was established with the geometric average method. The results indicated that the climate suitability was high in the tea growth season in Zhejiang Province, and the three kinds of climate suitability were all higher than 0.6. As for the single factor climate suitability, temperature suitability was the highest and sunshine suitability was the lowest. There were obvious inter-annual variations of tea climate suitability, with a decline trend in the 1970s, less variation in the 1980s, and an obvious incline trend after the 1990s. The change tendency of climate suitability for spring tea was similar with that of annual climate suitability, lower in the 1980s, higher in the 1970s and after the 1990s. However, the variation amplitude of the climate suitability for spring tea was larger. The climate suitability for summer tea and autumn tea showed a decline trend from 1971 to 2010.

Impacts of Climate Policy on Regional Air Quality, Health, and Air Quality Regulatory Procedures

NASA Astrophysics Data System (ADS)

Thompson, T. M.; Selin, N. E.

2011-12-01

Both the changing climate, and the policy implemented to address climate change can impact regional air quality. We evaluate the impacts of potential selected climate policies on modeled regional air quality with respect to national pollution standards, human health and the sensitivity of health uncertainty ranges. To assess changes in air quality due to climate policy, we couple output from a regional computable general equilibrium economic model (the US Regional Energy Policy [USREP] model), with a regional air quality model (the Comprehensive Air Quality Model with Extensions [CAMx]). USREP uses economic variables to determine how potential future U.S. climate policy would change emissions of regional pollutants (CO, VOC, NOx, SO2, NH3, black carbon, and organic carbon) from ten emissions-heavy sectors of the economy (electricity, coal, gas, crude oil, refined oil, energy intensive industry, other industry, service, agriculture, and transportation [light duty and heavy duty]). Changes in emissions are then modeled using CAMx to determine the impact on air quality in several cities in the Northeast US. We first calculate the impact of climate policy by using regulatory procedures used to show attainment with National Ambient Air Quality Standards (NAAQS) for ozone and particulate matter. Building on previous work, we compare those results with the calculated results and uncertainties associated with human health impacts due to climate policy. This work addresses a potential disconnect between NAAQS regulatory procedures and the cost/benefit analysis required for and by the Clean Air Act.

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

Biosphere-Atmosphere Transfer Scheme (BATS) version le as coupled to the NCAR community climate model. Technical note. [NCAR (National Center for Atmospheric Research)

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

Dickinson, R.E.; Henderson-Sellers, A.; Kennedy, P.J.

A comprehensive model of land-surface processes has been under development suitable for use with various National Center for Atmospheric Research (NCAR) General Circulation Models (GCMs). Special emphasis has been given to describing properly the role of vegetation in modifying the surface moisture and energy budgets. The result of these efforts has been incorporated into a boundary package, referred to as the Biosphere-Atmosphere Transfer Scheme (BATS). The current frozen version, BATS1e is a piece of software about four thousand lines of code that runs as an offline version or coupled to the Community Climate Model (CCM).

Normal forms for reduced stochastic climate models

PubMed Central

Majda, Andrew J.; Franzke, Christian; Crommelin, Daan

2009-01-01

The systematic development of reduced low-dimensional stochastic climate models from observations or comprehensive high-dimensional climate models is an important topic for atmospheric low-frequency variability, climate sensitivity, and improved extended range forecasting. Here techniques from applied mathematics are utilized to systematically derive normal forms for reduced stochastic climate models for low-frequency variables. The use of a few Empirical Orthogonal Functions (EOFs) (also known as Principal Component Analysis, Karhunen–Loéve and Proper Orthogonal Decomposition) depending on observational data to span the low-frequency subspace requires the assessment of dyad interactions besides the more familiar triads in the interaction between the low- and high-frequency subspaces of the dynamics. It is shown below that the dyad and multiplicative triad interactions combine with the climatological linear operator interactions to simultaneously produce both strong nonlinear dissipation and Correlated Additive and Multiplicative (CAM) stochastic noise. For a single low-frequency variable the dyad interactions and climatological linear operator alone produce a normal form with CAM noise from advection of the large scales by the small scales and simultaneously strong cubic damping. These normal forms should prove useful for developing systematic strategies for the estimation of stochastic models from climate data. As an illustrative example the one-dimensional normal form is applied below to low-frequency patterns such as the North Atlantic Oscillation (NAO) in a climate model. The results here also illustrate the short comings of a recent linear scalar CAM noise model proposed elsewhere for low-frequency variability. PMID:19228943

Global Potential for Hydro-generated Electricity and Climate Change Impact

NASA Astrophysics Data System (ADS)

Zhou, Y.; Hejazi, M. I.; Leon, C.; Calvin, K. V.; Thomson, A. M.; Li, H. Y.

2014-12-01

Hydropower is a dominant renewable energy source at the global level, accounting for more than 15% of the world's total power supply. It is also very vulnerable to climate change. Improved understanding of climate change impact on hydropower can help develop adaptation measures to increase the resilience of energy system. In this study, we developed a comprehensive estimate of global hydropower potential using runoff and stream flow data derived from a global hydrologic model with a river routing sub-model, along with turbine technology performance, cost assumptions, and environmental consideration (Figure 1). We find that hydropower has the potential to supply a significant portion of the world energy needs, although this potential varies substantially by regions. Resources in a number of countries exceed by multiple folds the total current demand for electricity, e.g., Russia and Indonesia. A sensitivity analysis indicates that hydropower potential can be highly sensitive to a number of parameters including designed flow for capacity, cost and financing, turbine efficiency, and stream flow. The climate change impact on hydropower potential was evaluated by using runoff outputs from 4 climate models (HadCM3, PCM, CGCM2, and CSIRO2). It was found that the climate change on hydropower shows large variation not only by regions, but also climate models, and this demonstrates the importance of incorporating climate change into infrastructure-planning at the regional level though the existing uncertainties.

CMIP5 Scientific Gaps and Recommendations for CMIP6

DOE PAGES

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

2017-01-23

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP,more » that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less

CMIP5 Scientific Gaps and Recommendations for CMIP6

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

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

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP,more » that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less

Advocating for Safe Schools, Positive School Climate, and Comprehensive Mental Health Services

ERIC Educational Resources Information Center

Cowan, Katherine C.; Vaillancourt, Kelly

2013-01-01

The tragedy at Sandy Hook Elementary School, Newtown, CT (USA) has brought the conversation about how to reduce violence, make schools safer, improve school climate, and increase access to mental health services to the forefront of the national conversation. Advocating for comprehensive initiatives to address school safety, school climate, and…

Confronting the Uncertainty in Aerosol Forcing Using Comprehensive Observational Data

NASA Astrophysics Data System (ADS)

Johnson, J. S.; Regayre, L. A.; Yoshioka, M.; Pringle, K.; Sexton, D.; Lee, L.; Carslaw, K. S.

2017-12-01

The effect of aerosols on cloud droplet concentrations and radiative properties is the largest uncertainty in the overall radiative forcing of climate over the industrial period. In this study, we take advantage of a large perturbed parameter ensemble of simulations from the UK Met Office HadGEM-UKCA model (the aerosol component of the UK Earth System Model) to comprehensively sample uncertainty in aerosol forcing. Uncertain aerosol and atmospheric parameters cause substantial aerosol forcing uncertainty in climatically important regions. As the aerosol radiative forcing itself is unobservable, we investigate the potential for observations of aerosol and radiative properties to act as constraints on the large forcing uncertainty. We test how eight different theoretically perfect aerosol and radiation observations can constrain the forcing uncertainty over Europe. We find that the achievable constraint is weak unless many diverse observations are used simultaneously. This is due to the complex relationships between model output responses and the multiple interacting parameter uncertainties: compensating model errors mean there are many ways to produce the same model output (known as model equifinality) which impacts on the achievable constraint. However, using all eight observable quantities together we show that the aerosol forcing uncertainty can potentially be reduced by around 50%. This reduction occurs as we reduce a large sample of model variants (over 1 million) that cover the full parametric uncertainty to around 1% that are observationally plausible.Constraining the forcing uncertainty using real observations is a more complex undertaking, in which we must account for multiple further uncertainties including measurement uncertainties, structural model uncertainties and the model discrepancy from reality. Here, we make a first attempt to determine the true potential constraint on the forcing uncertainty from our model that is achievable using a comprehensive set of real aerosol and radiation observations taken from ground stations, flight campaigns and satellite. This research has been supported by the UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund, and by the NERC funded GASSP project.

Toward a U.S. National Phenological Assessment

NASA Astrophysics Data System (ADS)

Henebry, Geoffrey M.; Betancourt, Julio L.

2010-01-01

Third USA National Phenology Network (USA-NPN) and Research Coordination Network (RCN) Annual Meeting; Milwaukee, Wisconsin, 5-9 October 2009; Directional climate change will have profound and lasting effects throughout society that are best understood through fundamental physical and biological processes. One such process is phenology: how the timing of recurring biological events is affected by biotic and abiotic forces. Phenology is an early and integrative indicator of climate change readily understood by nonspecialists. Phenology affects the planting, maturation, and harvesting of food and fiber; pollination; timing and magnitude of allergies and disease; recreation and tourism; water quantity and quality; and ecosystem function and resilience. Thus, phenology is the gateway to climatic effects on both managed and unmanaged ecosystems. Adaptation to climatic variability and change will require integration of phenological data and models with climatic forecasts at seasonal to decadal time scales. Changes in phenologies have already manifested myriad effects of directional climate change. As these changes continue, it is critical to establish a comprehensive suite of benchmarks that can be tracked and mapped at local to continental scales with observations and climate models.

Parasite biodiversity faces extinction and redistribution in a changing climate.

PubMed

Carlson, Colin J; Burgio, Kevin R; Dougherty, Eric R; Phillips, Anna J; Bueno, Veronica M; Clements, Christopher F; Castaldo, Giovanni; Dallas, Tad A; Cizauskas, Carrie A; Cumming, Graeme S; Doña, Jorge; Harris, Nyeema C; Jovani, Roger; Mironov, Sergey; Muellerklein, Oliver C; Proctor, Heather C; Getz, Wayne M

2017-09-01

Climate change is a well-documented driver of both wildlife extinction and disease emergence, but the negative impacts of climate change on parasite diversity are undocumented. We compiled the most comprehensive spatially explicit data set available for parasites, projected range shifts in a changing climate, and estimated extinction rates for eight major parasite clades. On the basis of 53,133 occurrences capturing the geographic ranges of 457 parasite species, conservative model projections suggest that 5 to 10% of these species are committed to extinction by 2070 from climate-driven habitat loss alone. We find no evidence that parasites with zoonotic potential have a significantly higher potential to gain range in a changing climate, but we do find that ectoparasites (especially ticks) fare disproportionately worse than endoparasites. Accounting for host-driven coextinctions, models predict that up to 30% of parasitic worms are committed to extinction, driven by a combination of direct and indirect pressures. Despite high local extinction rates, parasite richness could still increase by an order of magnitude in some places, because species successfully tracking climate change invade temperate ecosystems and replace native species with unpredictable ecological consequences.

Emissions from prescribed burning of agricultural fields in the Pacific Northwest

Treesearch

A. L. Holder; B. K. Gullett; S. P. Urbanski; R. Elleman; S. O' Neill; D. Tabor; W. Mitchell; K. R. Baker

2017-01-01

Prescribed burns of winter wheat stubble and Kentucky bluegrass fields in northern Idaho and eastern Washington states (U.S.A.) were sampled using ground-, aerostat-, airplane-, and laboratory-based measurement platforms to determine emission factors, compare methods, and provide a current and comprehensive set of emissions data for air quality models, climate models,...

CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2015-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

The Implementation of the Full Service School Reform Model and Its Impact on Middle School Climate and Student Achievement: An Investigative Study

ERIC Educational Resources Information Center

Johnson, Joseph Hamilton

2012-01-01

The Full Service Schools (FSS) reform model is an inter-agency collaboration between the District of Columbia Public Schools (DCPS), Choices, Inc., Insights Education Group and the DC Department of Mental Health. This comprehensive school reform model is based in the Response to Intervention paradigm and is designed to mitigate student academic…

Comparing field- and model-based standing dead tree carbon stock estimates across forests of the US

Treesearch

Chistopher W. Woodall; Grant M. Domke; David W. MacFarlane; Christopher M. Oswalt

2012-01-01

As signatories to the United Nation Framework Convention on Climate Change, the US has been estimating standing dead tree (SDT) carbon (C) stocks using a model based on live tree attributes. The USDA Forest Service began sampling SDTs nationwide in 1999. With comprehensive field data now available, the objective of this study was to compare field- and model-based...

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Jiang, J. H.

2013-12-01

The latest Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with newly available global observations. The traditional approach to climate model evaluation, which compares a single parameter at a time, identifies symptomatic model biases and errors but fails to diagnose the model problems. The model diagnosis process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. To address these challenges, we are developing a parallel, distributed web-service system that enables the physics-based multi-variable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. We have developed a methodology to transform an existing science application code into a web service using a Python wrapper interface and Python web service frameworks (i.e., Flask, Gunicorn, and Tornado). The web-service system, called Climate Model Diagnostic Analyzer (CMDA), currently supports (1) all the datasets from Obs4MIPs and a few ocean datasets from NOAA and Argo, which can serve as observation-based reference data for model evaluation and (2) many of CMIP5 model outputs covering a broad range of atmosphere, ocean, and land variables from the CMIP5 specific historical runs and AMIP runs. Analysis capabilities currently supported by CMDA are (1) the calculation of annual and seasonal means of physical variables, (2) the calculation of time evolution of the means in any specified geographical region, (3) the calculation of correlation between two variables, and (4) the calculation of difference between two variables. A web user interface is chosen for CMDA because it not only lowers the learning curve and removes the adoption barrier of the tool but also enables instantaneous use, avoiding the hassle of local software installation and environment incompatibility. CMDA is planned to be used as an educational tool for the summer school organized by JPL's Center for Climate Science in 2014. The requirements of the educational tool are defined with the interaction with the school organizers, and CMDA is customized to meet the requirements accordingly. The tool needs to be production quality for 30+ simultaneous users. The summer school will thus serve as a valuable testbed for the tool development, preparing CMDA to serve the Earth-science modeling and model-analysis community at the end of the project. This work was funded by the NASA Earth Science Program called Computational Modeling Algorithms and Cyberinfrastructure (CMAC).

Comprehensive Representation of Hydrologic and Geomorphic Process Coupling in Numerical Models: Internal Dynamics and Basin Evolution

NASA Astrophysics Data System (ADS)

Istanbulluoglu, E.; Vivoni, E. R.; Ivanov, V. Y.; Bras, R. L.

2005-12-01

Landscape morphology has an important control on the spatial and temporal organization of basin hydrologic response to climate forcing, affecting soil moisture redistribution as well as vegetation function. On the other hand, erosion, driven by hydrology and modulated by vegetation, produces landforms over geologic time scales that reflect characteristic signatures of the dominant land forming process. Responding to extreme climate events or anthropogenic disturbances of the land surface, infrequent but rapid forms of erosion (e.g., arroyo development, landsliding) can modify topography such that basin hydrology is significantly influenced. Despite significant advances in both hydrologic and geomorphic modeling over the past two decades, the dynamic interactions between basin hydrology, geomorphology and terrestrial ecology are not adequately captured in current model frameworks. In order to investigate hydrologic-geomorphic-ecologic interactions at the basin scale we present initial efforts in integrating the CHILD landscape evolution model (Tucker et al. 2001) with the tRIBS hydrology model (Ivanov et al. 2004), both developed in a common software environment. In this talk, we present preliminary results of the numerical modeling of the coupled evolution of basin hydro-geomorphic response and resulting landscape morphology in two sets of examples. First, we discuss the long-term evolution of both the hydrologic response and the resulting basin morphology from an initially uplifted plateau. In the second set of modeling experiments, we implement changes in climate and land-use to an existing topography and compare basin hydrologic response to the model results when landscape form is fixed (e.g. no coupling between hydrology and geomorphology). Model results stress the importance of internal basin dynamics, including runoff generation mechanisms and hydrologic states, in shaping hydrologic response as well as the importance of employing comprehensive conceptualizations of hydrology in modeling landscape evolution.

Novel approaches to reducing uncertainty in regional climate predictions (Invited)

NASA Astrophysics Data System (ADS)

Ammann, C. M.

2009-12-01

Regional planning in preparation for future climate changes is rapidly gaining importance. However, compared to the global mean projections, correctly anticipating regional climate is often much more difficult, particularly with regard to hydrologic changes. The reason for the high, inherent uncertainty in location specific forecasts arises on one hand from the superposition of large internal variability in the atmosphere-ocean system on the more gradual changes. On the other hand, this problem is confounded by the fact that regional climate records are often short and therefore offer little guidance as to how an underlying trend can be identified within the noise. The use of indirect climate information (proxy records) from a host of natural archives has made significant progress recently. Based on an extended record, process studies can help reveal the regional response to changes in large scale climate that likely have to be expected. But in order to come up with robust, season and parameter specific (temperature versus moisture) climate reconstructions, comprehensive data compilations are needed that integrate proxy records of different characteristics, temporal representations, and different systematic and sampling uncertainties. Based on understanding of physical processes, and making explicit use of that knowledge, new dynamical and statistical techniques in paleoclimatology are being developed and explored. In addition to improved estimates of the past climate, the cascade of uncertainties is directly taken into account so that errors can more comprehensively be assessed. A brief overview of the problems and its potential implications for regional planning is followed by an application that demonstrates how collaboration between paleoclimatologists, climate modelers and statisticians can advance our understanding of the climate system and how agencies, businesses and individuals might be able to make better informed decisions in preparation for future climate.

The Impact of ENSO on Trace Gas Composition in the Upper Troposphere to Lower Stratosphere

NASA Technical Reports Server (NTRS)

Oman, Luke; Douglass, Anne; Ziemke, Jerry; Waugh, Darryn Warwick

2016-01-01

The El Nino-Southern Oscillation (ENSO) is the dominant mode of interannual variability in the tropical troposphere and its effects extend well into the stratosphere. Its impact on atmospheric dynamics and chemistry cause important changes to trace gas constituent distributions. A comprehensive suite of satellite observations, reanalyses, and chemistry climate model simulations are illuminating our understanding of processes like ENSO. Analyses of more than a decade of observations from NASAs Aura and Aqua satellites, combined with simulations from the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) and other Chemistry Climate Modeling Initiative (CCMI) models, and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis have provided key insights into the response of atmospheric composition to ENSO. While we will primarily focus on ozone and water vapor responses in the upper troposphere to lower stratosphere, the effects of ENSO ripple through many important trace gas species throughout the atmosphere. The very large 2015-2016 El Nino event provides an opportunity to closely examine these impacts with unprecedented observational breadth. An improved quantification of natural climate variations, like those from ENSO, is needed to detect and quantify anthropogenic climate changes.

Climate modelling of mass-extinction events: a review

NASA Astrophysics Data System (ADS)

Feulner, Georg

2009-07-01

Despite tremendous interest in the topic and decades of research, the origins of the major losses of biodiversity in the history of life on Earth remain elusive. A variety of possible causes for these mass-extinction events have been investigated, including impacts of asteroids or comets, large-scale volcanic eruptions, effects from changes in the distribution of continents caused by plate tectonics, and biological factors, to name but a few. Many of these suggested drivers involve or indeed require changes of Earth's climate, which then affect the biosphere of our planet, causing a global reduction in the diversity of biological species. It can be argued, therefore, that a detailed understanding of these climatic variations and their effects on ecosystems are prerequisites for a solution to the enigma of biological extinctions. Apart from investigations of the paleoclimate data of the time periods of mass extinctions, climate-modelling experiments should be able to shed some light on these dramatic events. Somewhat surprisingly, however, only a few comprehensive modelling studies of the climate changes associated with extinction events have been undertaken. These studies will be reviewed in this paper. Furthermore, the role of modelling in extinction research in general and suggestions for future research are discussed.

A Biome map for Modelling Global Mid-Pliocene Climate Change

NASA Astrophysics Data System (ADS)

Salzmann, U.; Haywood, A. M.

2006-12-01

The importance of vegetation-climate feedbacks was highlighted by several paleo-climate modelling exercises but their role as a boundary condition in Tertiary modelling has not been fully recognised or explored. Several paleo-vegetation datasets and maps have been produced for specific time slabs or regions for the Tertiary, but the vegetation classifications that have been used differ, thus making meaningful comparisons difficult. In order to facilitate further investigations into Tertiary climate and environmental change we are presently implementing the comprehensive GIS database TEVIS (Tertiary Environment and Vegetation Information System). TEVIS integrates marine and terrestrial vegetation data, taken from fossil pollen, leaf or wood, into an internally consistent classification scheme to produce for different time slabs global Tertiary Biome and Mega- Biome maps (Harrison & Prentice, 2003). In the frame of our ongoing 5-year programme we present a first global vegetation map for the mid-Pliocene time slab, a period of sustained global warmth. Data were synthesised from the PRISM data set (Thompson and Fleming 1996) after translating them to the Biome classification scheme and from new literature. The outcomes of the Biome map are compared with modelling results using an advanced numerical general circulation model (HadAM3) and the BIOME 4 vegetation model. Our combined proxy data and modelling approach will provide new palaeoclimate datasets to test models that are used to predict future climate change, and provide a more rigorous picture of climate and environmental changes during the Neogene.

Provider-agency fit in substance abuse treatment organizations: implications for learning climate, morale, and evidence-based practice implementation.

PubMed

Ramsey, Alex T; van den Berk-Clark, Carissa

2015-05-12

Substance abuse agencies have been slow to adopt and implement evidence-based practices (EBPs), due in part to poor provider morale and organizational climates that are not conducive to successful learning and integration of these practices. Person-organization fit theory suggests that alignment, or fit, between provider- and agency-level characteristics regarding the implementation of EBPs may influence provider morale and organizational learning climate and, thus, implementation success. The current study hypothesized that discrepancies, or lack of fit, between provider- and agency-level contextual factors would negatively predict provider morale and organizational learning climate, outcomes shown to be associated with successful EBP implementation. Direct service providers (n = 120) from four substance abuse treatment agencies responded to a survey involving provider morale, organizational learning climate, agency expectations for EBP use, agency resources for EBP use, and provider attitudes towards EBP use. Difference scores between combinations of provider- and agency-level factors were computed to model provider-agency fit. Quadratic regression analyses were conducted to more adequately and comprehensively model the level of the dependent variables across the entire "fit continuum". Discrepancies, or misfit, between agency expectations and provider attitudes and between agency resources and provider attitudes were associated with poorer provider morale and weaker organizational learning climate. For all hypotheses, the curvilinear model of provider-agency discrepancies significantly predicted provider morale and organizational learning climate, indicating that both directions of misfit (provider factors more favorable than agency factors, and vice-versa) were detrimental to morale and climate. However, outcomes were most negative when providers viewed EBPs favorably, but perceived that agency expectations and resources were less supportive of EBP use. The current research benefits from a strong theoretical framework, consistent findings, and significant practical implications for substance abuse treatment agencies. Comprehensive attempts to strengthen outcomes related to EBP implementation must consider both provider- and agency-level characteristics regarding EBP use. Organizational efforts to more closely align provider attitudes and agency priorities will likely constitute a key strategy in fostering the implementation of EBPs in substance abuse treatment organizations.

Applying a Comprehensive Contextual Climate Change Vulnerability Framework to New Zealand's Tourism Industry.

PubMed

Hopkins, Debbie

2015-03-01

Conceptualisations of 'vulnerability' vary amongst scholarly communities, contributing to a wide variety of applications. Research investigating vulnerability to climate change has often excluded non-climatic changes which may contribute to degrees of vulnerability perceived or experienced. This paper introduces a comprehensive contextual vulnerability framework which incorporates physical, social, economic and political factors which could amplify or reduce vulnerability. The framework is applied to New Zealand's tourism industry to explore its value in interpreting a complex, human-natural environment system with multiple competing vulnerabilities. The comprehensive contextual framework can inform government policy and industry decision making, integrating understandings of climate change within the broader context of internal and external social, physical, economic, and institutional stressors.

Projecting the Global Distribution of the Emerging Amphibian Fungal Pathogen, Batrachochytrium dendrobatidis, Based on IPCC Climate Futures

PubMed Central

Olson, Deanna H.; Blaustein, Andrew R.

2016-01-01

Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest) with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary), including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific) and also separately per region (region-specific). One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas, especially for sensitive species and those vulnerable to multiple threats. PMID:27513565

Assessment of hi-resolution multi-ensemble statistical downscaling regional climate scenarios over Japan

NASA Astrophysics Data System (ADS)

Dairaku, K.

2017-12-01

The Asia-Pacific regions are increasingly threatened by large scale natural disasters. Growing concerns that loss and damages of natural disasters are projected to further exacerbate by climate change and socio-economic change. Climate information and services for risk assessments are of great concern. Fundamental regional climate information is indispensable for understanding changing climate and making decisions on when and how to act. To meet with the needs of stakeholders such as National/local governments, spatio-temporal comprehensive and consistent information is necessary and useful for decision making. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 37 GCMs (RCP8.5) and a statistical downscaling (Bias Corrected Spatial Disaggregation (BCSD)) to investigate uncertainty of projected change associated with structural differences of the GCMs for the periods of historical climate (1950-2005) and near future climate (2026-2050). Statistical downscaling regional climate scenarios show good performance for annual and seasonal averages for precipitation and temperature. The regional climate scenarios show systematic underestimate of extreme events such as hot days of over 35 Celsius and annual maximum daily precipitation because of the interpolation processes in the BCSD method. Each model projected different responses in near future climate because of structural differences. The most of CMIP5 37 models show qualitatively consistent increase of average and extreme temperature and precipitation. The added values of statistical/dynamical downscaling methods are also investigated for locally forced nonlinear phenomena, extreme events.

Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990–2080

PubMed Central

Fischer, Günther; Shah, Mahendra; N. Tubiello, Francesco; van Velhuizen, Harrij

2005-01-01

A comprehensive assessment of the impacts of climate change on agro-ecosystems over this century is developed, up to 2080 and at a global level, albeit with significant regional detail. To this end an integrated ecological–economic modelling framework is employed, encompassing climate scenarios, agro-ecological zoning information, socio-economic drivers, as well as world food trade dynamics. Specifically, global simulations are performed using the FAO/IIASA agro-ecological zone model, in conjunction with IIASAs global food system model, using climate variables from five different general circulation models, under four different socio-economic scenarios from the intergovernmental panel on climate change. First, impacts of different scenarios of climate change on bio-physical soil and crop growth determinants of yield are evaluated on a 5′×5′ latitude/longitude global grid; second, the extent of potential agricultural land and related potential crop production is computed. The detailed bio-physical results are then fed into an economic analysis, to assess how climate impacts may interact with alternative development pathways, and key trends expected over this century for food demand and production, and trade, as well as key composite indices such as risk of hunger and malnutrition, are computed. This modelling approach connects the relevant bio-physical and socio-economic variables within a unified and coherent framework to produce a global assessment of food production and security under climate change. The results from the study suggest that critical impact asymmetries due to both climate and socio-economic structures may deepen current production and consumption gaps between developed and developing world; it is suggested that adaptation of agricultural techniques will be central to limit potential damages under climate change. PMID:16433094

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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.

Role of School Leadership and Climate in Student Achievement: The Mediating Role of Parental Involvement

ERIC Educational Resources Information Center

Alhosani, Abdulraheem Ali; Singh, Sanjay Kumar; Al Nahyan, Moza Tahnoon

2017-01-01

Purpose: The purpose of this paper is to develop a conceptual model on students' academic achievement that is well grounded in the academic research in the domain. The paper aims to weave together the divergent research findings into a comprehensive model for use by all the stakeholders. Design/methodology/approach: It is a literature review-based…

Climate change: evaluating your local and regional water resources

USGS Publications Warehouse

Flint, Lorraine E.; Flint, Alan L.; Thorne, James H.

2015-01-01

The BCM is a fine-scale hydrologic model that uses detailed maps of soils, geology, topography, and transient monthly or daily maps of potential evapotranspiration, air temperature, and precipitation to generate maps of recharge, runoff, snow pack, actual evapotranspiration, and climatic water deficit. With these comprehensive environmental inputs and experienced scientific analysis, the BCM provides resource managers with important hydrologic and ecologic understanding of a landscape or basin at hillslope to regional scales. The model is calibrated using historical climate and streamflow data over the range of geologic materials specific to an area. Once calibrated, the model is used to translate climate-change data into hydrologic responses for a defined landscape, to provide managers an understanding of potential ecological risks and threats to water supplies and managed hydrologic systems. Although limited to estimates of unimpaired hydrologic conditions, estimates of impaired conditions, such as agricultural demand, diversions, or reservoir outflows can be incorporated into the calibration of the model to expand its utility. Additionally, the model can be linked to other models, such as groundwater-flow models (that is, MODFLOW) or the integrated hydrologic model (MF-FMP), to provide information about subsurface hydrologic processes. The model can be applied at a relatively small scale, but also can be applied to large-scale national and international river basins.

The impact of equilibrating hemispheric albedos on tropical performance in the HadGEM2-ES coupled climate model

DOE PAGES

Haywood, Jim M.; Jones, Andy; Dunstone, Nick; ...

2016-01-14

Despite the fact that the southern hemisphere contains a far greater proportion of dark ocean than the northern hemisphere, the total amount of sunlight reflected from the hemispheres is equal. However, the majority of climate models do not adequately represent this equivalence. Here we examine the impact of equilibrating hemispheric albedos by various idealised methods in a comprehensive coupled climate model and find significant improvements in what have been considered longstanding and apparently intractable model biases. Monsoon precipitation biases almost vanish over all continental land areas, the penetration of monsoon rainfall across the Sahel and the west African monsoon “jump”more » become well represented, and indicators of hurricane frequency are significantly improved. The results appear not to be model specific, implying that hemispheric albedo equivalence may provide a fundamental constraint for climate models that must be satisfied if the dynamics driving these processes, in particular the strength of the Hadley cell, are to be adequately represented. Cross-equatorial energy transport is implicated as a crucial component that must be accurately modelled in coupled general circulation models. The results also suggest that the commonly used practice of prescribing sea-surface temperatures in models provides a less accurate represention of precipitation than constraining the hemispheric albedos.« less

Paleoclimates: Understanding climate change past and present

USGS Publications Warehouse

Cronin, Thomas M.

2010-01-01

The field of paleoclimatology relies on physical, chemical, and biological proxies of past climate changes that have been preserved in natural archives such as glacial ice, tree rings, sediments, corals, and speleothems. Paleoclimate archives obtained through field investigations, ocean sediment coring expeditions, ice sheet coring programs, and other projects allow scientists to reconstruct climate change over much of earth's history. When combined with computer model simulations, paleoclimatic reconstructions are used to test hypotheses about the causes of climatic change, such as greenhouse gases, solar variability, earth's orbital variations, and hydrological, oceanic, and tectonic processes. This book is a comprehensive, state-of-the art synthesis of paleoclimate research covering all geological timescales, emphasizing topics that shed light on modern trends in the earth's climate. Thomas M. Cronin discusses recent discoveries about past periods of global warmth, changes in atmospheric greenhouse gas concentrations, abrupt climate and sea-level change, natural temperature variability, and other topics directly relevant to controversies over the causes and impacts of climate change. This text is geared toward advanced undergraduate and graduate students and researchers in geology, geography, biology, glaciology, oceanography, atmospheric sciences, and climate modeling, fields that contribute to paleoclimatology. This volume can also serve as a reference for those requiring a general background on natural climate variability.

Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects

NASA Astrophysics Data System (ADS)

Hong, Chaopeng; Zhang, Qiang; Zhang, Yang; Tang, Youhua; Tong, Daniel; He, Kebin

2017-06-01

In this study, a regional coupled climate-chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional two-way coupled Weather Research and Forecasting - Community Multi-scale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over east Asia for a multi-year climatological application during 2006-2010, driven with CESM downscaling data under Representative Concentration Pathways 4.5 (RCP4.5), along with a short-term air quality application in representative months in 2013 that was driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the two-way coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2 m temperature (T2) in this study (with a mean bias of -0.6 °C) compared with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2. 5 in winter (with a normalized mean bias (NMB) of 6.4 % in 2013) and O3 in summer (with an NMB of 18.2 % in 2013) in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2. 5 concentrations in China, WRF-CMAQ was able to capture the high PM2. 5 concentrations in urban areas. In general, the two-way coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled modeling system with direct aerosol feedbacks predicted aerosol optical depth relatively well and significantly reduced the overprediction in downward shortwave radiation at the surface (SWDOWN) over polluted regions in China. The performance of cloud variables was not as good as other meteorological variables, and underpredictions of cloud fraction resulted in overpredictions of SWDOWN and underpredictions of shortwave and longwave cloud forcing. The importance of climate-chemistry interactions was demonstrated via the impacts of aerosol direct effects on climate and air quality. The aerosol effects on climate and air quality in east Asia (e.g., SWDOWN and T2 decreased by 21.8 W m-2 and 0.45 °C, respectively, and most pollutant concentrations increased by 4.8-9.5 % in January over China's major cities) were more significant than in other regions because of higher aerosol loadings that resulted from severe regional pollution, which indicates the need for applying online-coupled models over east Asia for regional climate and air quality modeling and to study the important climate-chemistry interactions. This work established a baseline for WRF-CMAQ simulations for a future period under the RCP4.5 climate scenario, which will be presented in a future paper.

Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data

PubMed Central

Scanlon, Bridget R.; Zhang, Zizhan; Save, Himanshu; Sun, Alexander Y.; van Beek, Ludovicus P. H.; Wiese, David N.; Reedy, Robert C.; Longuevergne, Laurent; Döll, Petra; Bierkens, Marc F. P.

2018-01-01

Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002–2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤−0.5 km3/y) and increasing (≥0.5 km3/y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km3/y, whereas most models estimate decreasing trends (−71 to 11 km3/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km3/y) but negative for models (−450 to −12 km3/y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated. PMID:29358394

Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data.

PubMed

Scanlon, Bridget R; Zhang, Zizhan; Save, Himanshu; Sun, Alexander Y; Müller Schmied, Hannes; van Beek, Ludovicus P H; Wiese, David N; Wada, Yoshihide; Long, Di; Reedy, Robert C; Longuevergne, Laurent; Döll, Petra; Bierkens, Marc F P

2018-02-06

Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002-2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤-0.5 km 3 /y) and increasing (≥0.5 km 3 /y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km 3 /y, whereas most models estimate decreasing trends (-71 to 11 km 3 /y). Land water storage trends, summed over all basins, are positive for GRACE (∼71-82 km 3 /y) but negative for models (-450 to -12 km 3 /y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated. Copyright © 2018 the Author(s). Published by PNAS.

Parasite biodiversity faces extinction and redistribution in a changing climate

PubMed Central

Carlson, Colin J.; Burgio, Kevin R.; Dougherty, Eric R.; Phillips, Anna J.; Bueno, Veronica M.; Clements, Christopher F.; Castaldo, Giovanni; Dallas, Tad A.; Cizauskas, Carrie A.; Cumming, Graeme S.; Doña, Jorge; Harris, Nyeema C.; Jovani, Roger; Mironov, Sergey; Muellerklein, Oliver C.; Proctor, Heather C.; Getz, Wayne M.

2017-01-01

Climate change is a well-documented driver of both wildlife extinction and disease emergence, but the negative impacts of climate change on parasite diversity are undocumented. We compiled the most comprehensive spatially explicit data set available for parasites, projected range shifts in a changing climate, and estimated extinction rates for eight major parasite clades. On the basis of 53,133 occurrences capturing the geographic ranges of 457 parasite species, conservative model projections suggest that 5 to 10% of these species are committed to extinction by 2070 from climate-driven habitat loss alone. We find no evidence that parasites with zoonotic potential have a significantly higher potential to gain range in a changing climate, but we do find that ectoparasites (especially ticks) fare disproportionately worse than endoparasites. Accounting for host-driven coextinctions, models predict that up to 30% of parasitic worms are committed to extinction, driven by a combination of direct and indirect pressures. Despite high local extinction rates, parasite richness could still increase by an order of magnitude in some places, because species successfully tracking climate change invade temperate ecosystems and replace native species with unpredictable ecological consequences. PMID:28913417

Climate-Driven Risk of Large Fire Occurrence in the Western United States, 1500 to 2003

NASA Astrophysics Data System (ADS)

Crockett, J.; Westerling, A. L.

2017-12-01

Spatially comprehensive fire climatology has provided managers with tools to understand thecauses and consequences of large forest wildfires, but a paleoclimate context is necessary foranticipating the trajectory of future climate-fire relationships. Although accumulated charcoalrecords and tree scars have been utilized in high resolution, regional fire reconstructions, there isuncertainty as to how current climate-fire relationships of the western United States (WUS) fitwithin the natural long-term variability. While contemporary PDSI falls within the naturalvariability of the past, contemporary temperatures skew higher. Here, we develop a WUSfire reconstruction by applying climate-fire-topography model built on the 1972 to 2003 periodto the past 500 years, validated by recently updated fire-scar histories from WUS forests. Theresultant narrative provides insight into changing climate-fire relationships during extendedperiods of high aridity and temperature, providing land managers with historical precedent toeffectively anticipate disturbances during future climate change.

Agricultural Adaptations to Climate Changes in West Africa

NASA Astrophysics Data System (ADS)

Guan, K.; Sultan, B.; Lobell, D. B.; Biasutti, M.; Piani, C.; Hammer, G. L.; McLean, G.

2014-12-01

Agricultural production in West Africa is highly vulnerable to climate variability and change and a fast growing demand for food adds yet another challenge. Assessing possible adaptation strategies of crop production in West Africa under climate change is thus critical for ensuring regional food security and improving human welfare. Our previous efforts have identified as the main features of climate change in West Africa a robust increase in temperature and a complex shift in the rainfall pattern (i.e. seasonality delay and total amount change). Unaddressed, these robust climate changes would reduce regional crop production by up to 20%. In the current work, we use two well-validated crop models (APSIM and SARRA-H) to comprehensively assess different crop adaptation options under future climate scenarios. Particularly, we assess adaptations in both the choice of crop types and management strategies. The expected outcome of this study is to provide West Africa with region-specific adaptation recommendations that take into account both climate variability and climate change.

Climate change and Ixodes tick-borne diseases of humans

PubMed Central

Ostfeld, Richard S.; Brunner, Jesse L.

2015-01-01

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

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.

Reality of using a model from local governments' perspective-How science community can help?

NASA Astrophysics Data System (ADS)

Mirzazad, S.

2016-12-01

Local governments across the US use historic data to approve capital improvement projects and update comprehensive/zoning plans. Due to the effects of climate change, historic data sets are no longer suitable, which requires communities to use climate models to project the future. However, the use of climate models also presents challenges for local governments such as: Variations between models: Because model-development methodologies vary, different climate models provide different end results. A local governments' decision concerning which climate model to use is tricky because the model drives policy direction and infrastructure investments that can be both expensive and controversial. Communicating the gaps of a model: There are always uncertainties associated with modeling. These gaps may range from the scale of a model to the type of data used in modeling. Effectively communicating this to a community is crucial to gain political support. Managing politics associated with using a model: In many cases, models project changes to the built environment that will detrimentally affect private property owners. This can result in strong push back from the community and could threaten the local tax base. Scientists have important roles; from development to delivery of models to assisting local governments navigate through these challenges. Bringing in entities with experience of working with local governments can contribute to a successful outcome. In this proposed session, ICLEI-Local Governments for Sustainability will use the USGS CoSMoS as a case study for lessons learned in establishing a framework for effective collaboration between local governments and the science community.

NOAA's State Climate Summaries for the National Climate Assessment: A Sustained Assessment Product

NASA Astrophysics Data System (ADS)

Kunkel, K.; Champion, S.; Frankson, R.; Easterling, D. R.; Griffin, J.; Runkle, J. D.; Stevens, L. E.; Stewart, B. C.; Sun, L.; Veasey, S.

2016-12-01

A set of State Climate Summaries have been produced for all 50 U.S. states as part of the National Climate Assessment Sustained Assessment and represent a NOAA contribution to this process. Each summary includes information on observed and projected climate change conditions and impacts associated with future greenhouse gas emissions pathways. The summaries focus on the physical climate and coastal issues as a part of NOAA's mission. Core climate data and simulations used to produce these summaries have been previously published, and have been analyzed to represent a targeted synthesis of historical and plausible future climate conditions. As these are intended to be supplemental to major climate assessment development, the scope of the content remains true to a "summary" style document. Each state's Climate Summary includes its climatology and projections of future temperatures and precipitation, which are presented in order to provide a context for the assessment of future impacts. The climatological component focuses on temperature, precipitation, and noteworthy weather events specific to each state and relevant to the climate change discussion. Future climate scenarios are also briefly discussed, using well-known and consistent sets of climate model simulations based on two possible futures of greenhouse gas emissions. These future scenarios present an internally consistent climate picture for every state and are intended to inform the potential impacts of climate change. These 50 State Climate Summaries were produced by NOAA's National Centers for Environmental Information (NCEI) and the North Carolina State University Cooperative Institute for Climate and Satellites - NC (CICS-NC) with additional input provided by climate experts, including the NOAA Regional Climate Centers and State Climatologists. Each summary document also underwent a comprehensive and anonymous peer review. Each summary contains text, figures, and an interactive web presentation. A full suite of the comprehensive analyses and metadata are also available. The audience is targeted as both decision-makers and informed non-scientists. This presentation will discuss the scientific development for the project, demonstrate the suite of information, and provide examples of noteworthy figures from select states.

Land-use change trajectories up to 2050. Insights from a global agro-economic model comparison

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

Schmitz, Christoph; van Meijl, Hans; Kyle, G. Page

Changes in agricultural land use have important implications for environmental services. Previous studies of agricultural land-use futures have been published indicating large uncertainty due to different model assumptions and methodologies. In this article we present a first comprehensive comparison of global agro-economic models that have harmonized drivers of population, GDP, and biophysical yields. The comparison allows us to ask two research questions: (1) How much cropland will be used under different socioeconomic and climate change scenarios? (2) How can differences in model results be explained? The comparison includes four partial and six general equilibrium models that differ in how theymore » model land supply and amount of potentially available land. We analyze results of two different socioeconomic scenarios and three climate scenarios (one with constant climate). Most models (7 out of 10) project an increase of cropland of 10–25% by 2050 compared to 2005 (under constant climate), but one model projects a decrease. Pasture land expands in some models, which increase the treat on natural vegetation further. Across all models most of the cropland expansion takes place in South America and sub-Saharan Africa. In general, the strongest differences in model results are related to differences in the costs of land expansion, the endogenous productivity responses, and the assumptions about potential cropland.« less

Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)

NASA Astrophysics Data System (ADS)

Dethloff, Klaus; Rex, Markus; Shupe, Matthew

2016-04-01

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) is an international initiative under the International Arctic Science Committee (IASC) umbrella that aims to improve numerical model representations of sea ice, weather, and climate processes through coupled system observations and modeling activities that link the central Arctic atmosphere, sea ice, ocean, and the ecosystem. Observations of many critical parameters such as cloud properties, surface energy fluxes, atmospheric aerosols, small-scale sea-ice and oceanic processes, biological feedbacks with the sea-ice ice and ocean, and others have never been made in the central Arctic in all seasons, and certainly not in a coupled system fashion. The primary objective of MOSAiC is to develop a better understanding of these important coupled-system processes so they can be more accurately represented in regional- and global-scale weather- and climate models. Such enhancements will contribute to improved modeling of global climate and weather, and Arctic sea-ice predictive capabilities. The MOSAiC observations are an important opportunity to gather the high quality and comprehensive observations needed to improve numerical modeling of critical, scale-dependent processes impacting Arctic predictability given diminished sea ice coverage and increased model complexity. Model improvements are needed to understand the effects of a changing Arctic on mid-latitude weather and climate. MOSAiC is specifically designed to provide the multi-parameter, coordinated observations needed to improve sub-grid scale model parameterizations especially with respect to thinner ice conditions. To facilitate, evaluate, and develop the needed model improvements, MOSAiC will employ a hierarchy of modeling approaches ranging from process model studies, to regional climate model intercomparisons, to operational forecasts and assimilation of real-time observations. Model evaluations prior to the field program will be used to identify specific gaps and parameterization needs. Preliminary modeling and operational forecasting will also be necessary to directly guide field planning and optimal implementation of field resources, and to support the safety of the project. The MOSAiC Observatory will be deployed in, and drift with, the Arctic sea-ice pack for at least a full annual cycle, starting in fall 2019 and ending in autumn 2020. Initial plans are for the drift to start in the newly forming autumn sea-ice in, or near, the East Siberian Sea. The specific location will be selected to allow for the observatory to follow the Transpolar Drift towards the North Pole and on to the Fram Strait. IASC has adopted MOSAiC as a key international activity, the German Alfred Wegener Institute has made the huge contribution of the icebreaker Polarstern to serve as the central drifting observatory for this year long endeavor, and the US Department of Energy has committed a comprehensive atmospheric measurement suite. Many other nations and agencies have expressed interest in participation and in gaining access to this unprecedented observational dataset. International coordination is needed to support this groundbreaking endeavor.

A physically-based approach of treating dust-water cloud interactions in climate models

NASA Astrophysics Data System (ADS)

Kumar, P.; Karydis, V.; Barahona, D.; Sokolik, I. N.; Nenes, A.

2011-12-01

All aerosol-cloud-climate assessment studies to date assume that the ability of dust (and other insoluble species) to act as a Cloud Condensation Nuclei (CCN) is determined solely by their dry size and amount of soluble material. Recent evidence however clearly shows that dust can act as efficient CCN (even if lacking appreciable amounts of soluble material) through adsorption of water vapor onto the surface of the particle. This "inherent" CCN activity is augmented as the dust accumulates soluble material through atmospheric aging. A comprehensive treatment of dust-cloud interactions therefore requires including both of these sources of CCN activity in atmospheric models. This study presents a "unified" theory of CCN activity that considers both effects of adsorption and solute. The theory is corroborated and constrained with experiments of CCN activity of mineral aerosols generated from clays, calcite, quartz, dry lake beds and desert soil samples from Northern Africa, East Asia/China, and Northern America. The unified activation theory then is included within the mechanistic droplet activation parameterization of Kumar et al. (2009) (including the giant CCN correction of Barahona et al., 2010), for a comprehensive treatment of dust impacts on global CCN and cloud droplet number. The parameterization is demonstrated with the NASA Global Modeling Initiative (GMI) Chemical Transport Model using wind fields computed with the Goddard Institute for Space Studies (GISS) general circulation model. References Barahona, D. et al. (2010) Comprehensively Accounting for the Effect of Giant CCN in Cloud Activation Parameterizations, Atmos.Chem.Phys., 10, 2467-2473 Kumar, P., I.N. Sokolik, and A. Nenes (2009), Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN, Atmos.Chem.Phys., 9, 2517- 2532

Assessing the Added Value of Dynamical Downscaling in the Context of Hydrologic Implication

NASA Astrophysics Data System (ADS)

Lu, M.; IM, E. S.; Lee, M. H.

2017-12-01

There is a scientific consensus that high-resolution climate simulations downscaled by Regional Climate Models (RCMs) can provide valuable refined information over the target region. However, a significant body of hydrologic impact assessment has been performing using the climate information provided by Global Climate Models (GCMs) in spite of a fundamental spatial scale gap. It is probably based on the assumption that the substantial biases and spatial scale gap from GCMs raw data can be simply removed by applying the statistical bias correction and spatial disaggregation. Indeed, many previous studies argue that the benefit of dynamical downscaling using RCMs is minimal when linking climate data with the hydrological model, from the comparison of the impact between bias-corrected GCMs and bias-corrected RCMs on hydrologic simulations. It may be true for long-term averaged climatological pattern, but it is not necessarily the case when looking into variability across various temporal spectrum. In this study, we investigate the added value of dynamical downscaling focusing on the performance in capturing climate variability. For doing this, we evaluate the performance of the distributed hydrological model over the Korean river basin using the raw output from GCM and RCM, and bias-corrected output from GCM and RCM. The impacts of climate input data on streamflow simulation are comprehensively analyzed. [Acknowledgements]This research is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 17AWMP-B083066-04).

Comparison of three ice cloud optical schemes in climate simulations with community atmospheric model version 5

NASA Astrophysics Data System (ADS)

Zhao, Wenjie; Peng, Yiran; Wang, Bin; Yi, Bingqi; Lin, Yanluan; Li, Jiangnan

2018-05-01

A newly implemented Baum-Yang scheme for simulating ice cloud optical properties is compared with existing schemes (Mitchell and Fu schemes) in a standalone radiative transfer model and in the global climate model (GCM) Community Atmospheric Model Version 5 (CAM5). This study systematically analyzes the effect of different ice cloud optical schemes on global radiation and climate by a series of simulations with a simplified standalone radiative transfer model, atmospheric GCM CAM5, and a comprehensive coupled climate model. Results from the standalone radiative model show that Baum-Yang scheme yields generally weaker effects of ice cloud on temperature profiles both in shortwave and longwave spectrum. CAM5 simulations indicate that Baum-Yang scheme in place of Mitchell/Fu scheme tends to cool the upper atmosphere and strengthen the thermodynamic instability in low- and mid-latitudes, which could intensify the Hadley circulation and dehydrate the subtropics. When CAM5 is coupled with a slab ocean model to include simplified air-sea interaction, reduced downward longwave flux to surface in Baum-Yang scheme mitigates ice-albedo feedback in the Arctic as well as water vapor and cloud feedbacks in low- and mid-latitudes, resulting in an overall temperature decrease by 3.0/1.4 °C globally compared with Mitchell/Fu schemes. Radiative effect and climate feedback of the three ice cloud optical schemes documented in this study can be referred for future improvements on ice cloud simulation in CAM5.

Projected 21st century coastal flooding in the Southern California Bight. Part 1: Development of the third generation CoSMoS model

USGS Publications Warehouse

O'Neill, Andrea; Erikson, Li; Barnard, Patrick; Limber, Patrick; Vitousek, Sean; Warrick, Jonathan; Foxgrover, Amy C.; Lovering, Jessica

2018-01-01

Due to the effects of climate change over the course of the next century, the combination of rising sea levels, severe storms, and coastal change will threaten the sustainability of coastal communities, development, and ecosystems as we know them today. To clearly identify coastal vulnerabilities and develop appropriate adaptation strategies due to projected increased levels of coastal flooding and erosion, coastal managers need local-scale hazards projections using the best available climate and coastal science. In collaboration with leading scientists world-wide, the USGS designed the Coastal Storm Modeling System (CoSMoS) to assess the coastal impacts of climate change for the California coast, including the combination of sea-level rise, storms, and coastal change. In this project, we directly address the needs of coastal resource managers in Southern California by integrating a vast range of global climate change projections in a thorough and comprehensive numerical modeling framework. In Part 1 of a two-part submission on CoSMoS, methods and the latest improvements are discussed, and an example of hazard projections is presented.

Enhanced poleward propagation of storms under climate change

NASA Astrophysics Data System (ADS)

Tamarin-Brodsky, Talia; Kaspi, Yohai

2017-12-01

Earth's midlatitudes are dominated by regions of large atmospheric weather variability—often referred to as storm tracks— which influence the distribution of temperature, precipitation and wind in the extratropics. Comprehensive climate models forced by increased greenhouse gas emissions suggest that under global warming the storm tracks shift poleward. While the poleward shift is a robust response across most models, there is currently no consensus on what the underlying dynamical mechanism is. Here we present a new perspective on the poleward shift, which is based on a Lagrangian view of the storm tracks. We show that in addition to a poleward shift in the genesis latitude of the storms, associated with the shift in baroclinicity, the latitudinal displacement of cyclonic storms increases under global warming. This is achieved by applying a storm-tracking algorithm to an ensemble of CMIP5 models. The increased latitudinal propagation in a warmer climate is shown to be a result of stronger upper-level winds and increased atmospheric water vapour. These changes in the propagation characteristics of the storms can have a significant impact on midlatitude climate.

Data Management System for the National Energy-Water System (NEWS) Assessment Framework

NASA Astrophysics Data System (ADS)

Corsi, F.; Prousevitch, A.; Glidden, S.; Piasecki, M.; Celicourt, P.; Miara, A.; Fekete, B. M.; Vorosmarty, C. J.; Macknick, J.; Cohen, S. M.

2015-12-01

Aiming at providing a comprehensive assessment of the water-energy nexus, the National Energy-Water System (NEWS) project requires the integration of data to support a modeling framework that links climate, hydrological, power production, transmission, and economical models. Large amounts of Georeferenced data has to be streamed to the components of the inter-disciplinary model to explore future challenges and tradeoffs in the US power production, based on climate scenarios, power plant locations and technologies, available water resources, ecosystem sustainability, and economic demand. We used open source and in-house build software components to build a system that addresses two major data challenges: On-the-fly re-projection, re-gridding, interpolation, extrapolation, nodata patching, merging, temporal and spatial aggregation, of static and time series datasets in virtually any file formats and file structures, and any geographic extent for the models I/O, directly at run time; Comprehensive data management based on metadata cataloguing and discovery in repositories utilizing the MAGIC Table (Manipulation and Geographic Inquiry Control database). This innovative concept allows models to access data on-the-fly by data ID, irrespective of file path, file structure, file format and regardless its GIS specifications. In addition, a web-based information and computational system is being developed to control the I/O of spatially distributed Earth system, climate, and hydrological, power grid, and economical data flow within the NEWS framework. The system allows scenario building, data exploration, visualization, querying, and manipulation any loaded gridded, point, and vector polygon dataset. The system has demonstrated its potential for applications in other fields of Earth science modeling, education, and outreach. Over time, this implementation of the system will provide near real-time assessment of various current and future scenarios of the water-energy nexus.

Carbon dioxide and climate: a second assessment

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

Not Available

For over a century, concern has been expressed that increases in atmospheric carbon dioxide (CO/sub 2/) concentration could affect global climate by changing the heat balance of the atmosphere and Earth. Observations reveal steadily increasing concentrations of CO/sub 2/, and experiments with numerical climate models indicate that continued increase would eventually produce significant climatic change. Comprehensive assessment of the issue will require projection of future CO/sub 2/ emissions and study of the disposition of this excess carbon in the atmosphere, ocean, and biota; the effect on climate; and the implications for human welfare. This study focuses on one aspect, estimationmore » of the effect on climate of assumed future increases in atmospheric CO/sub 2/. Conclusions are drawn principally from present-day numerical models of the climate system. To address the significant role of the oceans, the study also makes use of observations of the distributions of anthropogenic tracers other than CO/sub 2/. The rapid scientific developments in these areas suggest that periodic reassessments will be warranted. The starting point for the study was a similar 1979 review by a Climate Research Board panel chaired by the late Jule G. Charney. The present study has not found any new results that necessitate substantial revision of the conclusions of the Charney report.« less

Global warming not so harmful for all plants - response of holomycotrophic orchid species for the future climate change.

PubMed

Kolanowska, Marta; Kras, Marta; Lipińska, Monika; Mystkowska, Katarzyna; Szlachetko, Dariusz L; Naczk, Aleksandra M

2017-10-05

Current and expected changes in global climate are major threat for biological diversity affecting individuals, communities and ecosystems. However, there is no general trend in the plants response to the climate change. The aim of present study was to evaluate impact of the future climate changes on the distribution of holomycotrophic orchid species using ecological niche modeling approach. Three different scenarios of future climate changes were tested to obtain the most comprehensive insight in the possible habitat loss of 16 holomycotrophic orchids. The extinction of Cephalanthera austiniae was predicted in all analyses. The coverage of suitable niches of Pogoniopsis schenckii will decrease to 1-30% of its current extent. The reduction of at least 50% of climatic niche of Erythrorchis cassythoides and Limodorum abortivum will be observed. In turn, the coverage of suitable niches of Hexalectris spicata, Uleiorchis ulaei and Wullschlaegelia calcarata may be even 16-74 times larger than in the present time. The conducted niche modeling and analysis of the similarity of their climatic tolerance showed instead that the future modification of the coverage of their suitable niches will not be unified and the future climate changes may be not so harmful for holomycotrophic orchids as expected.

NCPP's Use of Standard Metadata to Promote Open and Transparent Climate Modeling

NASA Astrophysics Data System (ADS)

Treshansky, A.; Barsugli, J. J.; Guentchev, G.; Rood, R. B.; DeLuca, C.

2012-12-01

The National Climate Predictions and Projections (NCPP) Platform is developing comprehensive regional and local information about the evolving climate to inform decision making and adaptation planning. This includes both creating and providing tools to create metadata about the models and processes used to create its derived data products. NCPP is using the Common Information Model (CIM), an ontology developed by a broad set of international partners in climate research, as its metadata language. This use of a standard ensures interoperability within the climate community as well as permitting access to the ecosystem of tools and services emerging alongside the CIM. The CIM itself is divided into a general-purpose (UML & XML) schema which structures metadata documents, and a project or community-specific (XML) Controlled Vocabulary (CV) which constraints the content of metadata documents. NCPP has already modified the CIM Schema to accommodate downscaling models, simulations, and experiments. NCPP is currently developing a CV for use by the downscaling community. Incorporating downscaling into the CIM will lead to several benefits: easy access to the existing CIM Documents describing CMIP5 models and simulations that are being downscaled, access to software tools that have been developed in order to search, manipulate, and visualize CIM metadata, and coordination with national and international efforts such as ES-DOC that are working to make climate model descriptions and datasets interoperable. Providing detailed metadata descriptions which include the full provenance of derived data products will contribute to making that data (and, the models and processes which generated that data) more open and transparent to the user community.

Tuning a climate model using nudging to reanalysis.

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Understanding the Changes in Global Crop Yields Through Changes in Climate and Technology

NASA Astrophysics Data System (ADS)

Najafi, Ehsan; Devineni, Naresh; Khanbilvardi, Reza M.; Kogan, Felix

2018-03-01

During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

Improved Analysis of Earth System Models and Observations using Simple Climate Models

NASA Astrophysics Data System (ADS)

Nadiga, B. T.; Urban, N. M.

2016-12-01

Earth system models (ESM) are the most comprehensive tools we have to study climate change and develop climate projections. However, the computational infrastructure required and the cost incurred in running such ESMs precludes direct use of such models in conjunction with a wide variety of tools that can further our understanding of climate. Here we are referring to tools that range from dynamical systems tools that give insight into underlying flow structure and topology to tools that come from various applied mathematical and statistical techniques and are central to quantifying stability, sensitivity, uncertainty and predictability to machine learning tools that are now being rapidly developed or improved. Our approach to facilitate the use of such models is to analyze output of ESM experiments (cf. CMIP) using a range of simpler models that consider integral balances of important quantities such as mass and/or energy in a Bayesian framework.We highlight the use of this approach in the context of the uptake of heat by the world oceans in the ongoing global warming. Indeed, since in excess of 90% of the anomalous radiative forcing due greenhouse gas emissions is sequestered in the world oceans, the nature of ocean heat uptake crucially determines the surface warming that is realized (cf. climate sensitivity). Nevertheless, ESMs themselves are never run long enough to directly assess climate sensitivity. So, we consider a range of models based on integral balances--balances that have to be realized in all first-principles based models of the climate system including the most detailed state-of-the art climate simulations. The models range from simple models of energy balance to those that consider dynamically important ocean processes such as the conveyor-belt circulation (Meridional Overturning Circulation, MOC), North Atlantic Deep Water (NADW) formation, Antarctic Circumpolar Current (ACC) and eddy mixing. Results from Bayesian analysis of such models using both ESM experiments and actual observations are presented. One such result points to the importance of direct sequestration of heat below 700 m, a process that is not allowed for in the simple models that have been traditionally used to deduce climate sensitivity.

VALUE - A Framework to Validate Downscaling Approaches for Climate Change Studies

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutiérrez, José M.; Kotlarski, Sven; Chandler, Richard E.; Hertig, Elke; Wibig, Joanna; Huth, Radan; Wilke, Renate A. I.

2015-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. Here, we present the key ingredients of this framework. VALUE's main approach to validation is user-focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.

VALUE: A framework to validate downscaling approaches for climate change studies

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutiérrez, José M.; Kotlarski, Sven; Chandler, Richard E.; Hertig, Elke; Wibig, Joanna; Huth, Radan; Wilcke, Renate A. I.

2015-01-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. In this paper, we present the key ingredients of this framework. VALUE's main approach to validation is user- focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.

Backscatter modelling and inversion from Cassini/SAR data: Implications for Titan's sand seas properties and climatic conditions

NASA Astrophysics Data System (ADS)

Lucas, A.; Rodriguez, S.; Lemonnier, F.; Paillou, P.; Le Gall, A. A.; Narteau, C.

2015-12-01

Sand seas on Titan may reflect the present and past climatic conditions. Understanding the morphodynamics and physicochemical properties of Titan's dunes is therefore essential for a better comprehension of the climatic and geological history of the largest Saturn's moon. We derived quantitatively surface properties (texture, composition) from the modelling of microwave backscattered signal and Monte Carlo inversion of despeckled Cassini/SAR data over the equatorial sand seas. We show that dunes and inter-dunes have significantly different physical properties. Absorption is more efficient in the dunes compared to the inter-dunes. The inter-dunes are smoother with an higher dielectric constant than the dunes. Considering the composition, the inter-dunes are in between the dunes and the bright inselbergs, suggesting the presence of a shallow layer of sediment in between the dunes. Additionally potential secondary bedforms may have been detected. Implications for dune morphodynamics, sediment inventory and climatic conditions occurring on Titan will be discussed.

Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5

NASA Astrophysics Data System (ADS)

Dufresne, J.-L.; Foujols, M.-A.; Denvil, S.; Caubel, A.; Marti, O.; Aumont, O.; Balkanski, Y.; Bekki, S.; Bellenger, H.; Benshila, R.; Bony, S.; Bopp, L.; Braconnot, P.; Brockmann, P.; Cadule, P.; Cheruy, F.; Codron, F.; Cozic, A.; Cugnet, D.; de Noblet, N.; Duvel, J.-P.; Ethé, C.; Fairhead, L.; Fichefet, T.; Flavoni, S.; Friedlingstein, P.; Grandpeix, J.-Y.; Guez, L.; Guilyardi, E.; Hauglustaine, D.; Hourdin, F.; Idelkadi, A.; Ghattas, J.; Joussaume, S.; Kageyama, M.; Krinner, G.; Labetoulle, S.; Lahellec, A.; Lefebvre, M.-P.; Lefevre, F.; Levy, C.; Li, Z. X.; Lloyd, J.; Lott, F.; Madec, G.; Mancip, M.; Marchand, M.; Masson, S.; Meurdesoif, Y.; Mignot, J.; Musat, I.; Parouty, S.; Polcher, J.; Rio, C.; Schulz, M.; Swingedouw, D.; Szopa, S.; Talandier, C.; Terray, P.; Viovy, N.; Vuichard, N.

2013-05-01

We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

A review of multi-risk methodologies for natural hazards: Consequences and challenges for a climate change impact assessment.

PubMed

Gallina, Valentina; Torresan, Silvia; Critto, Andrea; Sperotto, Anna; Glade, Thomas; Marcomini, Antonio

2016-03-01

This paper presents a review of existing multi-risk assessment concepts and tools applied by organisations and projects providing the basis for the development of a multi-risk methodology in a climate change perspective. Relevant initiatives were developed for the assessment of multiple natural hazards (e.g. floods, storm surges, droughts) affecting the same area in a defined timeframe (e.g. year, season, decade). Major research efforts were focused on the identification and aggregation of multiple hazard types (e.g. independent, correlated, cascading hazards) by means of quantitative and semi-quantitative approaches. Moreover, several methodologies aim to assess the vulnerability of multiple targets to specific natural hazards by means of vulnerability functions and indicators at the regional and local scale. The overall results of the review show that multi-risk approaches do not consider the effects of climate change and mostly rely on the analysis of static vulnerability (i.e. no time-dependent vulnerabilities, no changes among exposed elements). A relevant challenge is therefore to develop comprehensive formal approaches for the assessment of different climate-induced hazards and risks, including dynamic exposure and vulnerability. This requires the selection and aggregation of suitable hazard and vulnerability metrics to make a synthesis of information about multiple climate impacts, the spatial analysis and ranking of risks, including their visualization and communication to end-users. To face these issues, climate impact assessors should develop cross-sectorial collaborations among different expertise (e.g. modellers, natural scientists, economists) integrating information on climate change scenarios with sectorial climate impact assessment, towards the development of a comprehensive multi-risk assessment process. Copyright © 2015 Elsevier Ltd. All rights reserved.

Constructing optimal ensemble projections for predictive environmental modelling in Northern Eurasia

NASA Astrophysics Data System (ADS)

Anisimov, Oleg; Kokorev, Vasily

2013-04-01

Large uncertainties in climate impact modelling are associated with the forcing climate data. This study is targeted at the evaluation of the quality of GCM-based climatic projections in the specific context of predictive environmental modelling in Northern Eurasia. To accomplish this task, we used the output from 36 CMIP5 GCMs from the IPCC AR-5 data base for the control period 1975-2005 and calculated several climatic characteristics and indexes that are most often used in the impact models, i.e. the summer warmth index, duration of the vegetation growth period, precipitation sums, dryness index, thawing degree-day sums, and the annual temperature amplitude. We used data from 744 weather stations in Russia and neighbouring countries to analyze the spatial patterns of modern climatic change and to delineate 17 large regions with coherent temperature changes in the past few decades. GSM results and observational data were averaged over the coherent regions and compared with each other. Ultimately, we evaluated the skills of individual models, ranked them in the context of regional impact modelling and identified top-end GCMs that "better than average" reproduce modern regional changes of the selected meteorological parameters and climatic indexes. Selected top-end GCMs were used to compose several ensembles, each combining results from the different number of models. Ensembles were ranked using the same algorithm and outliers eliminated. We then used data from top-end ensembles for the 2000-2100 period to construct the climatic projections that are likely to be "better than average" in predicting climatic parameters that govern the state of environment in Northern Eurasia. The ultimate conclusions of our study are the following. • High-end GCMs that demonstrate excellent skills in conventional atmospheric model intercomparison experiments are not necessarily the best in replicating climatic characteristics that govern the state of environment in Northern Eurasia, and independent model evaluation on regional level is necessary to identify "better than average" GCMs. • Each of the ensembles combining results from several "better than average" models replicate selected meteorological parameters and climatic indexes better than any single GCM. The ensemble skills are parameter-specific and depend on models it consists of. The best results are not necessarily those based on the ensemble comprised by all "better than average" models. • Comprehensive evaluation of climatic scenarios using specific criteria narrows the range of uncertainties in environmental projections.

Studying the Causes of Recent Climate Change

NASA Astrophysics Data System (ADS)

Santer, Benjamin D.

2011-11-01

This chapter describes progress in the field of "detection and attribution" (D&A) research, which seeks to identify certain "fingerprints," or patterns of climate change, and to correlate them with possible human factors influencing the climate. Such studies contributed to the scientific confidence with which the Fourth Assessment Report of the Intergovernmental Panel on Climate Change was able to assert that anthropogenic greenhouse gases had had a discernible effect on global warming since the mid-20th century. D&A methods have greatly improved to incorporate many more climate variables and to include increasingly finer variations in space and time. The chapter also describes the intercomparison of global climate models and the comprehensive data base of model simulations now available to anyone free of charge. The following is the testimony given by Benjamin Santer to the U.S. House of Representative Committee on Science and Technology, Subcommittee on Energy and Environment, on November 17, 2010. It is adapted from a chapter that Tom Wigley and Benjamin Santer published in a book edited by the late Stephen Schneider [1] and from previous testimony given by Dr. Santer to the House Select Committee on Energy Independence and Global Warming.[2

Incorporating Anthropogenic Influences into Fire Probability Models: Effects of Human Activity and Climate Change on Fire Activity in California.

PubMed

Mann, Michael L; Batllori, Enric; Moritz, Max A; Waller, Eric K; Berck, Peter; Flint, Alan L; Flint, Lorraine E; Dolfi, Emmalee

2016-01-01

The costly interactions between humans and wildfires throughout California demonstrate the need to understand the relationships between them, especially in the face of a changing climate and expanding human communities. Although a number of statistical and process-based wildfire models exist for California, there is enormous uncertainty about the location and number of future fires, with previously published estimates of increases ranging from nine to fifty-three percent by the end of the century. Our goal is to assess the role of climate and anthropogenic influences on the state's fire regimes from 1975 to 2050. We develop an empirical model that integrates estimates of biophysical indicators relevant to plant communities and anthropogenic influences at each forecast time step. Historically, we find that anthropogenic influences account for up to fifty percent of explanatory power in the model. We also find that the total area burned is likely to increase, with burned area expected to increase by 2.2 and 5.0 percent by 2050 under climatic bookends (PCM and GFDL climate models, respectively). Our two climate models show considerable agreement, but due to potential shifts in rainfall patterns, substantial uncertainty remains for the semiarid inland deserts and coastal areas of the south. Given the strength of human-related variables in some regions, however, it is clear that comprehensive projections of future fire activity should include both anthropogenic and biophysical influences. Previous findings of substantially increased numbers of fires and burned area for California may be tied to omitted variable bias from the exclusion of human influences. The omission of anthropogenic variables in our model would overstate the importance of climatic ones by at least 24%. As such, the failure to include anthropogenic effects in many models likely overstates the response of wildfire to climatic change.

Incorporating Anthropogenic Influences into Fire Probability Models: Effects of Human Activity and Climate Change on Fire Activity in California

PubMed Central

Batllori, Enric; Moritz, Max A.; Waller, Eric K.; Berck, Peter; Flint, Alan L.; Flint, Lorraine E.; Dolfi, Emmalee

2016-01-01

The costly interactions between humans and wildfires throughout California demonstrate the need to understand the relationships between them, especially in the face of a changing climate and expanding human communities. Although a number of statistical and process-based wildfire models exist for California, there is enormous uncertainty about the location and number of future fires, with previously published estimates of increases ranging from nine to fifty-three percent by the end of the century. Our goal is to assess the role of climate and anthropogenic influences on the state’s fire regimes from 1975 to 2050. We develop an empirical model that integrates estimates of biophysical indicators relevant to plant communities and anthropogenic influences at each forecast time step. Historically, we find that anthropogenic influences account for up to fifty percent of explanatory power in the model. We also find that the total area burned is likely to increase, with burned area expected to increase by 2.2 and 5.0 percent by 2050 under climatic bookends (PCM and GFDL climate models, respectively). Our two climate models show considerable agreement, but due to potential shifts in rainfall patterns, substantial uncertainty remains for the semiarid inland deserts and coastal areas of the south. Given the strength of human-related variables in some regions, however, it is clear that comprehensive projections of future fire activity should include both anthropogenic and biophysical influences. Previous findings of substantially increased numbers of fires and burned area for California may be tied to omitted variable bias from the exclusion of human influences. The omission of anthropogenic variables in our model would overstate the importance of climatic ones by at least 24%. As such, the failure to include anthropogenic effects in many models likely overstates the response of wildfire to climatic change. PMID:27124597

Modeling historic variation and its application for understanding future variability (section 3)

Treesearch

Robert E. Keane

2012-01-01

Although some may doubt its usefulness in a future with rapidly changing climates, exotic introductions, and increased human land use, the historical range of variation (HRV) of ecological landscape characteristics provides a relatively useful reference point for evaluating the impacts of landmanagement activities. Unfortunately, comprehensive spatial and temporal data...

The effects of weather and climate change on dengue.

PubMed

Colón-González, Felipe J; Fezzi, Carlo; Lake, Iain R; Hunter, Paul R

2013-11-01

There is much uncertainty about the future impact of climate change on vector-borne diseases. Such uncertainty reflects the difficulties in modelling the complex interactions between disease, climatic and socioeconomic determinants. We used a comprehensive panel dataset from Mexico covering 23 years of province-specific dengue reports across nine climatic regions to estimate the impact of weather on dengue, accounting for the effects of non-climatic factors. Using a Generalized Additive Model, we estimated statistically significant effects of weather and access to piped water on dengue. The effects of weather were highly nonlinear. Minimum temperature (Tmin) had almost no effect on dengue incidence below 5 °C, but Tmin values above 18 °C showed a rapidly increasing effect. Maximum temperature above 20 °C also showed an increasing effect on dengue incidence with a peak around 32 °C, after which the effect declined. There is also an increasing effect of precipitation as it rose to about 550 mm, beyond which such effect declines. Rising access to piped water was related to increasing dengue incidence. We used our model estimations to project the potential impact of climate change on dengue incidence under three emission scenarios by 2030, 2050, and 2080. An increase of up to 40% in dengue incidence by 2080 was estimated under climate change while holding the other driving factors constant. Our results indicate that weather significantly influences dengue incidence in Mexico and that such relationships are highly nonlinear. These findings highlight the importance of using flexible model specifications when analysing weather-health interactions. Climate change may contribute to an increase in dengue incidence. Rising access to piped water may aggravate dengue incidence if it leads to increased domestic water storage. Climate change may therefore influence the success or failure of future efforts against dengue.

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

Munger, J. William; Foster, David R.; Richardson, Andrew D.

This report summarizes work to improve quantitative understanding of the terrestrial ecosystem processes that control carbon sequestration in unmanaged forests It builds upon the comprehensive long-term observations of CO2 fluxes, climate and forest structure and function at the Harvard Forest in Petersham, MA. This record includes the longest CO2 flux time series in the world. The site is a keystone for the AmeriFlux network. Project Description The project synthesizes observations made at the Harvard Forest HFEMS and Hemlock towers, which represent the dominant mixed deciduous and coniferous forest types in the northeastern United States. The 20+ year record of carbonmore » uptake at Harvard Forest and the associated comprehensive meteorological and biometric data, comprise one of the best data sets to challenge ecosystem models on time scales spanning hourly, daily, monthly, interannual and multi-decadal intervals, as needed to understand ecosystem change and climate feedbacks.« less

Nurse characteristics, leadership, safety climate, emotional labour and intention to stay for nurses: a structural equation modelling approach.

PubMed

Liang, Hui-Yu; Tang, Fu-In; Wang, Tze-Fang; Lin, Kai-Ching; Yu, Shu

2016-12-01

The aim of this study was to propose a theoretical model and apply it to examine the structural relationships among nurse characteristics, leadership characteristics, safety climate, emotional labour and intention to stay for hospital nurses. Global nursing shortages negatively affect the quality of care. The shortages can be reduced by retaining nurses. Few studies have independently examined the relationships among leadership, safety climate, emotional labour and nurses' intention to stay; more comprehensive theoretical foundations for examining nurses' intention to stay and its related factors are lacking. Cross-sectional. A purposive sample of 414 full-time nurses was recruited from two regional hospitals in Taiwan. A structured questionnaire was used to collect data from November 2013-June 2014. Structural equation modelling was employed to test the theoretical models of the relationships among the constructs. Our data supported the theoretical model. Intention to stay was positively correlated with age and the safety climate, whereas working hours per week and emotional labour were negatively correlated. The nursing position and transformational leadership indirectly affected intention to stay; this effect was mediated separately by emotional labour and the safety climate. Our data supported the model fit. Our findings provide practical implications for healthcare organizations and administrators to increase nurses' intent to stay. Strategies including a safer climate, appropriate working hours and lower emotional labour can directly increase nurses' intent to stay. Transformational leadership did not directly influence nurses' intention to stay; however, it reduced emotional labour, thereby increasing intention to stay. © 2016 John Wiley & Sons Ltd.

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

Haywood, Jim M.; Jones, Andy; Dunstone, Nick

Despite the fact that the southern hemisphere contains a far greater proportion of dark ocean than the northern hemisphere, the total amount of sunlight reflected from the hemispheres is equal. However, the majority of climate models do not adequately represent this equivalence. Here we examine the impact of equilibrating hemispheric albedos by various idealised methods in a comprehensive coupled climate model and find significant improvements in what have been considered longstanding and apparently intractable model biases. Monsoon precipitation biases almost vanish over all continental land areas, the penetration of monsoon rainfall across the Sahel and the west African monsoon “jump”more » become well represented, and indicators of hurricane frequency are significantly improved. The results appear not to be model specific, implying that hemispheric albedo equivalence may provide a fundamental constraint for climate models that must be satisfied if the dynamics driving these processes, in particular the strength of the Hadley cell, are to be adequately represented. Cross-equatorial energy transport is implicated as a crucial component that must be accurately modelled in coupled general circulation models. The results also suggest that the commonly used practice of prescribing sea-surface temperatures in models provides a less accurate represention of precipitation than constraining the hemispheric albedos.« less

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-04-01

The Indian summer monsoon shapes the livelihood of a large share of the world's population. About 80% of annual precipitation over India occurs during the monsoon season from June through September. Next to its seasonal mean rainfall the day-to-day variability is crucial for the risk of flooding, national water supply and agricultural productivity. Here we show that the latest ensemble of climate model simulations, prepared for the IPCC's AR-5, consistently projects significant increases in day-to-day rainfall variability under unmitigated climate change. While all models show an increase in day-to-day variability, some models are more realistic in capturing the observed seasonal mean rainfall over India than others. While no model's monsoon rainfall exceeds the observed value by more than two standard deviations, half of the models simulate a significantly weaker monsoon than observed. The relative increase in day-to-day variability by the year 2100 ranges from 15% to 48% under the strongest scenario (RCP-8.5), in the ten models which capture seasonal mean rainfall closest to observations. The variability increase per degree of global warming is independent of the scenario in most models, and is 8% +/- 4% per K on average. This consistent projection across 20 comprehensive climate models provides confidence in the results and suggests the necessity of profound adaptation measures in the case of unmitigated climate change.

Potential role of vegetation feedback in the climate sensitivity of high-latitude regions: A case study at 6000 years B.P.

USGS Publications Warehouse

Kutzbach, J.-E.; Bartlein, P.J.; Foley, J.A.; Harrison, S.P.; Hosteller, S.W.; Liu, Z.; Prentice, I.C.; Webb, T.

1996-01-01

Previous climate model simulations have shown that the configuration of the Earth's orbit during the early to mid-Holocene (approximately 10-5 kyr) can account for the generally warmer-than-present conditions experienced by the high latitudes of the northern hemisphere. New simulations for 6 kyr with two atmospheric/mixed-layer ocean models (Community Climate Model, version 1, CCM1, and Global ENvironmental and Ecological Simulation of Interactive Systems, version 2, GENESIS 2) are presented here and compared with results from two previous simulations with GENESIS 1 that were obtained with and without the albedo feedback due to climate-induced poleward expansion of the boreal forest. The climate model results are summarized in the form of potential vegetation maps obtained with the global BIOME model, which facilitates visual comparisons both among models and with pollen and plant macrofossil data recording shifts of the forest-tundra boundary. A preliminary synthesis shows that the forest limit was shifted 100-200 km north in most sectors. Both CCM1 and GENESIS 2 produced a shift of this magnitude. GENESIS 1 however produced too small a shift, except when the boreal forest albedo feedback was included. The feedback in this case was estimated to have amplified forest expansion by approximately 50%. The forest limit changes also show meridional patterns (greatest expansion in central Siberia and little or none in Alaska and Labrador) which have yet to be reproduced by models. Further progress in understanding of the processes involved in the response of climate and vegetation to orbital forcing will require both the deployment of coupled atmosphere-biosphere-ocean models and the development of more comprehensive observational data sets.

Tailoring the visual communication of climate projections for local adaptation practitioners in Germany and the UK

PubMed Central

Lorenz, Susanne; Dessai, Suraje; Forster, Piers M.; Paavola, Jouni

2015-01-01

Visualizations are widely used in the communication of climate projections. However, their effectiveness has rarely been assessed among their target audience. Given recent calls to increase the usability of climate information through the tailoring of climate projections, it is imperative to assess the effectiveness of different visualizations. This paper explores the complexities of tailoring through an online survey conducted with 162 local adaptation practitioners in Germany and the UK. The survey examined respondents’ assessed and perceived comprehension (PC) of visual representations of climate projections as well as preferences for using different visualizations in communicating and planning for a changing climate. Comprehension and use are tested using four different graph formats, which are split into two pairs. Within each pair the information content is the same but is visualized differently. We show that even within a fairly homogeneous user group, such as local adaptation practitioners, there are clear differences in respondents’ comprehension of and preference for visualizations. We do not find a consistent association between assessed comprehension and PC or use within the two pairs of visualizations that we analysed. There is, however, a clear link between PC and use of graph format. This suggests that respondents use what they think they understand the best, rather than what they actually understand the best. These findings highlight that audience-specific targeted communication may be more complex and challenging than previously recognized. PMID:26460109

A comparative review of multi-risk modelling methodologies for climate change adaptation in mountain regions

NASA Astrophysics Data System (ADS)

Terzi, Stefano; Torresan, Silvia; Schneiderbauer, Stefan

2017-04-01

Keywords: Climate change, mountain regions, multi-risk assessment, climate change adaptation. Climate change has already led to a wide range of impacts on the environment, the economy and society. Adaptation actions are needed to cope with the impacts that have already occurred (e.g. storms, glaciers melting, floods, droughts) and to prepare for future scenarios of climate change. Mountain environment is particularly vulnerable to the climate changes due to its exposure to recent climate warming (e.g. water regime changes, thawing of permafrost) and due to the high degree of specialization of both natural and human systems (e.g. alpine species, valley population density, tourism-based economy). As a consequence, the mountain local governments are encouraged to undertake territorial governance policies to climate change, considering multi-risks and opportunities for the mountain economy and identifying the best portfolio of adaptation strategies. This study aims to provide a literature review of available qualitative and quantitative tools, methodological guidelines and best practices to conduct multi-risk assessments in the mountain environment within the context of climate change. We analyzed multi-risk modelling and assessment methods applied in alpine regions (e.g. event trees, Bayesian Networks, Agent Based Models) in order to identify key concepts (exposure, resilience, vulnerability, risk, adaptive capacity), climatic drivers, cause-effect relationships and socio-ecological systems to be integrated in a comprehensive framework. The main outcomes of the review, including a comparison of existing techniques based on different criteria (e.g. scale of analysis, targeted questions, level of complexity) and a snapshot of the developed multi-risk framework for climate change adaptation will be here presented and discussed.

Developing Models for Predictive Climate Science

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

Drake, John B; Jones, Philip W

2007-01-01

The Community Climate System Model results from a multi-agency collaboration designed to construct cutting-edge climate science simulation models for a broad research community. Predictive climate simulations are currently being prepared for the petascale computers of the near future. Modeling capabilities are continuously being improved in order to provide better answers to critical questions about Earth's climate. Climate change and its implications are front page news in today's world. Could global warming be responsible for the July 2006 heat waves in Europe and the United States? Should more resources be devoted to preparing for an increase in the frequency of strongmore » tropical storms and hurricanes like Katrina? Will coastal cities be flooded due to a rise in sea level? The National Climatic Data Center (NCDC), which archives all weather data for the nation, reports that global surface temperatures have increased over the last century, and that the rate of increase is three times greater since 1976. Will temperatures continue to climb at this rate, will they decline again, or will the rate of increase become even steeper? To address such a flurry of questions, scientists must adopt a systematic approach and develop a predictive framework. With responsibility for advising on energy and technology strategies, the DOE is dedicated to advancing climate research in order to elucidate the causes of climate change, including the role of carbon loading from fossil fuel use. Thus, climate science--which by nature involves advanced computing technology and methods--has been the focus of a number of DOE's SciDAC research projects. Dr. John Drake (ORNL) and Dr. Philip Jones (LANL) served as principal investigators on the SciDAC project, 'Collaborative Design and Development of the Community Climate System Model for Terascale Computers.' The Community Climate System Model (CCSM) is a fully-coupled global system that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The collaborative SciDAC team--including over a dozen researchers at institutions around the country--developed, validated, documented, and optimized the performance of CCSM using the latest software engineering approaches, computational technology, and scientific knowledge. Many of the factors that must be accounted for in a comprehensive model of the climate system are illustrated in figure 1.« less

Building an ensemble of climate scenarios for decision-making in hydrology: benefits, pitfalls and uncertainties

NASA Astrophysics Data System (ADS)

Braun, Marco; Chaumont, Diane

2013-04-01

Using climate model output to explore climate change impacts on hydrology requires several considerations, choices and methods in the post treatment of the datasets. In the effort of producing a comprehensive data base of climate change scenarios for over 300 watersheds in the Canadian province of Québec, a selection of state of the art procedures were applied to an ensemble comprising 87 climate simulations. The climate data ensemble is based on global climate simulations from the Coupled Model Intercomparison Project - Phase 3 (CMIP3) and regional climate simulations from the North American Regional Climate Change Assessment Program (NARCCAP) and operational simulations produced at Ouranos. Information on the response of hydrological systems to changing climate conditions can be derived by linking climate simulations with hydrological models. However, the direct use of raw climate model output variables as drivers for hydrological models is limited by issues such as spatial resolution and the calibration of hydro models with observations. Methods for downscaling and bias correcting the data are required to achieve seamless integration of climate simulations with hydro models. The effects on the results of four different approaches to data post processing were explored and compared. We present the lessons learned from building the largest data base yet for multiple stakeholders in the hydro power and water management sector in Québec putting an emphasis on the benefits and pitfalls in choosing simulations, extracting the data, performing bias corrections and documenting the results. A discussion of the sources and significance of uncertainties in the data will also be included. The climatological data base was subsequently used by the state owned hydro power company Hydro-Québec and the Centre d'expertise hydrique du Québec (CEHQ), the provincial water authority, to simulate future stream flows and analyse the impacts on hydrological indicators. While this submission focuses on the production of climatic scenarios for application in hydrology, the submission « The (cQ)2 project: assessing watershed scale hydrological changes for the province of Québec at the 2050 horizon, a collaborative framework » by Catherine Guay describes how Hydro-Québec and CEHQ put the data into use.

Tree-ring growth of Scots pine, Common beech and Pedunculate oak under future climate in northeastern Germany

NASA Astrophysics Data System (ADS)

Jurasinski, Gerald; Scharnweber, Tobias; Schröder, Christian; Lennartz, Bernd; Bauwe, Andreas

2017-04-01

Tree growth depends, among other factors, largely on the prevailing climatic conditions. Therefore, tree growth patterns are to be expected under climate change. Here, we analyze the tree-ring growth response of three major European tree species to projected future climate across a climatic (mostly precipitation) gradient in northeastern Germany. We used monthly data for temperature, precipitation, and the standardized precipitation evapotranspiration index (SPEI) over multiple time scales (1, 3, 6, 12, and 24 months) to construct models of tree-ring growth for Scots pine (Pinus syl- vestris L.) at three pure stands, and for Common beech (Fagus sylvatica L.) and Pedunculate oak (Quercus robur L.) at three mature mixed stands. The regression models were derived using a two-step approach based on partial least squares regression (PLSR) to extract potentially well explaining variables followed by ordinary least squares regression (OLSR) to consolidate the models to the least number of variables while retaining high explanatory power. The stability of the models was tested with a comprehensive calibration-verification scheme. All models were successfully verified with R2s ranging from 0.21 for the western pine stand to 0.62 for the beech stand in the east. For growth prediction, climate data forecasted until 2100 by the regional climate model WETTREG2010 based on the A1B Intergovernmental Panel on Climate Change (IPCC) emission scenario was used. For beech and oak, growth rates will likely decrease until the end of the 21st century. For pine, modeled growth trends vary and range from a slight growth increase to a weak decrease in growth rates depending on the position along the climatic gradient. The climatic gradient across the study area will possibly affect the future growth of oak with larger growth reductions towards the drier east. For beech, site-specific adaptations seem to override the influence of the climatic gradient. We conclude that in Northeastern Germany Scots pine has great potential to remain resilient to projected climate change without any greater impairment, whereas Common beech and Pedunculate oak will likely face lesser growth under the expected warmer and dryer climate conditions. The results call for an adaptation of forest management to mitigate the negative effects of climate change for beech and oak in the region.

MOSAiC - Multidisciplinary drifting Observatory for the Study of Arctic Climate

NASA Astrophysics Data System (ADS)

Shupe, M.; Persson, O. P.; Tjernstrom, M. K.; Dethloff, K.

2012-12-01

The climate in the Arctic is changing faster than in other regions of the Earth, with near surface temperatures rising more than twice as fast as the global average and the perennial sea-ice cover shrinking fast, especially in summer. The Arctic is transitioning towards a new climate regime dominated by first year sea-ice. At the same time, the scientific understanding of processes and feedbacks causing this rapid change is poor and climate modeling in the Arctic remains problematic. Furthermore, the key physical processes and process-interactions in this new emerging Arctic system are likely different from those in the old system that was dominated by multi-year ice. Our understanding of this complex climate system, and ability to improve climate and weather models, is limited by the lack of observations in the extreme and remote central Arctic. Multi-year, detailed and comprehensive measurements, extending from the atmosphere through the sea-ice and into the ocean in the central Arctic Basin are needed to provide process-level understanding of the central Arctic climate system. To address this need, a manned, international drifting station will be installed in the young sea-ice of the western Arctic and follow the evolution of the ice pack as it proceeds through the transpolar drift towards the Fram Strait over the course of 1-2 years. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), proposed to start in autumn 2017, will be guided by the broad theme: What are the causes and consequences of diminished Arctic sea-ice coverage? To address this theme requires a number of interdisciplinary investigations that target more specific science questions. *How do ongoing changes in the Arctic ice-ocean-atmosphere system drive heat and mass transfers of importance to climate and ecosystems? *What are the processes and feedbacks affecting sea ice cover, atmosphere-ocean stratification and energy budget in the Arctic? *Will an ice reduced Arctic become more biologically productive and what are the consequences of this to other components of the system? *How do the different scales of heterogeneity within the atmosphere ice and ocean interact to impact the linkages or feedbacks within the system? *How do interfacial exchange rates, biology and chemistry couple to regulate the major elemental cycles? MOSAiC will address these multi-disciplinary questions using intensive observations and modeling of processes that transfer energy, mass, and momentum through the atmosphere-ice-ocean system. The centerpiece of the observatory will be an icebreaker-based station to serve as a hub for intensive and comprehensive observations of climatically-significant physical, chemical, and biological processes through the vertical column. To provide important spatial context and horizontal variability, this facility will be the focal point for a constellation of coordinated observations made by drifting buoys, unmanned aerial and underwater vehicles, aircraft, ships, and satellites. These MOSAiC observational activities will serve as a testbed for evaluation and development of models at scales ranging from high-resolution, process models to regional and global climate models. MOSAiC observational and modeling activities will be linked at the outset, such that model needs will be integral in observational design, implementation, and analysis.

An Integrated Systems Approach to Designing Climate Change Adaptation Policy in Water Resources

NASA Astrophysics Data System (ADS)

Ryu, D.; Malano, H. M.; Davidson, B.; George, B.

2014-12-01

Climate change projections are characterised by large uncertainties with rainfall variability being the key challenge in designing adaptation policies. Climate change adaptation in water resources shows all the typical characteristics of 'wicked' problems typified by cognitive uncertainty as new scientific knowledge becomes available, problem instability, knowledge imperfection and strategic uncertainty due to institutional changes that inevitably occur over time. Planning that is characterised by uncertainties and instability requires an approach that can accommodate flexibility and adaptive capacity for decision-making. An ability to take corrective measures in the event that scenarios and responses envisaged initially derive into forms at some future stage. We present an integrated-multidisciplinary and comprehensive framework designed to interface and inform science and decision making in the formulation of water resource management strategies to deal with climate change in the Musi Catchment of Andhra Pradesh, India. At the core of this framework is a dialogue between stakeholders, decision makers and scientists to define a set of plausible responses to an ensemble of climate change scenarios derived from global climate modelling. The modelling framework used to evaluate the resulting combination of climate scenarios and adaptation responses includes the surface and groundwater assessment models (SWAT & MODFLOW) and the water allocation modelling (REALM) to determine the water security of each adaptation strategy. Three climate scenarios extracted from downscaled climate models were selected for evaluation together with four agreed responses—changing cropping patterns, increasing watershed development, changing the volume of groundwater extraction and improving irrigation efficiency. Water security in this context is represented by the combination of level of water availability and its associated security of supply for three economic activities (agriculture, urban, industrial) on a spatially distributed basis. The resulting combinations of climate scenarios and adaptation responses were subjected to a combined hydro-economic assessment based on the degree of water security together with its cost-effectiveness against the Business-as-usual scenario.

Conceptualizing Holistic Community Resilience to Climate ...

EPA Pesticide Factsheets

The concept of resilience has been evolving over the past decade as a way to address the current and future challenges nations, states, and cities face from a changing climate. Understanding how the environment (natural and built), climate event risk, societal interactions, and governance reflect community resilience for adaptive management is critical for envisioning urban and natural environments that can persist through extreme weather events and longer-term shifts in climate. To be successful, this interaction of these five domains must result in maintaining quality of life and ensuring equal access to the benefits or the protection from harm for all segments of the population. An exhaustive literature review of climate resilience approaches was conducted examining the two primary elements of resilience—vulnerability and recoverability. The results of this review were examined to determine if any existing frameworks addressed the above five major areas in an integrated manner. While some aspects of a resilience model were available for existing sources, no comprehensive approach was available. A new conceptual model for resilience to climate events is proposed that incorporates some available structures and addresses these five domains at a national, regional, state, and county spatial scale for a variety of climate-induced events ranging from superstorms to droughts and their concomitant events such as wildfires, floods, and pest invasions. This conceptua

Aligning Comprehensive School Counseling Programs and Positive Behavioral Interventions and Supports to Maximize School Counselors' Efforts

ERIC Educational Resources Information Center

Goodman-Scott, Emily; Betters-Bubon, Jennifer; Donohue, Peg

2015-01-01

School counselors are tasked with contributing to a safe and preventative school climate serving students' academic, career, and social/emotional needs through comprehensive school counseling program implementation. Positive Behavioral Interventions and Supports (PBIS) prioritizes a positive school climate, is widely implemented in the United…

School Climate: An Essential Component of a Comprehensive School Safety Plan

ERIC Educational Resources Information Center

Stark, Heidi

2017-01-01

The intentional assessment and management of school climate is an essential component of a comprehensive school safety plan. The value of this preventive aspect of school safety is often diminished as schools invest resources in physical security measures as a narrowly focused effort to increase school safety (Addington, 2009). This dissertation…

The Finer Details: Climate Modeling

NASA Technical Reports Server (NTRS)

2000-01-01

If you want to know whether you will need sunscreen or an umbrella for tomorrow's picnic, you can simply read the local weather report. However, if you are calculating the impact of gas combustion on global temperatures, or anticipating next year's rainfall levels to set water conservation policy, you must conduct a more comprehensive investigation. Such complex matters require long-range modeling techniques that predict broad trends in climate development rather than day-to-day details. Climate models are built from equations that calculate the progression of weather-related conditions over time. Based on the laws of physics, climate model equations have been developed to predict a number of environmental factors, for example: 1. Amount of solar radiation that hits the Earth. 2. Varying proportions of gases that make up the air. 3. Temperature at the Earth's surface. 4. Circulation of ocean and wind currents. 5. Development of cloud cover. Numerical modeling of the climate can improve our understanding of both the past and, the future. A model can confirm the accuracy of environmental measurements taken. in, the past and can even fill in gaps in those records. In addition, by quantifying the relationship between different aspects of climate, scientists can estimate how a future change in one aspect may alter the rest of the world. For example, could an increase in the temperature of the Pacific Ocean somehow set off a drought on the other side of the world? A computer simulation could lead to an answer for this and other questions. Quantifying the chaotic, nonlinear activities that shape our climate is no easy matter. You cannot run these simulations on your desktop computer and expect results by the time you have finished checking your morning e-mail. Efficient and accurate climate modeling requires powerful computers that can process billions of mathematical calculations in a single second. The NCCS exists to provide this degree of vast computing capability.

The effects of atmospheric chemistry on radiation budget in the Community Earth Systems Model

NASA Astrophysics Data System (ADS)

Choi, Y.; Czader, B.; Diao, L.; Rodriguez, J.; Jeong, G.

2013-12-01

The Community Earth Systems Model (CESM)-Whole Atmosphere Community Climate Model (WACCM) simulations were performed to study the impact of atmospheric chemistry on the radiation budget over the surface within a weather prediction time scale. The secondary goal is to get a simplified and optimized chemistry module for the short time period. Three different chemistry modules were utilized to represent tropospheric and stratospheric chemistry, which differ in how their reactions and species are represented: (1) simplified tropospheric and stratospheric chemistry (approximately 30 species), (2) simplified tropospheric chemistry and comprehensive stratospheric chemistry from the Model of Ozone and Related Chemical Tracers, version 3 (MOZART-3, approximately 60 species), and (3) comprehensive tropospheric and stratospheric chemistry (MOZART-4, approximately 120 species). Our results indicate the different details in chemistry treatment from these model components affect the surface temperature and impact the radiation budget.

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

NASA Astrophysics Data System (ADS)

González, D. L., II; Angus, M. P.; Tetteh, I. K.; Bello, G. A.; Padmanabhan, K.; Pendse, S. V.; Srinivas, S.; Yu, J.; Semazzi, F.; Kumar, V.; Samatova, N. F.

2014-04-01

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and Dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall, including well-known associations from prior climate knowledge, as well as promising discoveries that invite further research by the climate science community.

Radiative Forcing by Well-Mixed Greenhouse Gases: Estimates from Climate Models in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4)

NASA Technical Reports Server (NTRS)

Collins, W. D.; Ramaswamy, V.; Schwarzkopf, M. D.; Sun, Y.; Portmann, R. W.; Fu, Q.; Casanova, S. E. B.; Dufresne, J.-L.; Fillmore, D. W.; Forster, P. M. D.;

Development of virtual research environment for regional climatic and ecological studies and continuous education support

NASA Astrophysics Data System (ADS)

Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Bogomolov, Vasily; Gordova, Yulia; Martynova, Yulia; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2014-05-01

Volumes of environmental data archives are growing immensely due to recent models, high performance computers and sensors development. It makes impossible their comprehensive analysis in conventional manner on workplace using in house computing facilities, data storage and processing software at hands. One of possible answers to this challenge is creation of virtual research environment (VRE), which should provide a researcher with an integrated access to huge data resources, tools and services across disciplines and user communities and enable researchers to process structured and qualitative data in virtual workspaces. VRE should integrate data, network and computing resources providing interdisciplinary climatic research community with opportunity to get profound understanding of ongoing and possible future climatic changes and their consequences. Presented are first steps and plans for development of VRE prototype element aimed at regional climatic and ecological monitoring and modeling as well as at continuous education and training support. Recently developed experimental software and hardware platform aimed at integrated analysis of heterogeneous georeferenced data "Climate" (http://climate.scert.ru/, Gordov et al., 2013; Shulgina et al., 2013; Okladnikov et al., 2013) is used as a VRE element prototype and approach test bench. VRE under development will integrate on the base of geoportal distributed thematic data storage, processing and analysis systems and set of models of complex climatic and environmental processes run on supercomputers. VRE specific tools are aimed at high resolution rendering on-going climatic processes occurring in Northern Eurasia and reliable and found prognoses of their dynamics for selected sets of future mankind activity scenaria. Currently the VRE element is accessible via developed geoportal at the same link (http://climate.scert.ru/) and integrates the WRF and «Planet Simulator» models, basic reanalysis and instrumental measurements data and support profound statistical analysis of storaged and modeled on demand data. In particular, one can run the integrated models, preprocess modeling results data, using dedicated modules for numerical processing perform analysys and visualize obtained results. New functionality recently has been added to the statistical analysis tools set aimed at detailed studies of climatic extremes occurring in Northern Asia. The VRE element is also supporting thematic educational courses for students and post-graduate students of the Tomsk State University. In particular, it allow students to perform on-line thematic laboratory work cycles on the basics of analysis of current and potential future regional climate change using Siberia territory as an example (Gordova et al, 2013). We plan to expand the integrated models set and add comprehensive surface and Arctic Ocean description. Developed VRE element "Climate" provides specialists involved into multidisciplinary research projects with reliable and practical instruments for integrated research of climate and ecosystems changes on global and regional scales. With its help even a user without programming skills can process and visualize multidimensional observational and model data through unified web-interface using a common graphical web-browser. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grant 13-05-12034, grant 14-05-00502, and integrated project SB RAS 131. References 1. Gordov E.P., Lykosov V.N., Krupchatnikov V.N., Okladnikov I.G., Titov A.G., Shulgina T.M. Computationaland information technologies for monitoring and modeling of climate changes and their consequences. Novosibirsk: Nauka, Siberian branch, 2013. - 195 p. (in Russian) 2. T.M. Shulgina, E.P. Gordov, I.G. Okladnikov, A.G., Titov, E.Yu. Genina, N.P. Gorbatenko, I.V. Kuzhevskaya,A.S. Akhmetshina. Software complex for a regional climate change analysis. // Vestnik NGU. Series: Information technologies. 2013. Vol. 11. Issue 1. P. 124-131. (in Russian) 3. I.G. Okladnikov, A.G. Titov, T.M. Shulgina, E.P. Gordov, V.Yu. Bogomolov, Yu.V. Martynova, S.P. Suschenko,A.V. Skvortsov. Software for analysis and visualization of climate change monitoring and forecasting data //Numerical methods and programming, 2013. Vol. 14. P. 123-131.(in Russian) 4. Yu.E. Gordova, E.Yu. Genina, V.P. Gorbatenko, E.P. Gordov, I.V. Kuzhevskaya, Yu.V. Martynova , I.G. Okladnikov, A.G. Titov, T.M. Shulgina, N.K. Barashkova Support of the educational process in modern climatology within the web-gis platform «Climate». Open and Distant Education. 2013, No 1(49)., P. 14-19.(in Russian)

Extraction of Urban Morphology Parameters from Generic European Datasets: A Case Study for Antwerp, Berlin and Almada

NASA Astrophysics Data System (ADS)

Stevens, Catherine; Thomas, Bart

2014-05-01

Climate change is driven by global processes such as the global ocean circulation and its variability over time leading to changing weather patterns on regional scales as well as changes in the severity and occurrence of extreme events such as heat waves. The response of urban societies to the evolving climate depends not only on their regional climate characteristics but also on other local factors such as the urban heat island effect. Simulation of this phenomenon with local urban climate models requires comprehensive information about the urban morphology. This study focusses on the extraction of the planar and frontal area indices from detailed 3D city models and their relationship with the European Soil Sealing Level database from the European Environment Agency. These parameters have been calculated on a 1km2 grid and compared with soil sealing values aggregated at the same spatial resolution. The optimal size of the grid is a trade-off between the level of detail and the robustness of the established relationships by reducing the scatter at small scales. Moreover, the transferability of the results to other geographical areas has been investigated. The analyses have been conducted in the framework of the NACLIM FP7 project funded by the European Commission and include the cities of Antwerp (BE), Berlin (DE) and Almada (PT) represented by different climate and urban characteristics. First results show a correlation of 70% between the planar area index and the averaged soil sealing using a linear regression model at a 1km scale. Moreover, a good correspondence has been found between the relationships for Antwerp and Berlin which is promising for urban climate modellers to reduce model complexity and analyse various climate scenarios in an effective way.

The tropical rain belts with an annual cycle and a continent model intercomparison project: TRACMIP

DOE PAGES

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; ...

2016-11-16

This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

The Tropical Rain Belts with an Annual Cycle and a Continent Model Intercomparison Project: TRACMIP

NASA Technical Reports Server (NTRS)

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; Bader, Juergen; Bordoni, Simona; Codron, Francis; Dixon, Ross D.; Jonas, Jeffrey; Kang, Sarah M.; Klingaman, Nicholas P.;

Development and Performance of Alternative Electricity Sector Pathways Subject to Multiple Climate and Water Projections

NASA Astrophysics Data System (ADS)

Newmark, R. L.; Vorosmarty, C. J.; Miara, A.; Cohen, S.; Macknick, J.; Sun, Y.; Corsi, F.; Fekete, B. M.; Tidwell, V. C.

2017-12-01

Climate change impacts on air temperatures and water availability have the potential to alter future electricity sector investment decisions as well as the reliability and performance of the power sector. Different electricity sector configurations are more or less vulnerable to climate-induced changes. For example, once-through cooled thermal facilities are the most cost-effective and efficient technologies under cooler and wetter conditions, but can be substantially affected by and vulnerable to warmer and drier conditions. Non-thermal renewable technologies, such as PV and wind, are essentially "drought-proof" but have other integration and reliability challenges. Prior efforts have explored the impacts of climate change on electric sector development for a limited set of climate and electricity scenarios. Here, we provide a comprehensive suite of scenarios that evaluate how different electricity sector pathways could be affected by a range of climate and water resource conditions. We use four representative concentration pathway (RCP) scenarios under five global circulation models (GCM) as climate drivers to a Water Balance Model (WBM), to provide twenty separate future climate-water conditions. These climate-water conditions influence electricity sector development from present day to 2050 as determined using the Regional Energy Deployment Systems (ReEDS) model. Four unique electricity sector pathways will be considered, including business-as-usual, carbon cap, high renewable energy technology costs, and coal reliance scenarios. The combination of climate-water and electricity sector pathway scenarios leads to 80 potential future cases resulting in different national and regional electricity infrastructure configurations. The vulnerability of these configurations in relation to climate change (including in-stream thermal pollution impacts and environmental regulations) is evaluated using the Thermoelectric Power and Thermal Pollution (TP2M) model, providing quantitative estimates of the power sector's ability to meet loads, given changes in air temperature, water temperature, and water availability.

Building climate adaptation capabilities through technology and community

NASA Astrophysics Data System (ADS)

Murray, D.; McWhirter, J.; Intsiful, J. D.; Cozzini, S.

2011-12-01

To effectively plan for adaptation to changes in climate, decision makers require infrastructure and tools that will provide them with timely access to current and future climate information. For example, climate scientists and operational forecasters need to access global and regional model projections and current climate information that they can use to prepare monitoring products and reports and then publish these for the decision makers. Through the UNDP African Adaption Programme, an infrastructure is being built across Africa that will provide multi-tiered access to such information. Web accessible servers running RAMADDA, an open source content management system for geoscience information, will provide access to the information at many levels: from the raw and processed climate model output to real-time climate conditions and predictions to documents and presentation for government officials. Output from regional climate models (e.g. RegCM4) and downscaled global climate models will be accessible through RAMADDA. The Integrated Data Viewer (IDV) is being used by scientists to create visualizations that assist the understanding of climate processes and projections, using the data on these as well as external servers. Since RAMADDA is more than a data server, it is also being used as a publishing platform for the generated material that will be available and searchable by the decision makers. Users can wade through the enormous volumes of information and extract subsets for their region or project of interest. Participants from 20 countries attended workshops at ICTP during 2011. They received training on setting up and installing the servers and necessary software and are now working on deploying the systems in their respective countries. This is the first time an integrated and comprehensive approach to climate change adaptation has been widely applied in Africa. It is expected that this infrastructure will enhance North-South collaboration and improve the delivery of technical support and services. This improved infrastructure will enhance the capacity of countries to provide a wide range of robust products and services in a timely manner.

The Poleward Shift of Storm Tracks Under Climate Change: Tracking Cyclones in CMIP5

NASA Astrophysics Data System (ADS)

Kaspi, Y.; Tamarin, T.

2017-12-01

Extratropical cyclones dominate the distribution of precipitation and wind in the midlatitudes, and therefore their frequency, intensity, and paths have a significant effect on weather and climate. Comprehensive climate models forced by enhanced greenhouse gas emissions suggest that under a climate change scenario, the latitudinal band of storm tracks would shift poleward. While the poleward shift is a robust response across most models, there is currently no consensus on what is the dominant dynamical mechanism. Here we use a Lagrangian approach to study the poleward shift, by employing a storm-tracking algorithm on an ensemble of CMIP5 models forced by increased CO2 emissions. We demonstrate that in addition to a poleward shift in the latitude of storm genesis, associated with the expansion of the Hadley cell, the averaged cyclonic storm also propagates more poleward until it reaches its maximum intensity. A mechanism for enhanced poleward motion of cyclones in a warmer climate is proposed, supported by idealized global warming experiments, and relates the shift to changes in upper level jet and atmospheric water vapour content. Our results imply that under the RCP8.5 climate change scenario, the averaged latitude of peak cyclone intensity shifts poleward by about 1.2○ (1.0○) in the Atlantic (Pacific) storm track in the Northern Hemisphere (NH), and by about 1.6○ in the Southern Hemisphere (SH) storm track. These changes in cyclone tracks can have a significant impact on midlatitude climate.

AgMIP: New Results from Sub-Saharan Africa and South Asia Regional Integrated Assessments

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2014-12-01

AgMIP conducted the first set of comprehensive regional integrated assessments of climate change impacts on smallholder farmers in Sub-Saharan Africa and South Asia led by researchers from the regions themselves. The project developed new methods integrating climate, crop, livestock and economic models to conduct climate change impact assessments that characterize impacts on smallholder groups. AgMIP projections of climate change impacts on agriculture are more realistic than previous assessments because they take agricultural development into account. Using the best available data and models, the assessments directly evaluated yield, income, and poverty outcomes including the effects of adaptation packages and development pathways. Results show that even with agricultural development, climate change generally will exert negative pressure on yields of smallholder farmers in Sub-Saharan Africa and South Asia. Without adaptation, climate change leads to increased poverty in some locations in Sub-Saharan Africa and South Asia compared to a future in which climate change does not occur. Adaptation can significantly improve smallholder farmer responses to climate change. AgMIP expert teams identified improved varieties, sowing practices, fertilizer application, and irrigation applications as prioritized adaptation strategies. These targeted adaptation packages were able to overcome a portion of detrimental impacts but could not compensate completely in many locations. Even in cases where average impact is near zero, vulnerability (i.e., those at risk of loss) can be substantial even when mean impacts are positive.

Multi-Decadal Variation of Aerosols: Sources, Transport, and Climate Effects

NASA Technical Reports Server (NTRS)

Chin, Mian; Diehl, Thomas; Bian, Huisheng; Streets, David

2008-01-01

We present a global model study of multi-decadal changes of atmospheric aerosols and their climate effects using a global chemistry transport model along with the near-term to longterm data records. We focus on a 27-year time period of satellite era from 1980 to 2006, during which a suite of aerosol data from satellite observations, ground-based measurements, and intensive field experiments have become available. We will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which involves a time-varying, comprehensive global emission dataset that we put together in our previous investigations and will be improved/extended in this project. This global emission dataset includes emissions of aerosols and their precursors from fuel combustion, biomass burning, volcanic eruptions, and other sources from 1980 to the present. Using the model and satellite data, we will analyze (1) the long-term global and regional aerosol trends and their relationship to the changes of aerosol and precursor emissions from anthropogenic and natural sources, (2) the intercontinental source-receptor relationships controlled by emission, transport pathway, and climate variability.

Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

NASA Astrophysics Data System (ADS)

Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

2015-11-01

In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall, direct degradation of ecosystems and biodiversity loss. Human population growth and socioeconomic changes, notably on the eastern and southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (Lund-Potsdam-Jena managed Land - LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development paves the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments of the consequences of land use transitions, the influence of management practices and climate change impacts.

Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

NASA Astrophysics Data System (ADS)

Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

2015-06-01

Climate and land use change in the Mediterranean region is expected to affect natural and agricultural ecosystems by decreases in precipitation, increases in temperature as well as biodiversity loss and anthropogenic degradation of natural resources. Demographic growth in the Eastern and Southern shores will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development pave the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments on the consequences of land use transitions, the influence of management practices and climate change impacts.

Joint Applications Pilot of the National Climate Predictions and Projections Platform and the North Central Climate Science Center: Delivering climate projections on regional scales to support adaptation planning

NASA Astrophysics Data System (ADS)

Ray, A. J.; Ojima, D. S.; Morisette, J. T.

2012-12-01

The DOI North Central Climate Science Center (NC CSC) and the NOAA/NCAR National Climate Predictions and Projections (NCPP) Platform and have initiated a joint pilot study to collaboratively explore the "best available climate information" to support key land management questions and how to provide this information. NCPP's mission is to support state of the art approaches to develop and deliver comprehensive regional climate information and facilitate its use in decision making and adaptation planning. This presentation will describe the evolving joint pilot as a tangible, real-world demonstration of linkages between climate science, ecosystem science and resource management. Our joint pilot is developing a deliberate, ongoing interaction to prototype how NCPP will work with CSCs to develop and deliver needed climate information products, including translational information to support climate data understanding and use. This pilot also will build capacity in the North Central CSC by working with NCPP to use climate information used as input to ecological modeling. We will discuss lessons to date on developing and delivering needed climate information products based on this strategic partnership. Four projects have been funded to collaborate to incorporate climate information as part of an ecological modeling project, which in turn will address key DOI stakeholder priorities in the region: Riparian Corridors: Projecting climate change effects on cottonwood and willow seed dispersal phenology, flood timing, and seedling recruitment in western riparian forests. Sage Grouse & Habitats: Integrating climate and biological data into land management decision models to assess species and habitat vulnerability Grasslands & Forests: Projecting future effects of land management, natural disturbance, and CO2 on woody encroachment in the Northern Great Plains The value of climate information: Supporting management decisions in the Plains and Prairie Potholes LCC. NCCSC's role in these projects is to provide the connections between climate data and running ecological models, and prototype these for future work. NCPP will develop capacities to provide enhanced climate information at relevant spatial and temporal scales, both for historical climate and projections of future climate, and will work to link expert guidance and understanding of modeling processes and evaluation of modeling with the use of numerical climate data. Translational information thus is a suite of information that aids in translation of numerical climate information into usable knowledge for applications, e.g. ecological response models, hydrologic risk studies. This information includes technical and scientific aspects including, but not limited to: 1) results of objective, quantitative evaluation of climate models & downscaling techniques, 2) guidance on appropriate uses and interpretation, i.e., understanding the advantages and limitations of various downscaling techniques for specific user applications, 3) characterizing and interpreting uncertainty, 4) Descriptions meaningful to applications, e.g. narratives. NCPP believes that translational information is best co-developed between climate scientists and applications scientists, such as the NC-CSC pilot.

Recent advances in understanding secondary organic aerosols: implications for global climate forcing

NASA Astrophysics Data System (ADS)

Shrivastava, Manish

2017-04-01

Anthropogenic emissions and land-use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding pre-industrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features 1) influence estimates of aerosol radiative forcing and 2) can confound estimates of the historical response of climate to increases in greenhouse gases (e.g. the 'climate sensitivity'). Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, often represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This presentation is based on a US Department of Energy Atmospheric Systems Research sponsored workshop, which highlighted key SOA processes overlooked in climate models that could greatly affect climate forcing estimates. We will highlight the importance of processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including: formation of extremely low-volatility organics in the gas-phase; isoprene epoxydiols (IEPOX) multi-phase chemistry; particle-phase oligomerization; and physical properties such as viscosity. We also highlight some of the recently discovered important processes that involve interactions between natural biogenic emissions and anthropogenic emissions such as effects of sulfur and NOx emissions on SOA. We will present examples of integrated model-measurement studies that relate the observed evolution of organic aerosol mass and number with knowledge of particle properties such as volatility and viscosity. We will also highlight the importance of continuing efforts to rank the most influential SOA processes that affect climate forcing, but are often missing in climate models. Ultimately, gas- and particle-phase chemistry processes that capture the dynamic evolution of number and mass concentrations of SOA particles need to be accurately and efficiently represented in regional and global atmospheric chemistry-climate models.

Hydrologic response of the Crow Wing Watershed, Minnesota, to mid-Holocene climate change

USGS Publications Warehouse

Person, M.; Roy, P.; Wright, H.; Gutowski, W.; Ito, E.; Winter, T.; Rosenberry, D.; Cohen, D.

2007-01-01

In this study, we have integrated a suite of Holocene paleoclimatic proxies with mathematical modeling in an attempt to obtain a comprehensive picture of how watersheds respond to past climate change. A three-dimensional surface-water-groundwater model was developed to assess the effects of mid-Holocene climate change on water resources within the Crow Wing Watershed, Upper Mississippi Basin in north central Minnesota. The model was first calibrated to a 50 yr historical record of average annual surface-water discharge, monthly groundwater levels, and lake-level fluctuations. The model was able to reproduce reasonably well long-term historical records (1949-1999) of water-table and lake-level fluctuations across the watershed as well as stream discharge near the watershed outlet. The calibrated model was then used to reproduce paleogroundwater and lake levels using climate reconstructions based on pollen-transfer functions from Williams Lake just outside the watershed. Computed declines in mid-Holocene lake levels for two lakes at opposite ends of the watershed were between 6 and 18 m. Simulated streamflow near the outlet of the watershed decreased to 70% of modern average annual discharge after ???200 yr. The area covered by wetlands for the entire watershed was reduced by ???16%. The mid-Holocene hydrologic changes indicated by these model results and corroborated by several lake-core records across the Crow Wing Watershed may serve as a useful proxy of the hydrologic response to future warm, dry climatic forecasts (ca. 2050) made by some atmospheric general-circulation models for the glaciated Midwestern United States. ?? 2007 Geological Society of America.

Challenges in global modeling of wetland extent and wetland methane dynamics

NASA Astrophysics Data System (ADS)

Spahni, R.; Melton, J. R.; Wania, R.; Stocker, B. D.; Zürcher, S.; Joos, F.

2012-12-01

Global wetlands are known to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. Modelling of global wetland extent and wetland CH4 dynamics remains a challenge. Here we present results from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) that investigated our present ability to simulate large scale wetland characteristics (e.g. wetland type, water table, carbon cycling, gas transport, etc.) and corresponding CH4 emissions. Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The WETCHIMP experiments showed that while models disagree in spatial and temporal patterns of simulated CH4 emissions and wetland areal extent, they all do agree on a strong positive response to increased carbon dioxide concentrations. WETCHIMP made clear that we currently lack observation data sets that are adequate to evaluate model CH4 soil-atmosphere fluxes at a spatial scale comparable to model grid cells. Thus there are substantial parameter and structural uncertainties in large-scale CH4 emission models. As an illustration of the implications of CH4 emissions on climate we show results of the LPX-Bern model, as one of the models participating in WETCHIMP. LPX-Bern is forced with observed 20th century climate and climate output from an ensemble of five comprehensive climate models for a low and a high emission scenario till 2100 AD. In the high emission scenario increased substrate availability for methanogenesis due to a strong stimulation of net primary productivity, and faster soil turnover leads to an amplification of CH4 emissions with the sharpest increase in peatlands (+180% compared to present). Combined with prescribed anthropogenic CH4 emissions, simulated atmospheric CH4 concentration reaches ~4500 ppbv by 2100 AD, about 800 ppbv more than in standard IPCC scenarios. This represents a significant contribution to radiative forcing of global climate.

The CEOP Inter-Monsoon Studies (CIMS)

NASA Technical Reports Server (NTRS)

Lau, William K. M.

2003-01-01

Prediction of climate relies on models, and better model prediction depends on good model physics. Improving model physics requires the maximal utilization of climate data of the past, present and future. CEOP provides the first example of a comprehensive, integrated global and regional data set, consisting of globally gridded data, reference site in-situ observations, model location time series (MOLTS), and integrated satellite data for a two-year period covering two complete annual cycles of 2003-2004. The monsoon regions are the most important socio-economically in terms of devastation by floods and droughts, and potential impacts from climate change md fluctuatinns nf the hydrologic cyc!e. Scientifically, it is most challenging, because of complex interactions of atmosphere, land and oceans, local vs. remote forcings in contributing to climate variability and change in the region. Given that many common features, and physical teleconnection exist among different monsoon regions, an international research focus on monsoon must be coordinated and sustained. Current models of the monsoon are grossly inadequate for regional predictions. For improvement, models must be confronted with relevant observations, and model physic developers must be made to be aware of the wealth of information from existing climate data, field measurements, and satellite data that can be used to improve models. Model transferability studles must be conducted. CIMS is a major initiative under CEOP to engage the modeling and the observational communities to join in a coordinated effort to study the monsoons. The objectives of CIMS are (a) To provide a better understanding of fundamental physical processes (diurnal cycle, annual cycle, and intraseasonal oscillations) in monsoon regions around the world and (b) To demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. In this talk, I will present the basic concepts of CIMS and the key scientific problems facing monsoon climates and provide examples of common monsoon features, and possible monsoon induced teleconnections linking different parts of the world.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

NASA Astrophysics Data System (ADS)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

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

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob

This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

Tailoring the visual communication of climate projections for local adaptation practitioners in Germany and the UK.

PubMed

Lorenz, Susanne; Dessai, Suraje; Forster, Piers M; Paavola, Jouni

2015-11-28

Visualizations are widely used in the communication of climate projections. However, their effectiveness has rarely been assessed among their target audience. Given recent calls to increase the usability of climate information through the tailoring of climate projections, it is imperative to assess the effectiveness of different visualizations. This paper explores the complexities of tailoring through an online survey conducted with 162 local adaptation practitioners in Germany and the UK. The survey examined respondents' assessed and perceived comprehension (PC) of visual representations of climate projections as well as preferences for using different visualizations in communicating and planning for a changing climate. Comprehension and use are tested using four different graph formats, which are split into two pairs. Within each pair the information content is the same but is visualized differently. We show that even within a fairly homogeneous user group, such as local adaptation practitioners, there are clear differences in respondents' comprehension of and preference for visualizations. We do not find a consistent association between assessed comprehension and PC or use within the two pairs of visualizations that we analysed. There is, however, a clear link between PC and use of graph format. This suggests that respondents use what they think they understand the best, rather than what they actually understand the best. These findings highlight that audience-specific targeted communication may be more complex and challenging than previously recognized. © 2015 The Authors.

Estimation of rainfall using remote sensing for Riyadh climate, KSA

NASA Astrophysics Data System (ADS)

AlHassoun, Saleh A.

2013-05-01

Rainfall data constitute an important parameter for studying water resources-related problems. Remote sensing techniques could provide rapid and comprehensive overview of the rainfall distribution in a given area. Thus, the infrared data from the LandSat satellite in conjunction with the Scofield-oliver method were used to monitor and model rainfall in Riyadh area as a resemble of any area in the Kingdom of Saudi Arabia(KSA). Four convective clouds that covered two rain gage stations were analyzed. Good estimation of rainfall was obtained from satellite images. The results showed that the satellite rainfall estimations were well correlated to rain gage measurements. The satellite climate data appear to be useful for monitoring and modeling rainfall at any area where no rain gage is available.

Determination of Martian Northern Polar Insolation Levels Using a Geodetic Elevation Model

NASA Technical Reports Server (NTRS)

Arrell, J. R.; Zuber, M. T.

2000-01-01

Solar insolation levels at the Martian polar caps bear significantly on the seasonal and climatic cycling of volatiles on that planet. In the northern hemisphere, the Martian surface slopes downhill from the equator to the pole such that the north polar cap is situated in a 5-km-deep hemispheric-scale depression. This large-scale topographic setting plays an important role in the insolation of the northern polar cap. Elevations measured by the Mars Orbiter Laser Altimeter (MOLA) provide comprehensive, high-accuracy topographical information required to precisely determine polar insolation. In this study, we employ a geodetic elevation model to quantify the north polar insolation and consider implications for seasonal and climatic changes. Additional information is contained in original extended abstract.

Identification of robust statistical downscaling methods based on a comprehensive suite of performance metrics for South Korea

NASA Astrophysics Data System (ADS)

Eum, H. I.; Cannon, A. J.

2015-12-01

Climate models are a key provider to investigate impacts of projected future climate conditions on regional hydrologic systems. However, there is a considerable mismatch of spatial resolution between GCMs and regional applications, in particular a region characterized by complex terrain such as Korean peninsula. Therefore, a downscaling procedure is an essential to assess regional impacts of climate change. Numerous statistical downscaling methods have been used mainly due to the computational efficiency and simplicity. In this study, four statistical downscaling methods [Bias-Correction/Spatial Disaggregation (BCSD), Bias-Correction/Constructed Analogue (BCCA), Multivariate Adaptive Constructed Analogs (MACA), and Bias-Correction/Climate Imprint (BCCI)] are applied to downscale the latest Climate Forecast System Reanalysis data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. By split sampling scheme, all methods are calibrated with observational station data for 19 years from 1973 to 1991 are and tested for the recent 19 years from 1992 to 2010. To assess skill of the downscaling methods, we construct a comprehensive suite of performance metrics that measure an ability of reproducing temporal correlation, distribution, spatial correlation, and extreme events. In addition, we employ Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify robust statistical downscaling methods based on the performance metrics for each season. The results show that downscaling skill is considerably affected by the skill of CFSR and all methods lead to large improvements in representing all performance metrics. According to seasonal performance metrics evaluated, when TOPSIS is applied, MACA is identified as the most reliable and robust method for all variables and seasons. Note that such result is derived from CFSR output which is recognized as near perfect climate data in climate studies. Therefore, the ranking of this study may be changed when various GCMs are downscaled and evaluated. Nevertheless, it may be informative for end-users (i.e. modelers or water resources managers) to understand and select more suitable downscaling methods corresponding to priorities on regional applications.

FUPSOL: Modelling the Future and Past Solar Influence on Earth Climate

NASA Astrophysics Data System (ADS)

Anet, J. G.; Rozanov, E.; Peter, T.

2012-04-01

Global warming is becoming one of the main threats to mankind. There is growing evidence that anthropogenic greenhouse gases have become the dominant factor since about 1970. At the same time natural factors of climate change such as solar and volcanic forcings cannot be neglected on longer time scales. Despite growing scientific efforts over the last decades in both, observations and simulations, the uncertainty of the solar contribution to the past climate change remained unacceptably high (IPCC, 2007), the reasons being on one hand missing observations of solar irradiance prior to the satellite era, and on the other hand a majority of models so far not including all processes relevant for solar-climate interactions. This project aims at elucidating the processes governing the effects of solar activity variations on Earth's climate. We use the state-of-the-art coupled atmosphere-ocean-chemistry-climate model (AOCCM) SOCOL (Schraner et al, 2008) developed in Switzerland by coupling the community Earth System Model (ESM) COSMOS distributed by MPI for Meteorology (Hamburg, Germany) with a comprehensive atmospheric chemistry module. The model solves an extensive set of equations describing the dynamics of the atmosphere and ocean, radiative transfer, transport of species, their chemical transformations, cloud formation and the hydrological cycle. The intention is to show how past solar variations affected climate and how the decrease in solar forcing expected for the next decades will affect climate on global and regional scales. We will simulate the global climate system behavior during Dalton minimum (1790 and 1830) and first half of 21st century with a series of multiyear ensemble experiments and perform these experiments using all known anthropogenic and natural climate forcing taken in different combinations to understand the effects of solar irradiance in different spectral regions and particle precipitation variability. Further on, we will quantify the solar influence on global climate in the future by evaluating the simulations and using information from past analogs such as the Dalton minimum. In the end, the project aims at reducing the uncertainty of the solar contribution to past and future climate change, which so far remained high despite many years of analyses of observational records and theoretical investigations with climate models of different complexity.

The Green Sahara: Climate Change, Hydrologic History and Human Occupation

NASA Technical Reports Server (NTRS)

Blom, Ronald G.; Farr, Tom G.; Feynmann, Joan; Ruzmaikin, Alexander; Paillou, Philippe

2009-01-01

Archaeology can provide insight into interactions of climate change and human activities in sensitive areas such as the Sahara, to the benefit of both disciplines. Such analyses can help set bounds on climate change projections, perhaps identify elements of tipping points, and provide constraints on models. The opportunity exists to more precisely constrain the relationship of natural solar and climate interactions, improving understanding of present and future anthropogenic forcing. We are beginning to explore the relationship of human occupation of the Sahara and long-term solar irradiance variations synergetic with changes in atmospheric-ocean circulation patterns. Archaeological and climate records for the last 12 K years are gaining adequate precision to make such comparisons possible. We employ a range of climate records taken over the globe (e.g. Antarctica, Greenland, Cariaco Basin, West African Ocean cores, records from caves) to identify the timing and spatial patterns affecting Saharan climate to compare with archaeological records. We see correlation in changing ocean temperature patterns approx. contemporaneous with drying of the Sahara approx. 6K years BP. The role of radar images and other remote sensing in this work includes providing a geographically comprehensive geomorphic overview of this key area. Such coverage is becoming available from the Japanese PALSAR radar system, which can guide field work to collect archaeological and climatic data to further constrain the climate change chronology and link to models. Our initial remote sensing efforts concentrate on the Gilf Kebir area of Egypt.

The Global Climate Dashboard: a Software Interface to Stream Comprehensive Climate Data

NASA Astrophysics Data System (ADS)

Gardiner, N.; Phillips, M.; NOAA Climate Portal Dashboard

2011-12-01

The Global Climate Dashboard is an integral component of NOAA's web portal to climate data, services, and value-added content for decision-makers, teachers, and the science-attentive public (www.clmate.gov). The dashboard provides a rapid view of observational data that demonstrate climate change and variability, as well as outputs from the Climate Model Intercomparison Project version 3, which was built to support the Intergovernmental Panel on Climate Change fourth assessment. The data shown in the dashboard therefore span a range of climate science disciplines with applications that serve audiences with diverse needs. The dashboard is designed with reusable software components that allow it to be implemented incrementally on a wide range of platforms including desktops, tablet devices, and mobile phones. The underlying software components support live streaming of data and provide a way of encapsulating graph sytles and other presentation details into a device-independent standard format that results in a common visual look and feel across all platforms. Here we describe the pedagogical objectives, technical implementation, and the deployment of the dashboard through climate.gov and partner web sites and describe plans to develop a mobile application using the same framework.

Making decisions based on an imperfect ensemble of climate simulators: strategies and future directions

NASA Astrophysics Data System (ADS)

Sanderson, B. M.

2017-12-01

The CMIP ensembles represent the most comprehensive source of information available to decision-makers for climate adaptation, yet it is clear that there are fundamental limitations in our ability to treat the ensemble as an unbiased sample of possible future climate trajectories. There is considerable evidence that models are not independent, and increasing complexity and resolution combined with computational constraints prevent a thorough exploration of parametric uncertainty or internal variability. Although more data than ever is available for calibration, the optimization of each model is influenced by institutional priorities, historical precedent and available resources. The resulting ensemble thus represents a miscellany of climate simulators which defy traditional statistical interpretation. Models are in some cases interdependent, but are sufficiently complex that the degree of interdependency is conditional on the application. Configurations have been updated using available observations to some degree, but not in a consistent or easily identifiable fashion. This means that the ensemble cannot be viewed as a true posterior distribution updated by available data, but nor can observational data alone be used to assess individual model likelihood. We assess recent literature for combining projections from an imperfect ensemble of climate simulators. Beginning with our published methodology for addressing model interdependency and skill in the weighting scheme for the 4th US National Climate Assessment, we consider strategies for incorporating process-based constraints on future response, perturbed parameter experiments and multi-model output into an integrated framework. We focus on a number of guiding questions: Is the traditional framework of confidence in projections inferred from model agreement leading to biased or misleading conclusions? Can the benefits of upweighting skillful models be reconciled with the increased risk of truth lying outside the weighted ensemble distribution? If CMIP is an ensemble of partially informed best-guesses, can we infer anything about the parent distribution of all possible models of the climate system (and if not, are we implicitly under-representing the risk of a climate catastrophe outside of the envelope of CMIP simulations)?

The AgMIP Wheat Pilot: A multi-model approach for climate change impact assessments.

NASA Astrophysics Data System (ADS)

Asseng, S.

2012-12-01

Asseng S., F. Ewert, C. Rosenzweig, J.W. Jones, J.L. Hatfield, A. Ruane, K.J. Boote, P. Thorburn, R.P. Rötter, D. Cammarano, N. Brisson, B. Basso, P. Martre, D. Ripoche, P. Bertuzzi, P. Steduto, L. Heng, M.A. Semenov, P. Stratonovitch, C. Stockle, G. O'Leary, P.K. Aggarwal, S. Naresh Kumar, C. Izaurralde, J.W. White, L.A. Hunt, R. Grant, K.C. Kersebaum, T. Palosuo, J. Hooker, T. Osborne, J. Wolf, I. Supit, J.E. Olesen, J. Doltra, C. Nendel, S. Gayler, J. Ingwersen, E. Priesack, T. Streck, F. Tao, C. Müller, K. Waha, R. Goldberg, C. Angulo, I. Shcherbak, C. Biernath, D. Wallach, M. Travasso, A. Challinor. Abstract: Crop simulation models have been used to assess the impact of climate change on agriculture. These assessments are often carried out with a single model in a limited number of environments and without determining the uncertainty of simulated impacts. There is a need for a coordinated effort bringing together multiple modeling teams which has been recognized by the Agricultural Model Intercomparison and Improvement Project (AgMIP; www.agmip.org). AgMIP aims to provide more robust estimates of climate impacts on crop yields and agricultural trade, including estimates of associated uncertainties. Here, we present the AgMIP Wheat Pilot Study, the most comprehensive model intercomparison of the response of wheat crops to climate change to date, including 27 wheat models. Crop model uncertainties in assessing climate change impacts are explored and compared with field experimental and Global Circulation Model uncertainties. Causes of impact uncertainties and ways to reduce these are discussed.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Assessing Portuguese Guadiana Basin water management impacts under climate change and paleoclimate variability

NASA Astrophysics Data System (ADS)

Maia, Rodrigo; Oliveira, Bruno; Ramos, Vanessa; Brekke, Levi

2014-05-01

The water balance in each reservoir and the subsequent, related, water resource management decisions are, presently, highly information dependent and are therefore often limited to a reactive response (even if aimed towards preventing future issues regarding the water system). Taking advantage of the availability of scenarios for climate projections, it is now possible to estimate the likely future evolution of climate which represents an important stepping stone towards proactive, adaptative, water resource management. The purpose of the present study was to assess the potential effects of climate change in terms of temperature, precipitation, runoff and water availability/scarcity for application in water resource management decisions. The analysis here presented was applied to the Portuguese portion of the Guadiana River Basin, using a combination of observed climate and runoff data and the results of the Global Climate Models. The Guadiana River Basin was represented by its reservoirs on the Portuguese portion of the basin and, for the future period, an estimated value of the inflows originating in the Spanish part of the Basin. The change in climate was determined in terms of relative and absolute variations of climate (precipitation and temperature) and hydrology (runoff and water balance related information). Apart from the previously referred data, an hydrological model and a water management model were applied so as to obtain an extended range of data regarding runoff generation (calibrated to observed data) and water balance in the reservoirs (considering the climate change impacts in the inflows, outflows and water consumption). The water management model was defined in order to represent the reservoirs interaction including upstream to downstream discharges and water transfers. Under the present climate change context, decision-makers and stakeholders are ever more vulnerable to the uncertainties of climate. Projected climate in the Guadiana basin indicates an increase in temperatures and a reduction of the precipitation values which go well beyond the observed values and, therefore, must be forcefully included in any realistic proactive water resource management decision. Using the results of this study it is possible to estimate future water availability and consumption satisfaction allowing for the elaboration of informed management decisions. In this study, the CMIP 3 Global Climate Models were considered for the definition of the effects of climate change, using the median and extreme tendencies based on the range of variation of the multiple climate projection scenarios. The observed climate variability, along with these model-derived tendencies, were used to inform the hydrology and water management models for the historical and future periods, respectively. Additionally, for a more comprehensive analysis on climate variability, a stochastic model was implemented based on the paleoclimate variability obtained from tree-ring records.

Using Bayesian networks to assess the vulnerability of Hawaiian terrestrial biota to climate change

NASA Astrophysics Data System (ADS)

Fortini, L.; Jacobi, J.; Price, J.; Vorsino, A.; Paxton, E.; Amidon, F.; 'Ohukani'ohi'a Gon, S., III; Koob, G.; Brink, K.; Burgett, J.; Miller, S.

2012-12-01

As the effects of climate change on individual species become increasingly apparent, there is a clear need for effective adaptation planning to prevent an increase in species extinctions worldwide. Given the limited understanding of species responses to climate change, vulnerability assessments and species distribution models (SDMs) have been two common tools used to jump-start climate change adaptation efforts. However, although these two approaches generally serve the same purpose of understanding species future responses to climate change, they have rarely mixed. In collaboration with research and management partners from federal, state and non-profit organizations, we are conducting a climate change vulnerability assessment for hundreds of plant and forest bird species of the Main Hawaiian Islands. This assessment is the first to comprehensively consider the potential threats of climate change to a significant portion of Hawaii's fauna and flora (over one thousand species considered) and thus fills a critical gap defined by natural resource scientists and managers in the region. We have devised a flexible approach that effectively integrates species distribution models into a vulnerability assessment framework that can be easily updated with improved models and data. This tailors our assessment approach to the Pacific Island reality of often limited and fragmented information on species and large future climate uncertainties, This vulnerability assessment is based on a Bayesian network-based approach that integrates multiple landscape (e.g., topographic diversity, dispersal barriers), species trait (e.g., generation length, fecundity) and expert-knowledge based information (e.g., capacity to colonize restored habitat) relevant to long-term persistence of species under climate change. Our presentation will highlight some of the results from our assessment but will mainly focus on the utility of the flexible approach we have developed and its potential application in other settings.

Climate and soil type together explain the distribution of microendemic species in a biodiversity hotspot.

PubMed

Nattier, Romain; Grandcolas, Philippe; Pellens, Roseli; Jourdan, Hervé; Couloux, Arnaud; Poulain, Simon; Robillard, Tony

2013-01-01

The grasshopper genus Caledonula, endemic to New Caledonia, was studied to understand the evolution of species distributions in relation to climate and soil types. Based on a comprehensive sampling of 80 locations throughout the island, the genus was represented by five species, four of which are new to science, of which three are described here. All the species have limited distributions in New Caledonia. Bioclimatic niche modelling shows that all the species were found in association with a wet climate and reduced seasonality, explaining their restriction to the southern half of the island. The results suggest that the genus was ancestrally constrained by seasonality. A molecular phylogeny was reconstructed using two mitochondrial and two nuclear markers. The partially resolved tree showed monophyly of the species found on metalliferous soils, and molecular dating indicated a rather recent origin for the genus. Adaptation to metalliferous soils is suggested by both morphological changes and radiation on these soils. The genus Caledonula is therefore a good model to understand the origin of microendemism in the context of recent and mixed influences of climate and soil type.

Assessing and Upgrading Ocean Mixing for the Study of Climate Change

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Complementing carbon prices with technology policies to keep climate targets within reach

NASA Astrophysics Data System (ADS)

Bertram, Christoph; Luderer, Gunnar; Pietzcker, Robert C.; Schmid, Eva; Kriegler, Elmar; Edenhofer, Ottmar

2015-03-01

Economic theory suggests that comprehensive carbon pricing is most efficient to reach ambitious climate targets, and previous studies indicated that the carbon price required for limiting global mean warming to 2 °C is between US$16 and US$73 per tonne of CO2 in 2015 (ref. ). Yet, a global implementation of such high carbon prices is unlikely to be politically feasible in the short term. Instead, most climate policies enacted so far are technology policies or fragmented and moderate carbon pricing schemes. This paper shows that ambitious climate targets can be kept within reach until 2030 despite a sub-optimal policy mix. With a state-of-the-art energy-economy model we quantify the interactions and unique effects of three major policy components: (1) a carbon price starting at US$7 per tonne of CO2 in 2015 to incentivize economy-wide mitigation, flanked by (2) support for low-carbon energy technologies to pave the way for future decarbonization, and (3) a moratorium on new coal-fired power plants to limit stranded assets. We find that such a mix limits the efficiency losses compared with the optimal policy, and at the same time lowers distributional impacts. Therefore, we argue that this instrument mix might be a politically more feasible alternative to the optimal policy based on a comprehensive carbon price alone.

Land use allocation model considering climate change impact

NASA Astrophysics Data System (ADS)

Lee, D. K.; Yoon, E. J.; Song, Y. I.

2017-12-01

In Korea, climate change adaptation plans are being developed for each administrative district based on impact assessments constructed in various fields. This climate change impact assessments are superimposed on the actual space, which causes problems in land use allocation because the spatial distribution of individual impacts may be different each other. This implies that trade-offs between climate change impacts can occur depending on the composition of land use. Moreover, the actual space is complexly intertwined with various factors such as required area, legal regulations, and socioeconomic values, so land use allocation in consideration of climate change can be very difficult problem to solve (Liu et al. 2012; Porta et al. 2013).Optimization techniques can generate a sufficiently good alternatives for land use allocation at the strategic level if only the fitness function of relationship between impact and land use composition are derived. It has also been noted that land use optimization model is more effective than the scenario-based prediction model in achieving the objectives for problem solving (Zhang et al. 2014). Therefore in this study, we developed a quantitative tool, MOGA (Multi Objective Genetic Algorithm), which can generate a comprehensive land use allocations considering various climate change impacts, and apply it to the Gangwon-do in Korea. Genetic Algorithms (GAs) are the most popular optimization technique to address multi-objective in land use allocation. Also, it allows for immediate feedback to stake holders because it can run a number of experiments with different parameter values. And it is expected that land use decision makers and planners can formulate a detailed spatial plan or perform additional analysis based on the result of optimization model. Acknowledgments: This work was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program (Project number: 2014001310006)"

Climate Drivers of Blue Intensity from Two Eastern North American Conifers

NASA Astrophysics Data System (ADS)

Rayback, S. A.; Kilbride, J.; Pontius, J.; Tait, E.; Little, J.

2016-12-01

Gaining a comprehensive understanding of the climatic factors that drive tree radial growth over time is important in the context of global climate change. Herein, we explore minimum blue intensity (BI), a measure of lignin context in the latewood of tree rings, with the objective of developing BI chronologies for two eastern North American conifers to identify and explore climatic drivers and to compare BI-climate relationships to those of tree-ring widths (TRW). Using dendrochronological techniques, Tsuga canadensis and Picea rubens TRW and BI chronologies were developed at Abbey Pond (ABP) and The Cape National Research Area (CAPE), Vermont, USA, respectively. Climate drivers (1901-2010) were investigated using correlation and response function analyses and generalized linear mixed models. The ABP T. canadensis BI model explained the highest amount of variance (R2 = 0.350, adjR2=0.324) with September Tmin and June total percent cloudiness as predictors. The ABP T. canadensis TRW model explained 34% of the variance (R2 = 0.340, adjR2=0.328) with summer total precipitation and June PDSI as predictors. The CAPE P. rubens TRW and BI models explained 31% of the variance (R2 = 0.33, adjR2=0.310), based on p July Tmax, p August Tmean and fall Tmin as predictors, and 7% (R2 = 0.068, adjR2=0.060) based on Spring Tmin as the predictor, respectively. Moving window analyses confirm the moisture sensitivity of T. canadensis TRW and now BI and suggest an extension of the growing season. Similarly, P. rubens TRW responded consistently negative to high growing season temperatures, but TRW and BI benefited from a longer growing season. This study introduces two new BI chronologies, the first from northeastern North America, and highlights shifts underway in tree response to changing climate.

Climate Change Impact on Water Balance at the Chipola River Watershed in Florida

NASA Astrophysics Data System (ADS)

Griffen, J. M.; Chen, X.; Wang, D.; Hagen, S. C.

2013-12-01

As the largest tributary to the Apalachicola River, the Chipola River originates in southern Alabama, flows through the Florida Panhandle and drains into the Gulf of Mexico. The Chipola watershed is located in an intermediate climate environment with an aridity index of approximately 1.0. However, climate change affects the hydrologic cycle of Chipola River watershed at various temporal and spatial scales. Studying the effects of climate variations is of great importance for water and environmental management purposes in this watershed. This research is mainly focused on assessing climate change impact on the partitioning of rainfall and the following runoff generation in Chipola watershed, from long-term mean annual to inter-annual and to seasonal and monthly scales. A comprehensive water balance model at inter-annual scale is built in this study based on Budyko's framework, two-stage runoff theory and proportionality hypothesis. The inter-annual scale model considers the impact of storage change, seasonality and landscape controls, which are normally assumed to be negligible on a long-term scale. The model is applied to the Chipola River Watershed in Florida to project future water balance pattern with the input from a Regional Climate Model projection. Based on the projection results: evaporation will increase in the future in all 12 months; runoff will increase only in dry months of July to October, while significantly decrease in wet months of December to April; storage change will increase in wet months of January to April, while decrease in the dry months of August to November.

Towards a regional climate model coupled to a comprehensive hydrological model

NASA Astrophysics Data System (ADS)

Rasmussen, S. H.; Drews, M.; Christensen, J. H.; Butts, M. B.; Jensen, K. H.; Refsgaard, J.; Hydrological ModellingAssessing Climate Change Impacts At Different Scales (Hyacints)

2010-12-01

When planing new ground water abstractions wells, building areas, roads or other land use activities information about expected future groundwater table location for the lifetime of the construction may be critical. The life time of an abstraction well can be expected to be more than 50 years, while if for buildings may be up to 100 years or more. The construction of an abstraction well is expensive and it is important to know if clean groundwater is available for its expected life time. The future groundwater table is depending on the future climate. With climate change the hydrology is expected to change as well. Traditionally, this assessment has been done by driving hydrological models with output from a climate model. In this way feedback between the groundwater hydrology and the climate is neglected. Neglecting this feedback can lead to imprecise or wrong results. The goal of this work is to couple the regional climate model HIRHAM (Christensen et al. 2006) to the hydrological model MIKE SHE (Graham and Butts, 2006). The coupling exploits the new OpenMI technology that provides a standardized interface to define, describe and transfer data on a time step basis between software components that run simultaneously (Gregersen et al., 2007). HIRHAM runs on a UNIX platform whereas MIKE SHE and OpenMI are under WINDOWS. Therefore the first critical task has been to develop an effective communication link between the platforms. The first step towards assessing the coupled models performance are addressed by looking at simulated land-surface atmosphere feedback through variables such as evapotranspiration, sensible heat flux and soil moisture content. Christensen, O.B., Drews, M., Christensen, J.H., Dethloff, K., Ketelsen, K., Hebestadt, I. and Rinke, A. (2006) The HIRHAM Regional Climate Model. Version 5; DMI Scientific Report 0617. Danish Meteorological Institute. Graham, D.N. and Butts, M.B. (2005) Flexible, integrated watershed modelling with MIKE SHE, In Watershed Models, (Eds. V.P. Singh & D.K. Frevert) CRC Press. Pages 245-272, ISBN: 0849336090. Gregersen, J.B., Gijsbers, P.J.A. and Westen, S.J.P. (2007) OpenMI: Open modelling interface. Journal of Hydroinformatics, 09.3, 175191. doi: 10.2166/hydro.2007.023.

Development of a Permafrost Modeling Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Overeem, I.; Jafarov, E. E.; Piper, M.; Schaefer, K. M.

2016-12-01

Permafrost is seen as an essential Arctic climate indicator, and feedback of thawing permafrost to the global climate system through the impacts on the global carbon cycle remain an important research topic. Observations can assess the current state of permafrost, but models are eventually essential to make predictions of future permafrost extent. The purpose of our project, which we call PermaModel, is to develop an easy-to-access and comprehensive cyberinfrastructure aimed at promoting and improving permafrost modeling. The PermaModel Integrated Modeling Toolbox (IMT) includes three permafrost models of increasing complexity. The IMT will be housed within the existing cyberinfrastructure of the Community Surface Dynamics Modeling System (CSDMS), and made publically accessible through the CSDMS Web Modeling Tool (WMT). The WMT will provide easy online access to students, scientists, and stakeholders who want to use permafrost models, but lack the expertise. We plan to include multiple sets of sample inputs, representing a variety of conditions and locations, to enable immediate use of the IMT. We present here the first permafrost model, which is envisioned to be the most suitable for teaching purposes. The model promotes understanding of a 1D heat equation and permafrost active layer dynamics under monthly temperature/climate drivers in an online environment. Modeling labs are presented through the CSDMS Educational Repository and we solicit feedback from faculty for further design of these resources.

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

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

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

2014-01-01

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

Modeling the Climatic Consequences of Geoengineering

NASA Astrophysics Data System (ADS)

Somerville, R. C.

2005-12-01

The last half-century has seen the development of physically comprehensive computer models of the climate system. These models are the primary tool for making predictions of climate change due to human activities, such as emitting greenhouse gases into the atmosphere. Because scientific understanding of the climate system is incomplete, however, any climate model will necessarily have imperfections. The inevitable uncertainties associated with these models have sometimes been cited as reasons for not taking action to reduce such emissions. Climate models could certainly be employed to predict the results of various attempts at geoengineering, but many questions would arise. For example, in considering proposals to increase the planetary reflectivity by brightening parts of the land surface or by orbiting mirrors, can models be used to bound the results and to warm of unintended consequences? How could confidence limits be placed on such model results? How can climate changes due to proposed geoengineering be distinguished from natural variability? There are historical parallels on smaller scales, in which models have been employed to predict the results of attempts to alter the weather, such as the use of cloud seeding for precipitation enhancement, hail suppression and hurricane modification. However, there are also many lessons to be learned from the recent record of using models to simulate the effects of the great unintended geoengineering experiment involving greenhouse gases, now in progress. In this major research effort, the same types of questions have been studied at length. The best modern models have demonstrated an impressive ability to predict some aspects of climate change. A large body of evidence has already accumulated through comparing model predictions to many observed aspects of recent climate change, ranging from increases in ocean heat content to changes in atmospheric water vapor to reductions in glacier extent. The preponderance of expert opinion is that this evidence is now sufficient to establish the human cause of much recent climate change. Nevertheless, no model can provide detailed and fully trustworthy answers to every possible question of interest. As an example, how will the climatology of Atlantic hurricanes change as the greenhouse effect becomes stronger? Can models reliably forecast changes in the length of the hurricane season or changes in the geographical regions affected by hurricanes? The answer is no, or at least, not yet. Additionally, climate models are not based entirely on first principles, such as Newtonian physics. Instead, they have been developed primarily to simulate the present climate and relatively small departures from it. To achieve this goal, a certain amount of empiricism has been built into the models. The result has sometimes been to increase the apparent realism of models at the cost of limiting their generality. Thus, the available climate models may well be less capable of simulating a geoengineering experiment that might lead to a radically different climate. New model development may be required for this new application. The challenge is to distinguish between what models can and cannot do well. It would be irresponsible and unethical, either to undertake geoengineering projects without modeling their consequences, or to place blind faith in the models. To decide how best to model a proposed geoengineering technique requires a deep understanding of the strengths and weaknesses of climate models. The history of modeling successes and failures is a valuable guide to the wise interpretation of model results.

Modeling perceptions of climatic risk in crop production.

PubMed

Reinmuth, Evelyn; Parker, Phillip; Aurbacher, Joachim; Högy, Petra; Dabbert, Stephan

2017-01-01

In agricultural production, land-use decisions are components of economic planning that result in the strategic allocation of fields. Climate variability represents an uncertainty factor in crop production. Considering yield impact, climatic influence is perceived during and evaluated at the end of crop production cycles. In practice, this information is then incorporated into planning for the upcoming season. This process contributes to attitudes toward climate-induced risk in crop production. In the literature, however, the subjective valuation of risk is modeled as a risk attitude toward variations in (monetary) outcomes. Consequently, climatic influence may be obscured by political and market influences so that risk perceptions during the production process are neglected. We present a utility concept that allows the inclusion of annual risk scores based on mid-season risk perceptions that are incorporated into field-planning decisions. This approach is exemplified and implemented for winter wheat production in the Kraichgau, a region in Southwest Germany, using the integrated bio-economic simulation model FarmActor and empirical data from the region. Survey results indicate that a profitability threshold for this crop, the level of "still-good yield" (sgy), is 69 dt ha-1 (regional mean Kraichgau sample) for a given season. This threshold governs the monitoring process and risk estimators. We tested the modeled estimators against simulation results using ten projected future weather time series for winter wheat production. The mid-season estimators generally proved to be effective. This approach can be used to improve the modeling of planning decisions by providing a more comprehensive evaluation of field-crop response to climatic changes from an economic risk point of view. The methodology further provides economic insight in an agrometeorological context where prices for crops or inputs are lacking, but farmer attitudes toward risk should still be included in the analysis.

Identifying Electricity Capacity at Risk to Changes in Climate and Water Resources in the United States

NASA Astrophysics Data System (ADS)

Miara, A.; Macknick, J.; Vorosmarty, C. J.; Corsi, F.; Fekete, B. M.; Newmark, R. L.; Tidwell, V. C.; Cohen, S. M.

2016-12-01

Thermoelectric plants supply 85% of electricity generation in the United States. Under a warming climate, the performance of these power plants may be reduced, as thermoelectric generation is dependent upon cool ambient temperatures and sufficient water supplies at adequate temperatures. In this study, we assess the vulnerability and reliability of 1,100 operational power plants (2015) across the contiguous United States under a comprehensive set of climate scenarios (five Global Circulation Models each with four Representative Concentration Pathways). We model individual power plant capacities using the Thermoelectric Power and Thermal Pollution model (TP2M) coupled with the Water Balance Model (WBM) at a daily temporal resolution and 5x5 km spatial resolution. Together, these models calculate power plant capacity losses that account for geophysical constraints and river network dynamics. Potential losses at the single-plant level are put into a regional energy security context by assessing the collective system-level reliability at the North-American Electricity Reliability Corporation (NERC) regions. Results show that the thermoelectric sector at the national level has low vulnerability under the contemporary climate and that system-level reliability in terms of available thermoelectric resources relative to thermoelectric demand is sufficient. Under future climates scenarios, changes in water availability and warm ambient temperatures lead to constraints on operational capacity and increased vulnerability at individual power plant sites across all regions in the United States. However, there is a strong disparity in regional vulnerability trends and magnitudes that arise from each region's climate, hydrology and technology mix. Despite increases in vulnerabilities at the individual power plant level, regional energy systems may still be reliable (with no system failures) due to sufficient back-up reserve capacities.

Modeling perceptions of climatic risk in crop production

PubMed Central

Parker, Phillip; Aurbacher, Joachim; Högy, Petra; Dabbert, Stephan

2017-01-01

In agricultural production, land-use decisions are components of economic planning that result in the strategic allocation of fields. Climate variability represents an uncertainty factor in crop production. Considering yield impact, climatic influence is perceived during and evaluated at the end of crop production cycles. In practice, this information is then incorporated into planning for the upcoming season. This process contributes to attitudes toward climate-induced risk in crop production. In the literature, however, the subjective valuation of risk is modeled as a risk attitude toward variations in (monetary) outcomes. Consequently, climatic influence may be obscured by political and market influences so that risk perceptions during the production process are neglected. We present a utility concept that allows the inclusion of annual risk scores based on mid-season risk perceptions that are incorporated into field-planning decisions. This approach is exemplified and implemented for winter wheat production in the Kraichgau, a region in Southwest Germany, using the integrated bio-economic simulation model FarmActor and empirical data from the region. Survey results indicate that a profitability threshold for this crop, the level of “still-good yield” (sgy), is 69 dt ha-1 (regional mean Kraichgau sample) for a given season. This threshold governs the monitoring process and risk estimators. We tested the modeled estimators against simulation results using ten projected future weather time series for winter wheat production. The mid-season estimators generally proved to be effective. This approach can be used to improve the modeling of planning decisions by providing a more comprehensive evaluation of field-crop response to climatic changes from an economic risk point of view. The methodology further provides economic insight in an agrometeorological context where prices for crops or inputs are lacking, but farmer attitudes toward risk should still be included in the analysis. PMID:28763471

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

State-Dependence of the Climate Sensitivity in Earth System Models of Intermediate Complexity

NASA Astrophysics Data System (ADS)

Pfister, Patrik L.; Stocker, Thomas F.

2017-10-01

Growing evidence from general circulation models (GCMs) indicates that the equilibrium climate sensitivity (ECS) depends on the magnitude of forcing, which is commonly referred to as state-dependence. We present a comprehensive assessment of ECS state-dependence in Earth system models of intermediate complexity (EMICs) by analyzing millennial simulations with sustained 2×CO2 and 4×CO2 forcings. We compare different extrapolation methods and show that ECS is smaller in the higher-forcing scenario in 12 out of 15 EMICs, in contrast to the opposite behavior reported from GCMs. In one such EMIC, the Bern3D-LPX model, this state-dependence is mainly due to the weakening sea ice-albedo feedback in the Southern Ocean, which depends on model configuration. Due to ocean-mixing adjustments, state-dependence is only detected hundreds of years after the abrupt forcing, highlighting the need for long model integrations. Adjustments to feedback parametrizations of EMICs may be necessary if GCM intercomparisons confirm an opposite state-dependence.

What is Climate Leadership: Examples and Lessons Learned in Organizational Leadership Webinar

EPA Pesticide Factsheets

Organizations discuss creating comprehensive GHG inventories and aggressive emissions reduction goals, as well as leadership in their internal response to climate change, through engaging partners and addressing climate risk in their enterprise strategies.

Towards a comprehensive assessment and framework for low and high flow water risks

NASA Astrophysics Data System (ADS)

Motschmann, Alina; Huggel, Christian; Drenkhan, Fabian; León, Christian

2017-04-01

Driven by international organizations such as the Intergovernmental Panel on Climate Change (IPCC) the past years have seen a move from a vulnerability concept of climate change impacts towards a risk framework. Risk is now conceived at the intersection of climate-driven hazard and socioeconomic-driven vulnerability and exposure. The concept of risk so far has been mainly adopted for sudden-onset events. However, for slow-onset and cumulative climate change impacts such as changing water resources there is missing clarity and experience how to apply a risk framework. Research has hardly dealt with the challenge of how to integrate both low and high flow risks in a common framework. Comprehensive analyses of risks related to water resources considering climate change within multi-dimensional drivers across different scales are complex and often missing in climate-sensitive mountain regions where data scarcity and inconsistencies represent important limitations. Here we review existing vulnerability and risk assessments of low and high flow water conditions and identify critical conceptual and practical gaps. Based on this, we develop an integrated framework for low and high flow water risks which is applicable to both past and future conditions. The framework explicitly considers a water balance model simulating both water supply and demand on a daily basis. We test and apply this new framework in the highly glacierized Santa River catchment (SRC, Cordillera Blanca, Peru), representative for many developing mountain regions with both low and high flow water risks and poor data availability. In fact, in the SRC, both low and high flow hazards, such as droughts and floods, play a central role especially for agricultural, hydropower, domestic and mining use. During the dry season (austral winter) people are increasingly affected by water scarcity due to shrinking glaciers supplying melt water. On the other hand during the wet season (austral summer) high flow water risks are associated with hazards such as floods and debris flows and high socioeconomic vulnerability and exposure of e. g. infrastructure. Nonetheless, comprehensive water resource risk studies have barely been developed in the SRC and other developing high-mountain regions. To consider all components of risks as well as the economic and social conditions for different processes, a comprehensive risk assessment is needed. The urgency of this matter is emphasized by recent social conflicts in the SRC and the tropical Andes in general, related to prevailing drought conditions in combination with weak state institutions and unequal decision-making as well as differentiated perspectives on low flow versus high flow risks.

The Decadal Climate Prediction Project (DCPP) contribution to CMIP6

DOE PAGES

Boer, George J.; Smith, Douglas M.; Cassou, Christophe; ...

2016-01-01

The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Predictionmore » (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Furthermore, groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.« less

The Effects of Weather and Climate Change on Dengue

PubMed Central

Colón-González, Felipe J.; Fezzi, Carlo; Lake, Iain R.; Hunter, Paul R.

2013-01-01

Background There is much uncertainty about the future impact of climate change on vector-borne diseases. Such uncertainty reflects the difficulties in modelling the complex interactions between disease, climatic and socioeconomic determinants. We used a comprehensive panel dataset from Mexico covering 23 years of province-specific dengue reports across nine climatic regions to estimate the impact of weather on dengue, accounting for the effects of non-climatic factors. Methods and Findings Using a Generalized Additive Model, we estimated statistically significant effects of weather and access to piped water on dengue. The effects of weather were highly nonlinear. Minimum temperature (Tmin) had almost no effect on dengue incidence below 5°C, but Tmin values above 18°C showed a rapidly increasing effect. Maximum temperature above 20°C also showed an increasing effect on dengue incidence with a peak around 32°C, after which the effect declined. There is also an increasing effect of precipitation as it rose to about 550 mm, beyond which such effect declines. Rising access to piped water was related to increasing dengue incidence. We used our model estimations to project the potential impact of climate change on dengue incidence under three emission scenarios by 2030, 2050, and 2080. An increase of up to 40% in dengue incidence by 2080 was estimated under climate change while holding the other driving factors constant. Conclusions Our results indicate that weather significantly influences dengue incidence in Mexico and that such relationships are highly nonlinear. These findings highlight the importance of using flexible model specifications when analysing weather–health interactions. Climate change may contribute to an increase in dengue incidence. Rising access to piped water may aggravate dengue incidence if it leads to increased domestic water storage. Climate change may therefore influence the success or failure of future efforts against dengue. PMID:24244765

Integrating Climate Change Science and Sustainability in Environmental Science, Sociology, Philosophy and Business Courses.

NASA Astrophysics Data System (ADS)

Boudrias, M. A.; Cantzler, J.; Croom, S.; Huston, C.; Woods, M.

2015-12-01

Courses on sustainability can be taught from multiple perspectives with some focused on specific areas (environmental, socio-cultural, economic, ethics) and others taking a more integrated approach across areas of sustainability and academic disciplines. In conjunction with the Climate Change Education Program efforts to enhance climate change literacy with innovative approaches, resources and communication strategies developed by Climate Education Partners were used in two distinct ways to integrate climate change science and impacts into undergraduate and graduate level courses. At the graduate level, the first lecture in the MBA program in Sustainable Supply Chain Management is entirely dedicated to climate change science, local and global impacts and discussions about key messages to communicate to the business community. Basic science concepts are integrated with discussions about mitigation and adaptation focused on business leaders. The concepts learned are then applied to the semester-long business plan project for the students. At the undergraduate level, a new model of comprehensive integration across disciplines was implemented in Spring 2015 across three courses on Sustainability each with a specific lens: Natural Science, Sociology and Philosophy. All three courses used climate change as the 'big picture' framing concept and had similar learning objectives creating a framework where lens-specific topics, focusing on depth in a discipline, were balanced with integrated exercises across disciplines providing breadth and possibilities for integration. The comprehensive integration project was the creation of the climate action plan for the university with each team focused on key areas of action (water, energy, transportation, etc.) and each team built with at least one member from each class ensuring a natural science, sociological and philosophical perspective. The final project was presented orally to all three classes and an integrated paper included all three perspectives. The best projects are being compiled so they can be shared with the University of San Diego's planning committee.

The Impact of Effective Scheduling on the Climate and Culture in a Large Comprehensive High School

ERIC Educational Resources Information Center

Hayes, Matthew

2013-01-01

Scheduling in any school or organization plays a vital role in the effectiveness that stakeholders' needs are met. The administration at a large comprehensive high school in the Charlotte Mecklenburg School District realized that in order for their school to meet the changing needs of its student body, it had to build a culture and climate that…

A conceptual model for the impact of climate change on fox rabies in Alaska, 1980–2010

PubMed Central

Kim, Bryan I.; Blanton, Jesse D.; Gilbert, Amy; Castrodale, Louisa; Hueffer, Karsten; Slate, Dennis; Rupprecht, Charles E.

2013-01-01

The direct and interactive effects of climate change on host species and infectious disease dynamics are likely to initially manifest at latitudinal extremes. As such, Alaska represents a region in the United States for introspection on climate change and disease. Rabies is enzootic among arctic foxes (Vulpes lagopus) throughout the northern polar region. In Alaska, arctic and red foxes (Vulpes vulpes) are reservoirs for rabies, with most domestic animal and wildlife cases reported from northern and western coastal Alaska. Based on passive surveillance, a pronounced seasonal trend in rabid foxes occurs in Alaska, with a peak in winter and spring. This study describes climatic factors that may be associated with reported cyclic rabies occurrence. Based upon probabilistic modeling, a stronger seasonal effect in reported fox rabies cases appears at higher latitudes in Alaska, and rabies in arctic foxes appear disproportionately affected by climatic factors in comparison to red foxes. As temperatures continue a warming trend a decrease in reported rabid arctic foxes may be expected. The overall epidemiology of rabies in Alaska is likely to shift to increased viral transmission among red foxes as the primary reservoir in the region. Information on fox and lemming demographics, in addition to enhanced rabies surveillance among foxes at finer geographic scales, will be critical to develop more comprehensive models for rabies virus transmission in the region. PMID:23452510

Evaluating Options for Improving California's Drought Resilience

NASA Astrophysics Data System (ADS)

Ray, P. A.; Schwarz, A.; Wi, S.; Correa, M.; Brown, C.

2015-12-01

Through a unique collaborative arrangement, the University of Massachusetts (UMass) and the California Department of Water Resources (DWR) have together performed a baseline climate change analysis of the California state (State Water Project) and federal (Central Valley Project) water systems. The first step in the baseline analysis was development of an improved basinwide hydrologic model covering a large area of California including all major tributaries to the state and federal water systems. The CalLite modeling system used by DWR for planning purposes allowed simulation of the system of reservoirs, rivers, control points, and deliveries which are then used to create performance metrics that quantify a wide range of system characteristics including water deliveries, water quality, and environmental/ecological factors. A baseline climate stress test was conducted to identify current vulnerabilities to climate change through the linking of the modeling chain with Decision Scaling concepts through the UMass bottom-up climate stress-testing algorithm. This procedure allowed the first comprehensive climate stress analysis of the California state and federal water systems not constrained by observed historical variability and wet-dry year sequences. A forward-looking drought vulnerability and adaptation assessment of the water systems based on this workflow is ongoing and preliminary results will be presented. Presentation of results will include discussion of the collaborative arrangement between DWR and UMass, which is instrumental to both the success of the research and the education of policy makers.

A conceptual model for the impact of climate change on fox rabies in Alaska, 1980-2010.

PubMed

Kim, B I; Blanton, J D; Gilbert, A; Castrodale, L; Hueffer, K; Slate, D; Rupprecht, C E

2014-02-01

The direct and interactive effects of climate change on host species and infectious disease dynamics are likely to initially manifest\\ at latitudinal extremes. As such, Alaska represents a region in the United States for introspection on climate change and disease. Rabies is enzootic among arctic foxes (Vulpes lagopus) throughout the northern polar region. In Alaska, arctic and red foxes (Vulpes vulpes) are reservoirs for rabies, with most domestic animal and wildlife cases reported from northern and western coastal Alaska. Based on passive surveillance, a pronounced seasonal trend in rabid foxes occurs in Alaska, with a peak in winter and spring. This study describes climatic factors that may be associated with reported cyclic rabies occurrence. Based upon probabilistic modelling, a stronger seasonal effect in reported fox rabies cases appears at higher latitudes in Alaska, and rabies in arctic foxes appear disproportionately affected by climatic factors in comparison with red foxes. As temperatures continue a warming trend, a decrease in reported rabid arctic foxes may be expected. The overall epidemiology of rabies in Alaska is likely to shift to increased viral transmission among red foxes as the primary reservoir in the region. Information on fox and lemming demographics, in addition to enhanced rabies surveillance among foxes at finer geographic scales, will be critical to develop more comprehensive models for rabies virus transmission in the region. © 2013 Blackwell Verlag GmbH.

Two Case Studies to Quantify Resilience across Food-Energy-Water Systems: the Columbia River Treaty and Adaptation in Yakima River Basin Irrigation Systems

NASA Astrophysics Data System (ADS)

Malek, K.; Adam, J. C.; Richey, A.; Rushi, B. R.; Stockle, C.; Yoder, J.; Barik, M.; Lee, S. Y.; Rajagopalan, K.; Brady, M.; Barber, M. E.; Boll, J.; Padowski, J.

2017-12-01

The U.S. Pacific Northwest (PNW) plays a significant role in meeting agricultural and hydroelectric demands nationwide. Climatic and anthropogenic stressors, however, potentially threaten the productivity, resilience, and environmental health of the region. Our objective is to understand how resilience of each Food-Energy-Water (FEW) sector, and the combined Nexus, respond to exogenous perturbations and the extent to which technological and institutional advances can buffer these perturbations. In the process of taking information from complex integrated models and assessing resilience across FEW sectors, we start with two case studies: 1) Columbia River Treaty (CRT) with Canada that determines how multiple reservoirs in the Columbia River basin (CRB) are operated, and 2) climate change adaptation actions in the Yakima River basin (YRB). We discuss these case studies in terms of the similarities and contrasts related to FEW sectors and management complexities. Both the CRB and YBP systems are highly sensitive to climate change (they are both snowmelt-dominant) and already experience water conflict. The CRT is currently undergoing renegotiation; a new CRT will need to consider a much more comprehensive approach, e.g., treating environmental flows explicitly. The YRB also already experiences significant water conflict and thus the comprehensive Yakima Basin Integrated Plan (YBIP) is being pursued. We apply a new modeling framework that mechanistically captures the interactions between the FEW sectors to quantify the impacts of CRT and YBIP planning (as well as adaptation decisions taken by individuals, e.g., irrigators) on resilience in each sector. Proposed modification to the CRT may relieve impacts to multiple sectors. However, in the YRB, irrigators' actions to adapt to climate change (through investing in more efficient irrigation technology) could reduce downstream water availability for other users. Developing a process to quantify resilience to perturbations, such as climate change, will enable innovative solutions that co-balance benefits, and ultimately increase resilience, across all FEW sectors.

Future air pollution in the Shared Socio-economic Pathways

DOE PAGES

Rao, Shilpa; Klimont, Zbigniew; Smith, Steven J.; ...

2016-07-15

Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high,more » central, and low pollution control ambitions over the 21 st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. We provide an overview of pollutant emission trajectories under the SSP scenarios. Pollutant emissions in these scenarios cover a wider range than the scenarios used in previous international climate model comparisons. Furthermore, the SSP scenarios provide the opportunity to access a more comprehensive range of future global and regional air quality outcomes.« less

Future air pollution in the Shared Socio-economic Pathways

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

Rao, Shilpa; Klimont, Zbigniew; Smith, Steven J.

Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high,more » central, and low pollution control ambitions over the 21 st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. We provide an overview of pollutant emission trajectories under the SSP scenarios. Pollutant emissions in these scenarios cover a wider range than the scenarios used in previous international climate model comparisons. Furthermore, the SSP scenarios provide the opportunity to access a more comprehensive range of future global and regional air quality outcomes.« less

Climate Change Education for Mitigation and Adaptation

ERIC Educational Resources Information Center

Anderson, Allison

2012-01-01

This article makes the case for the education sector an untapped opportunity to combat climate change. It sets forth a definition of Climate Change Education for Sustainable Development that is comprehensive and multidisciplinary and asserts that it must not only include relevant content knowledge on climate change, environmental and social…

Assessing ocean vertical mixing schemes for the study of climate change

NASA Astrophysics Data System (ADS)

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

2014-12-01

Climate change is a burning issue of our time. It is critical to know the consequences of choosing "business as usual" vs. mitigating our emissions for impacts e.g. ecosystem disruption, sea-level rise, floods and droughts. To make predictions we must model realistically each component of the climate system. The ocean must be modeled carefully as it plays a critical role, including transporting heat and storing heat and dissolved carbon dioxide. Modeling the ocean realistically in turn requires physically based parameterizations of key processes in it that cannot be explicitly represented in a global climate model. One such process is vertical mixing. The turbulence group at NASA-GISS has developed a comprehensive new vertical mixing scheme (GISSVM) based on turbulence theory, including surface convection and wind shear, interior waves and double-diffusion, and bottom tides. The GISSVM is tested in stand-alone ocean simulations before being used in coupled climate models. It is also being upgraded to more faithfully represent the physical processes. To help assess mixing schemes, students use data from NASA-GISS to create visualizations and calculate statistics including mean bias and rms differences and correlations of fields. These are created and programmed with MATLAB. Results with the commonly used KPP mixing scheme and the present GISSVM and candidate improved variants of GISSVM will be compared between stand-alone ocean models and coupled models and observations. This project introduces students to modeling of a complex system, an important theme in contemporary science and helps them gain a better appreciation of climate science and a new perspective on it. They also gain familiarity with MATLAB, a widely used tool, and develop skills in writing and understanding programs. Moreover they contribute to the advancement of science by providing information that will help guide the improvement of the GISSVM and hence of ocean and climate models and ultimately our understanding and prediction of climate. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, a minority serving institution in an urban setting in central Brooklyn. This Project is supported by NSF award AGS-1359293 REU site: CUNY/GISS Center for Global Climate Research.

New climatic classification of Nepal

NASA Astrophysics Data System (ADS)

Karki, Ramchandra; Talchabhadel, Rocky; Aalto, Juha; Baidya, Saraju Kumar

2016-08-01

Although it is evident that Nepal has an extremely wide range of climates within a short latitudinal distance, there is a lack of comprehensive research in this field. The climatic zoning in a topographically complex country like Nepal has important implications for the selection of scientific station network design and climate model verification, as well as for studies examining the effects of climate change in terms of shifting climatic boundaries and vegetation in highly sensitive environments. This study presents a new high-resolution climate map of Nepal on the basis of long-term (1981-2010) monthly precipitation data for 240 stations and mean air temperature data for 74 stations, using original and modified Köppen-Geiger climate classification systems. Climatic variables used in Köppen-Geiger system were calculated (i) at each station and (ii) interpolated to 1-km spatial resolution using kriging which accounted for latitude, longitude, and elevation. The original Köppen-Geiger scheme could not identify all five types of climate (including tropical) observed in Nepal. Hence, the original scheme was slightly modified by changing the boundary of coldest month mean air temperature value from 18 °C to 14.5 °C in order to delineate the realistic climatic condition of Nepal. With this modification, all five types of climate (including tropical) were identified. The most common dominant type of climate for Nepal is temperate with dry winter and hot summer (Cwa).

Climate Leadership Award for Organizational Leadership

EPA Pesticide Factsheets

Apply to the Climate Leadership Award for Organizational Leadership, which publicly recognizes organizations for their comprehensive greenhouse gas inventories and aggressive emissions reduction goals.

U.S. Climate Change Science Program. Vision for the Program and Highlights of the Scientific Strategic Plan

NASA Technical Reports Server (NTRS)

2003-01-01

The vision document provides an overview of the Climate Change Science Program (CCSP) long-term strategic plan to enhance scientific understanding of global climate change.This document is a companion to the comprehensive Strategic Plan for the Climate Change Science Program. The report responds to the Presidents direction that climate change research activities be accelerated to provide the best possible scientific information to support public discussion and decisionmaking on climate-related issues.The plan also responds to Section 104 of the Global Change Research Act of 1990, which mandates the development and periodic updating of a long-term national global change research plan coordinated through the National Science and Technology Council.This is the first comprehensive update of a strategic plan for U.S. global change and climate change research since the origal plan for the U.S. Global Change Research Program was adopted at the inception of the program in 1989.

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).

Multi-model inference for incorporating trophic and climate uncertainty into stock assessments

NASA Astrophysics Data System (ADS)

Ianelli, James; Holsman, Kirstin K.; Punt, André E.; Aydin, Kerim

2016-12-01

Ecosystem-based fisheries management (EBFM) approaches allow a broader and more extensive consideration of objectives than is typically possible with conventional single-species approaches. Ecosystem linkages may include trophic interactions and climate change effects on productivity for the relevant species within the system. Presently, models are evolving to include a comprehensive set of fishery and ecosystem information to address these broader management considerations. The increased scope of EBFM approaches is accompanied with a greater number of plausible models to describe the systems. This can lead to harvest recommendations and biological reference points that differ considerably among models. Model selection for projections (and specific catch recommendations) often occurs through a process that tends to adopt familiar, often simpler, models without considering those that incorporate more complex ecosystem information. Multi-model inference provides a framework that resolves this dilemma by providing a means of including information from alternative, often divergent models to inform biological reference points and possible catch consequences. We apply an example of this approach to data for three species of groundfish in the Bering Sea: walleye pollock, Pacific cod, and arrowtooth flounder using three models: 1) an age-structured "conventional" single-species model, 2) an age-structured single-species model with temperature-specific weight at age, and 3) a temperature-specific multi-species stock assessment model. The latter two approaches also include consideration of alternative future climate scenarios, adding another dimension to evaluate model projection uncertainty. We show how Bayesian model-averaging methods can be used to incorporate such trophic and climate information to broaden single-species stock assessments by using an EBFM approach that may better characterize uncertainty.

Global mortality consequences of climate change accounting for adaptation costs and benefits

NASA Astrophysics Data System (ADS)

Rising, J. A.; Jina, A.; Carleton, T.; Hsiang, S. M.; Greenstone, M.

2017-12-01

Empirically-based and plausibly causal estimates of the damages of climate change are greatly needed to inform rapidly developing global and local climate policies. To accurately reflect the costs of climate change, it is essential to estimate how much populations will adapt to a changing climate, yet adaptation remains one of the least understood aspects of social responses to climate. In this paper, we develop and implement a novel methodology to estimate climate impacts on mortality rates. We assemble comprehensive sub-national panel data in 41 countries that account for 56% of the world's population, and combine them with high resolution daily climate data to flexibly estimate the causal effect of temperature on mortality. We find the impacts of temperature on mortality have a U-shaped response; both hot days and cold days cause excess mortality. However, this average response obscures substantial heterogeneity, as populations are differentially adapted to extreme temperatures. Our empirical model allows us to extrapolate response functions across the entire globe, as well as across time, using a range of economic, population, and climate change scenarios. We also develop a methodology to capture not only the benefits of adaptation, but also its costs. We combine these innovations to produce the first causal, micro-founded, global, empirically-derived climate damage function for human health. We project that by 2100, business-as-usual climate change is likely to incur mortality-only costs that amount to approximately 5% of global GDP for 5°C degrees of warming above pre-industrial levels. On average across model runs, we estimate that the upper bound on adaptation costs amounts to 55% of the total damages.

The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. II - Dynamical analysis

NASA Technical Reports Server (NTRS)

Phillips, T. J.

1984-01-01

The heating associated with equatorial, subtropical, and midlatitude ocean temperature anamolies in the Held-Suarez climate model is analyzed. The local and downstream response to the anomalies is analyzed, first by examining the seasonal variation in heating associated with each ocean temperature anomaly, and then by combining knowledge of the heating with linear dynamical theory in order to develop a more comprehensive explanation of the seasonal variation in local and downstream atmospheric response to each anomaly. The extent to which the linear theory of propagating waves can assist the interpretation of the remote cross-latitudinal response of the model to the ocean temperature anomalies is considered. Alternative hypotheses that attempt to avoid the contradictions inherent in a strict application of linear theory are investigated, and the impact of sampling errors on the assessment of statistical significance is also examined.

Whole Atmosphere Simulation of Anthropogenic Climate Change

NASA Astrophysics Data System (ADS)

Solomon, Stanley C.; Liu, Han-Li; Marsh, Daniel R.; McInerney, Joseph M.; Qian, Liying; Vitt, Francis M.

2018-02-01

We simulated anthropogenic global change through the entire atmosphere, including the thermosphere and ionosphere, using the Whole Atmosphere Community Climate Model-eXtended. The basic result was that even as the lower atmosphere gradually warms, the upper atmosphere rapidly cools. The simulations employed constant low solar activity conditions, to remove the effects of variable solar and geomagnetic activity. Global mean annual mean temperature increased at a rate of +0.2 K/decade at the surface and +0.4 K/decade in the upper troposphere but decreased by about -1 K/decade in the stratosphere-mesosphere and -2.8 K/decade in the thermosphere. Near the mesopause, temperature decreases were small compared to the interannual variation, so trends in that region are uncertain. Results were similar to previous modeling confined to specific atmospheric levels and compared favorably with available measurements. These simulations demonstrate the ability of a single comprehensive numerical model to characterize global change throughout the atmosphere.

Divergent surface and total soil moisture projections under global warming

USGS Publications Warehouse

Berg, Alexis; Sheffield, Justin; Milly, Paul C.D.

2017-01-01

Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.

Harmonisation of Global Land-Use Scenarios for the Period 1500-2100 for IPCC-AR5

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

Hurtt, George; Chini, Louise Parsons; Frolking, Steve

2009-06-01

In preparation for the fifth Intergovernmental Panel on Climate Change climate change assessment (IPCC-AR5), the international community is developing new advanced computer models (CMs) to address the combined effects of human activities (e.g. land-use and fossil fuel emissions) on the carbon-climate system. In addition, four Representative Concentration Pathway (RCP) scenarios of the future (2005-2100) are being developed by four Integrated Assessment Modeling teams (IAMs) to be used as input to the CMs for future climate projections. The diversity of requirements and approaches among CMs and IAMs for tracking land-use changes (past, present, and future), presents major challenges for treating land-usemore » comprehensively and consistently between these communities. As part of an international working group, we have been working to meet these challenges by developing a "harmonized" set of land-use change scenarios that smoothly connects gridded historical reconstructions of land-use with future projections, in a format required by CMs. This approach to harmonizing the treatment of land-use between two key modeling communities, CMs and IAMs, represents a major advance that will facilitate more consistent and fuller treatments of land-use/land-use change effects including both CO2 emissions and corresponding land-surface changes.« less

The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

NASA Astrophysics Data System (ADS)

Valdes, Paul J.; Armstrong, Edward; Badger, Marcus P. S.; Bradshaw, Catherine D.; Bragg, Fran; Crucifix, Michel; Davies-Barnard, Taraka; Day, Jonathan J.; Farnsworth, Alex; Gordon, Chris; Hopcroft, Peter O.; Kennedy, Alan T.; Lord, Natalie S.; Lunt, Dan J.; Marzocchi, Alice; Parry, Louise M.; Pope, Vicky; Roberts, William H. G.; Stone, Emma J.; Tourte, Gregory J. L.; Williams, Jonny H. T.

2017-10-01

Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea ice, and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the HadCM3 coupled general circulation model. This model was developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies, but has now been largely superseded for many scientific studies by more recently developed models. However, it continues to be extensively used by various institutions, including the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol, who have made modest adaptations to the base HadCM3 model over time. These adaptations mean that the original documentation is not entirely representative, and several other relatively undocumented configurations are in use. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, which together make up HadCM3@Bristol version 1.0. In order to differentiate variants that have undergone development at BRIDGE, we have introduced the letter B into the model nomenclature. We include descriptions of the atmosphere-only model (HadAM3B), the coupled model with a low-resolution ocean (HadCM3BL), the high-resolution atmosphere-only model (HadAM3BH), and the regional model (HadRM3B). These also include three versions of the land surface scheme. By comparing with observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation, and vegetation. This evaluation, combined with the relatively fast computational speed (up to 1000 times faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3B family of coupled climate models, predominantly for quantifying uncertainty and for long multi-millennial-scale simulations.

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.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

NASA Astrophysics Data System (ADS)

González, D. L., II; Angus, M. P.; Tetteh, I. K.; Bello, G. A.; Padmanabhan, K.; Pendse, S. V.; Srinivas, S.; Yu, J.; Semazzi, F.; Kumar, V.; Samatova, N. F.

2015-01-01

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. These relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño-Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.

On the data-driven inference of modulatory networks in climate science: An application to West African rainfall

DOE PAGES

Gonzalez, II, D. L.; Angus, M. P.; Tetteh, I. K.; ...

2015-01-13

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression,more » and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. As a result, these relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño–Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.« less

Large-scale determinants of intestinal schistosomiasis and intermediate host snail distribution across Africa: does climate matter?

PubMed

Stensgaard, Anna-Sofie; Utzinger, Jürg; Vounatsou, Penelope; Hürlimann, Eveline; Schur, Nadine; Saarnak, Christopher F L; Simoonga, Christopher; Mubita, Patricia; Kabatereine, Narcis B; Tchuem Tchuenté, Louis-Albert; Rahbek, Carsten; Kristensen, Thomas K

2013-11-01

The geographical ranges of most species, including many infectious disease agents and their vectors and intermediate hosts, are assumed to be constrained by climatic tolerances, mainly temperature. It has been suggested that global warming will cause an expansion of the areas potentially suitable for infectious disease transmission. However, the transmission of infectious diseases is governed by a myriad of ecological, economic, evolutionary and social factors. Hence, a deeper understanding of the total disease system (pathogens, vectors and hosts) and its drivers is important for predicting responses to climate change. Here, we combine a growing degree day model for Schistosoma mansoni with species distribution models for the intermediate host snail (Biomphalaria spp.) to investigate large-scale environmental determinants of the distribution of the African S. mansoni-Biomphalaria system and potential impacts of climatic changes. Snail species distribution models included several combinations of climatic and habitat-related predictors; the latter divided into "natural" and "human-impacted" habitat variables to measure anthropogenic influence. The predictive performance of the combined snail-parasite model was evaluated against a comprehensive compilation of historical S. mansoni parasitological survey records, and then examined for two climate change scenarios of increasing severity for 2080. Future projections indicate that while the potential S. mansoni transmission area expands, the snail ranges are more likely to contract and/or move into cooler areas in the south and east. Importantly, we also note that even though climate per se matters, the impact of humans on habitat play a crucial role in determining the distribution of the intermediate host snails in Africa. Thus, a future contraction in the geographical range size of the intermediate host snails caused by climatic changes does not necessarily translate into a decrease or zero-sum change in human schistosomiasis prevalence. Copyright © 2011 Elsevier B.V. All rights reserved.

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

Boer, George J.; Smith, Douglas M.; Cassou, Christophe

The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Predictionmore » (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Furthermore, groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.« less

Challenges and priorities for modelling livestock health and pathogens in the context of climate change.

PubMed

Özkan, Şeyda; Vitali, Andrea; Lacetera, Nicola; Amon, Barbara; Bannink, André; Bartley, Dave J; Blanco-Penedo, Isabel; de Haas, Yvette; Dufrasne, Isabelle; Elliott, John; Eory, Vera; Fox, Naomi J; Garnsworthy, Phil C; Gengler, Nicolas; Hammami, Hedi; Kyriazakis, Ilias; Leclère, David; Lessire, Françoise; Macleod, Michael; Robinson, Timothy P; Ruete, Alejandro; Sandars, Daniel L; Shrestha, Shailesh; Stott, Alistair W; Twardy, Stanislaw; Vanrobays, Marie-Laure; Ahmadi, Bouda Vosough; Weindl, Isabelle; Wheelhouse, Nick; Williams, Adrian G; Williams, Hefin W; Wilson, Anthony J; Østergaard, Søren; Kipling, Richard P

2016-11-01

Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire based exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change. Copyright © 2016 Elsevier Inc. All rights reserved.

Climate change: Cropping system changes and adaptations

USDA-ARS?s Scientific Manuscript database

Climate change impacts the life of every person; however, there is little comprehensive understanding of the direct and indirect effects of climate change on agriculture. Since our food, feed, fiber, and fruit is derived from agricultural systems, understanding the effects of changing temperature, p...

Current state of aerosol nucleation parameterizations for air-quality and climate modeling

NASA Astrophysics Data System (ADS)

Semeniuk, Kirill; Dastoor, Ashu

2018-04-01

Aerosol nucleation parameterization models commonly used in 3-D air quality and climate models have serious limitations. This includes classical nucleation theory based variants, empirical models and other formulations. Recent work based on detailed and extensive laboratory measurements and improved quantum chemistry computation has substantially advanced the state of nucleation parameterizations. In terms of inorganic nucleation involving BHN and THN including ion effects these new models should be considered as worthwhile replacements for the old models. However, the contribution of organic species to nucleation remains poorly quantified. New particle formation consists of a distinct post-nucleation growth regime which is characterized by a strong Kelvin curvature effect and is thus dependent on availability of very low volatility organic species or sulfuric acid. There have been advances in the understanding of the multiphase chemistry of biogenic and anthropogenic organic compounds which facilitate to overcome the initial aerosol growth barrier. Implementation of processes influencing new particle formation is challenging in 3-D models and there is a lack of comprehensive parameterizations. This review considers the existing models and recent innovations.

Climate and environmental change drives Ixodes ricinus geographical expansion at the northern range margin.

PubMed

Jore, Solveig; Vanwambeke, Sophie O; Viljugrein, Hildegunn; Isaksen, Ketil; Kristoffersen, Anja B; Woldehiwet, Zerai; Johansen, Bernt; Brun, Edgar; Brun-Hansen, Hege; Westermann, Sebastian; Larsen, Inger-Lise; Ytrehus, Bjørnar; Hofshagen, Merete

2014-01-08

Global environmental change is causing spatial and temporal shifts in the distribution of species and the associated diseases of humans, domesticated animals and wildlife. In the on-going debate on the influence of climate change on vectors and vector-borne diseases, there is a lack of a comprehensive interdisciplinary multi-factorial approach utilizing high quality spatial and temporal data. We explored biotic and abiotic factors associated with the latitudinal and altitudinal shifts in the distribution of Ixodes ricinus observed during the last three decades in Norway using antibodies against Anaplasma phagocytophilum in sheep as indicators for tick presence. Samples obtained from 2963 sheep from 90 farms in 3 ecologically different districts during 1978 - 2008 were analysed. We modelled the presence of antibodies against A. phagocytophilum to climatic-, environmental and demographic variables, and abundance of wild cervids and domestic animals, using mixed effect logistic regressions. Significant predictors were large diurnal fluctuations in ground surface temperature, spring precipitation, duration of snow cover, abundance of red deer and farm animals and bush encroachment/ecotones. The length of the growth season, mean temperature and the abundance of roe deer were not significant in the model. Our results highlight the need to consider climatic variables year-round to disentangle important seasonal variation, climatic threshold changes, climate variability and to consider the broader environmental change, including abiotic and biotic factors. The results offer novel insight in how tick and tick-borne disease distribution might be modified by future climate and environmental change.

A comprehensive assessment of different evapotranspiration products using the site-level FLUXNET database

NASA Astrophysics Data System (ADS)

Liu, J.

2017-12-01

Accurately estimate of ET is crucial for studies of land-atmosphere interactions. A series of ET products have been developed recently relying on various simulation methods, however, uncertainties in accuracy of products limit their implications. In this study, accuracies of total 8 popular global ET products simulated based on satellite retrieves (ETMODIS and ETZhang), reanalysis (ETJRA55), machine learning method (ETJung) and land surface models (ETCLM, ETMOS, ETNoah and ETVIC) forcing by Global Land Data Assimilation System (GLDAS), respectively, were comprehensively evaluated against observations from eddy covariance FLUXNET sites by yearly, land cover and climate zones. The result shows that all simulated ET products tend to underestimate in the lower ET ranges or overestimate in higher ET ranges compared with ET observations. Through the examining of four statistic criterias, the root mean square error (RMSE), mean bias error (MBE), R2, and Taylor skill score (TSS), ETJung provided a high performance whether yearly or land cover or climatic zones. Satellite based ET products also have impressive performance. ETMODIS and ETZhang present comparable accuracy, while were skilled for different land cover and climate zones, respectively. Generally, the ET products from GLDAS show reasonable accuracy, despite ETCLM has relative higher RMSE and MBE for yearly, land cover and climate zones comparisons. Although the ETJRA55 shows comparable R2 with other products, its performance was constraint by the high RMSE and MBE. Knowledge from this study is crucial for ET products improvement and selection when they were used.

Modelling land cover change in the Ganga basin

NASA Astrophysics Data System (ADS)

Moulds, S.; Tsarouchi, G.; Mijic, A.; Buytaert, W.

2013-12-01

Over recent decades the green revolution in India has driven substantial environmental change. Modelling experiments have identified northern India as a 'hot spot' of land-atmosphere coupling strength during the boreal summer. However, there is a wide range of sensitivity of atmospheric variables to soil moisture between individual climate models. The lack of a comprehensive land cover change dataset to force climate models has been identified as a major contributor to model uncertainty. In this work a time series dataset of land cover change between 1970 and 2010 is constructed for northern India to improve the quantification of regional hydrometeorological feedbacks. The MODIS instrument on board the Aqua and Terra satellites provides near-continuous remotely sensed datasets from 2000 to the present day. However, the quality of satellite products before 2000 is poor. To complete the dataset MODIS images are extrapolated back in time using the Conversion of Land Use and its Effects at small regional extent (CLUE-s) modelling framework. Non-spatial estimates of land cover area from national agriculture and forest statistics, available on a state-wise, annual basis, are used as a direct model input. Land cover change is allocated spatially as a function of biophysical and socioeconomic drivers identified using logistic regression. This dataset will provide an essential input to a high resolution, physically based land surface model to generate the lower boundary condition to assess the impact of land cover change on regional climate.

Challenges and priorities for modelling livestock health and pathogens in the context of climate change

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

Özkan, Şeyda

Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire basedmore » exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change. - Highlights: • Experts identified challenges for health and pathogen modelling under climate change. • Eighteen key challenges and associated research priorities were identified. • Increasing capacity will require improved organisation and sharing knowledge. • Better communication across the diverse topics and approaches in this field is needed.« less

Holocene shifts of the southern westerlies across the South Atlantic

NASA Astrophysics Data System (ADS)

Voigt, Ines; Chiessi, Cristiano M.; Prange, Matthias; Mulitza, Stefan; Groeneveld, Jeroen; Varma, Vidya; Henrich, Ruediger

2015-02-01

The southern westerly winds (SWW) exert a crucial influence over the world ocean and climate. Nevertheless, a comprehensive understanding of the Holocene temporal and spatial evolution of the SWW remains a significant challenge due to the sparsity of high-resolution marine archives and appropriate SWW proxies. Here we present a north-south transect of high-resolution planktonic foraminiferal oxygen isotope records from the western South Atlantic. Our proxy records reveal Holocene migrations of the Brazil-Malvinas Confluence (BMC), a highly sensitive feature for changes in the position and strength of the northern portion of the SWW. Through the tight coupling of the BMC position to the large-scale wind field, the records allow a quantitative reconstruction of Holocene latitudinal displacements of the SWW across the South Atlantic. Our data reveal a gradual poleward movement of the SWW by about 1-1.5° from the early to the mid-Holocene. Afterward, variability in the SWW is dominated by millennial scale displacements on the order of 1° in latitude with no recognizable longer-term trend. These findings are confronted with results from a state-of-the-art transient Holocene climate simulation using a comprehensive coupled atmosphere-ocean general circulation model. Proxy-inferred and modeled SWW shifts compare qualitatively, but the model underestimates both orbitally forced multimillennial and internal millennial SWW variability by almost an order of magnitude. The underestimated natural variability implies a substantial uncertainty in model projections of future SWW shifts.

Large-scale range collapse of Hawaiian forest birds under climate change and the need 21st century conservation options

USGS Publications Warehouse

Fortini, Lucas B.; Vorsino, Adam E.; Amidon, Fred A.; Paxton, Eben H.; Jacobi, James D.

2015-01-01

Hawaiian forest birds serve as an ideal group to explore the extent of climate change impacts on at-risk species. Avian malaria constrains many remaining Hawaiian forest bird species to high elevations where temperatures are too cool for malaria's life cycle and its principal mosquito vector. The impact of climate change on Hawaiian forest birds has been a recent focus of Hawaiian conservation biology, and has centered on the links between climate and avian malaria. To elucidate the differential impacts of projected climate shifts on species with known varying niches, disease resistance and tolerance, we use a comprehensive database of species sightings, regional climate projections and ensemble distribution models to project distribution shifts for all Hawaiian forest bird species. We illustrate that, under a likely scenario of continued disease-driven distribution limitation, all 10 species with highly reliable models (mostly narrow-ranged, single-island endemics) are expected to lose >50% of their range by 2100. Of those, three are expected to lose all range and three others are expected to lose >90% of their range. Projected range loss was smaller for several of the more widespread species; however improved data and models are necessary to refine future projections. Like other at-risk species, Hawaiian forest birds have specific habitat requirements that limit the possibility of range expansion for most species, as projected expansion is frequently in areas where forest habitat is presently not available (such as recent lava flows). Given the large projected range losses for all species, protecting high elevation forest alone is not an adequate long-term strategy for many species under climate change. We describe the types of additional conservation actions practitioners will likely need to consider, while providing results to help with such considerations.

Large-Scale Range Collapse of Hawaiian Forest Birds under Climate Change and the Need for 21st Century Conservation Options [corrected].

PubMed

Fortini, Lucas B; Vorsino, Adam E; Amidon, Fred A; Paxton, Eben H; Jacobi, James D

2015-01-01

Hawaiian forest birds serve as an ideal group to explore the extent of climate change impacts on at-risk species. Avian malaria constrains many remaining Hawaiian forest bird species to high elevations where temperatures are too cool for malaria's life cycle and its principal mosquito vector. The impact of climate change on Hawaiian forest birds has been a recent focus of Hawaiian conservation biology, and has centered on the links between climate and avian malaria. To elucidate the differential impacts of projected climate shifts on species with known varying niches, disease resistance and tolerance, we use a comprehensive database of species sightings, regional climate projections and ensemble distribution models to project distribution shifts for all Hawaiian forest bird species. We illustrate that, under a likely scenario of continued disease-driven distribution limitation, all 10 species with highly reliable models (mostly narrow-ranged, single-island endemics) are expected to lose >50% of their range by 2100. Of those, three are expected to lose all range and three others are expected to lose >90% of their range. Projected range loss was smaller for several of the more widespread species; however improved data and models are necessary to refine future projections. Like other at-risk species, Hawaiian forest birds have specific habitat requirements that limit the possibility of range expansion for most species, as projected expansion is frequently in areas where forest habitat is presently not available (such as recent lava flows). Given the large projected range losses for all species, protecting high elevation forest alone is not an adequate long-term strategy for many species under climate change. We describe the types of additional conservation actions practitioners will likely need to consider, while providing results to help with such considerations.

Large-Scale Range Collapse of Hawaiian Forest Birds under Climate Change and the Need 21st Century Conservation Options

PubMed Central

Fortini, Lucas B.; Vorsino, Adam E.; Amidon, Fred A.; Paxton, Eben H.; Jacobi, James D.

2015-01-01

Hawaiian forest birds serve as an ideal group to explore the extent of climate change impacts on at-risk species. Avian malaria constrains many remaining Hawaiian forest bird species to high elevations where temperatures are too cool for malaria’s life cycle and its principal mosquito vector. The impact of climate change on Hawaiian forest birds has been a recent focus of Hawaiian conservation biology, and has centered on the links between climate and avian malaria. To elucidate the differential impacts of projected climate shifts on species with known varying niches, disease resistance and tolerance, we use a comprehensive database of species sightings, regional climate projections and ensemble distribution models to project distribution shifts for all Hawaiian forest bird species. We illustrate that, under a likely scenario of continued disease-driven distribution limitation, all 10 species with highly reliable models (mostly narrow-ranged, single-island endemics) are expected to lose >50% of their range by 2100. Of those, three are expected to lose all range and three others are expected to lose >90% of their range. Projected range loss was smaller for several of the more widespread species; however improved data and models are necessary to refine future projections. Like other at-risk species, Hawaiian forest birds have specific habitat requirements that limit the possibility of range expansion for most species, as projected expansion is frequently in areas where forest habitat is presently not available (such as recent lava flows). Given the large projected range losses for all species, protecting high elevation forest alone is not an adequate long-term strategy for many species under climate change. We describe the types of additional conservation actions practitioners will likely need to consider, while providing results to help with such considerations. PMID:26509270

Commensurate comparisons of models with energy budget observations reveal consistent climate sensitivities

NASA Astrophysics Data System (ADS)

Armour, K.

2017-12-01

Global energy budget observations have been widely used to constrain the effective, or instantaneous climate sensitivity (ICS), producing median estimates around 2°C (Otto et al. 2013; Lewis & Curry 2015). A key question is whether the comprehensive climate models used to project future warming are consistent with these energy budget estimates of ICS. Yet, performing such comparisons has proven challenging. Within models, values of ICS robustly vary over time, as surface temperature patterns evolve with transient warming, and are generally smaller than the values of equilibrium climate sensitivity (ECS). Naively comparing values of ECS in CMIP5 models (median of about 3.4°C) to observation-based values of ICS has led to the suggestion that models are overly sensitive. This apparent discrepancy can partially be resolved by (i) comparing observation-based values of ICS to model values of ICS relevant for historical warming (Armour 2017; Proistosescu & Huybers 2017); (ii) taking into account the "efficacies" of non-CO2 radiative forcing agents (Marvel et al. 2015); and (iii) accounting for the sparseness of historical temperature observations and differences in sea-surface temperature and near-surface air temperature over the oceans (Richardson et al. 2016). Another potential source of discrepancy is a mismatch between observed and simulated surface temperature patterns over recent decades, due to either natural variability or model deficiencies in simulating historical warming patterns. The nature of the mismatch is such that simulated patterns can lead to more positive radiative feedbacks (higher ICS) relative to those engendered by observed patterns. The magnitude of this effect has not yet been addressed. Here we outline an approach to perform fully commensurate comparisons of climate models with global energy budget observations that take all of the above effects into account. We find that when apples-to-apples comparisons are made, values of ICS in models are consistently in good agreement with values of ICS inferred from global energy budget constraints. This suggests that the current generation of coupled climate models are not overly sensitive. However, since global energy budget observations do not constrain ECS, it is less certain whether model ECS values are realistic.

Recent advances in understanding secondary organic aerosol: Implications for global climate forcing

NASA Astrophysics Data System (ADS)

Shrivastava, Manish; Cappa, Christopher D.; Fan, Jiwen; Goldstein, Allen H.; Guenther, Alex B.; Jimenez, Jose L.; Kuang, Chongai; Laskin, Alexander; Martin, Scot T.; Ng, Nga Lee; Petaja, Tuukka; Pierce, Jeffrey R.; Rasch, Philip J.; Roldin, Pontus; Seinfeld, John H.; Shilling, John; Smith, James N.; Thornton, Joel A.; Volkamer, Rainer; Wang, Jian; Worsnop, Douglas R.; Zaveri, Rahul A.; Zelenyuk, Alla; Zhang, Qi

2017-06-01

Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This review summarizes some of the important developments during the past decade in understanding SOA formation. We highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid-catalyzed multiphase chemistry of isoprene epoxydiols, particle-phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process-related interactions, so that these processes can be accurately represented in atmospheric chemistry-climate models.

An Enhanced Engineering Perspective of Global Climate Systems and Statistical Formulation of Terrestrial CO2 Exchanges

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

Dai, Yuanshun; Baek, Seung H.; Garcia-Diza, Alberto

2012-01-01

This paper designs a comprehensive approach based on the engineering machine/system concept, to model, analyze, and assess the level of CO2 exchange between the atmosphere and terrestrial ecosystems, which is an important factor in understanding changes in global climate. The focus of this article is on spatial patterns and on the correlation between levels of CO2 fluxes and a variety of influencing factors in eco-environments. The engineering/machine concept used is a system protocol that includes the sequential activities of design, test, observe, and model. This concept is applied to explicitly include various influencing factors and interactions associated with CO2 fluxes.more » To formulate effective models of a large and complex climate system, this article introduces a modeling technique that will be referred to as Stochastic Filtering Analysis of Variance (SFANOVA). The CO2 flux data observed from some sites of AmeriFlux are used to illustrate and validate the analysis, prediction and globalization capabilities of the proposed engineering approach and the SF-ANOVA technology. The SF-ANOVA modeling approach was compared to stepwise regression, ridge regression, and neural networks. The comparison indicated that the proposed approach is a valid and effective tool with similar accuracy and less complexity than the other procedures.« less

Modeling biogeochemical responses of vegetation to ENSO: comparison and analysis on subgrid PFT patches

NASA Astrophysics Data System (ADS)

Xu, M.; Hoffman, F. M.

2016-12-01

The El Niño Southern Oscillation (ENSO) is an important interannual climate variability and has significant consequences and impacts on the global biosphere. The responses of vegetation to ENSO are highly heterogeneous and generally depend on the biophysical and biochemical characteristics associated with model plant functional types (PFTs). The modeled biogeochemical variables from Earth System Models (ESMs) are generally grid averages consisting of several PFTs within a gridcell, which will lead to difficulties in directly comparing them with site observations and large uncertainties in studying their responses to large scale climate variability. In this study, we conducted a transient ENSO simulation for the previoustwo decades from 1995 to 2020 using the DOE ACME v0.3 model. It has a comprehensive terrestrial biogeochemistry model that is fully coupled with a sophisticated atmospheric model with an advanced spectral element dynamical core. The model was driven by the NOAA optimum interpolation sea surface temperature (SST) for contemporary years and CFS v2 nine-month seasonal predicted and reconstructed SST for future years till to 2020. We saved the key biogeochemical variables in the subgrid PFT patches and compared them with site observations directly. Furthermore, we studied the biogeochemical responses of terrestrial vegetation to two largest ENSO events (1997-1998 and 2015-2016) for different PFTs. Our results show that it is useful and meaningful to compare and analyze model simulations in subgrid patches. The comparison and analysis not only gave us the details of responses of terrestrial ecosystem to global climate variability under changing climate, but also the insightful view on the model performance on the PFT level.

Differential Impacts of Climate Change on Crops and Agricultural Regions in India

NASA Astrophysics Data System (ADS)

Sharma, A. N.

2015-12-01

As India's farmers and policymakers consider potential adaptation strategies to climate change, some questions loom large: - Which climate variables best explain the variability of crop yields? - How does the vulnerability of crop yields to climate vary regionally? - How are these risks likely to change in the future? While process-based crop modelling has started to answer many of these questions, we believe statistical approaches can complement these in improving our understanding of climate vulnerabilities and appropriate responses. We use yield data collected over three decades for more than ten food crops grown in India along with a variety of statistical approaches to answer the above questions. The ability of climate variables to explain yield variation varies greatly by crop and season, which is expected. Equally important, the ability of models to predict crop yields as well as their coefficients varies greatly by district even for districts which are relatively close to each other and similar in their agricultural practices. We believe these results encourage caution and nuance when making projections about climate impacts on crop yields in the future. Most studies about climate impacts on crop yields focus on a handful of major food crops. By extending our analysis to all the crops with long-term district level data in India as well as two growing seasons we gain a more comprehensive picture. Our results indicate that there is a great deal of variability even at relatively small scales, and that this must be taken into account if projections are to be made useful to policymakers.

Century long observation constrained global dynamic downscaling and hydrologic implication

NASA Astrophysics Data System (ADS)

Kim, H.; Yoshimura, K.; Chang, E.; Famiglietti, J. S.; Oki, T.

2012-12-01

It has been suggested that greenhouse gas induced warming climate causes the acceleration of large scale hydrologic cycles, and, indeed, many regions on the Earth have been suffered by hydrologic extremes getting more frequent. However, historical observations are not able to provide enough information in comprehensive manner to understand their long-term variability and/or global distributions. In this study, a century long high resolution global climate data is developed in order to break through existing limitations. 20th Century Reanalysis (20CR) which has relatively low spatial resolution (~2.0°) and longer term availability (140 years) is dynamically downscaled into global T248 (~0.5°) resolution using Experimental Climate Prediction Center (ECPC) Global Spectral Model (GSM) by spectral nudging data assimilation technique. Also, Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU) observational data are adopted to reduce model dependent uncertainty. Downscaled product successfully represents realistic geographical detail keeping low frequency signal in mean state and spatiotemporal variability, while previous bias correction method fails to reproduce high frequency variability. Newly developed data is used to investigate how long-term large scale terrestrial hydrologic cycles have been changed globally and how they have been interacted with various climate modes, such as El-Niño Southern Oscillation (ENSO) and Atlantic Multidecadal Oscillation (AMO). As a further application, it will be used to provide atmospheric boundary condition of multiple land surface models in the Global Soil Wetness Project Phase 3 (GSWP3).

The climate response to five trillion tonnes of carbon

NASA Astrophysics Data System (ADS)

Tokarska, Katarzyna B.; Gillett, Nathan P.; Weaver, Andrew J.; Arora, Vivek K.; Eby, Michael

2016-09-01

Concrete actions to curtail greenhouse gas emissions have so far been limited on a global scale, and therefore the ultimate magnitude of climate change in the absence of further mitigation is an important consideration for climate policy. Estimates of fossil fuel reserves and resources are highly uncertain, and the amount used under a business-as-usual scenario would depend on prevailing economic and technological conditions. In the absence of global mitigation actions, five trillion tonnes of carbon (5 EgC), corresponding to the lower end of the range of estimates of the total fossil fuel resource, is often cited as an estimate of total cumulative emissions. An approximately linear relationship between global warming and cumulative CO2 emissions is known to hold up to 2 EgC emissions on decadal to centennial timescales; however, in some simple climate models the predicted warming at higher cumulative emissions is less than that predicted by such a linear relationship. Here, using simulations from four comprehensive Earth system models, we demonstrate that CO2-attributable warming continues to increase approximately linearly up to 5 EgC emissions. These models simulate, in response to 5 EgC of CO2 emissions, global mean warming of 6.4-9.5 °C, mean Arctic warming of 14.7-19.5 °C, and mean regional precipitation increases by more than a factor of four. These results indicate that the unregulated exploitation of the fossil fuel resource could ultimately result in considerably more profound climate changes than previously suggested.

Relationships Among Student, Staff, and Administrative Measures of School Climate and Student Health and Academic Outcomes.

PubMed

Gase, Lauren N; Gomez, Louis M; Kuo, Tony; Glenn, Beth A; Inkelas, Moira; Ponce, Ninez A

2017-05-01

School climate is an integral part of a comprehensive approach to improving the well-being of students; however, little is known about the relationships between its different domains and measures. We examined the relationships between student, staff, and administrative measures of school climate to understand the extent to which they were related to each other and student outcomes. The sample included 33,572 secondary school students from 121 schools in Los Angeles County during the 2014-2015 academic year. A multilevel regression model was constructed to examine the association between the domains and measures of school climate and 5 outcomes of student well-being: depressive symptoms or suicidal ideation, tobacco use, alcohol use, marijuana use, and grades. Student, staff, and administrative measures of school climate were weakly correlated. Strong associations were found between student outcomes and student reports of engagement and safety, while school staff reports and administrative measures of school climate showed limited associations with student outcomes. As schools seek to measure and implement interventions aimed at improving school climate, consideration should be given to grounding these efforts in a multidimensional conceptualization of climate that values student perspectives and includes elements of both engagement and safety. © 2017, American School Health Association.

Relationships between Student, Staff, and Administrative Measures of School Climate and Student Health and Academic Outcomes

PubMed Central

Gase, Lauren Nichol; Gomez, Louis M.; Kuo, Tony; Glenn, Beth A.; Inkelas, Moira; Ponce, Ninez A.

2018-01-01

BACKGROUND School climate is an integral part of a comprehensive approach to improving the wellbeing of students; however, little is known about the relationships between its different domains and measures. This study examined the relationships between student, staff, and administrative measures of school climate in order to understand the extent to which they were related to each other and student outcomes. METHODS The sample included 33,572 secondary school students from 121 schools in Los Angeles County during the 2014–2015 academic year. A multilevel regression model was constructed to examine the association between the domains and measures of school climate and five outcomes of student wellbeing: depressive symptoms or suicidal ideation, tobacco use, alcohol use, marijuana use, and grades. RESULTS Student, staff, and administrative measures of school climate were weakly correlated. Strong associations were found between student outcomes and student reports of engagement and safety, while school staff reports and administrative measures of school climate showed limited associations with student outcomes. CONCLUSIONS As schools seek to measure and implement interventions aimed at improving school climate, consideration should be given to grounding these efforts in a multi-dimensional conceptualization of climate that values student perspectives and includes elements of both engagement and safety. PMID:28382671

Civility norms, safety climate, and safety outcomes: a preliminary investigation.

PubMed

McGonagle, Alyssa K; Walsh, Benjamin M; Kath, Lisa M; Morrow, Stephanie L

2014-10-01

Working environments that are both civil and safe are good for business and employee well-being. Civility has been empirically linked to such important outcomes as organizational performance and individuals' positive work-related attitudes, yet research relating civility to safety is lacking. In this study, we link perceptions of civility norms to perceptions of safety climate and safety outcomes. Drawing on social exchange theory, we proposed and tested a model in 2 samples wherein civility norms indirectly relate to safety outcomes through associations with various safety climate facets. Our results supported direct relationships between civility and management safety climate and coworker safety climate. Additionally, indirect effects of civility norms on unsafe behaviors and injuries were observed. Indirect effects of civility norms on unsafe behaviors were observed through coworker safety climate and work-safety tension. Indirect effects of civility norms on injuries were observed through management safety climate and work-safety tension for full-time employees, although these effects did not hold for part-time employees. This study provides initial evidence that researchers and practitioners may want to look beyond safety climate to civility norms to more comprehensively understand the origins of unsafe behaviors and injuries and to develop appropriate preventive interventions. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Aridity under conditions of increased CO2

NASA Astrophysics Data System (ADS)

Greve, Peter; Roderick, Micheal L.; Seneviratne, Sonia I.

2016-04-01

A string of recent of studies led to the wide-held assumption that aridity will increase under conditions of increasing atmospheric CO2 concentrations and associated global warming. Such results generally build upon analyses of changes in the 'aridity index' (the ratio of potential evaporation to precipitation) and can be described as a direct thermodynamic effect on atmospheric water demand due to increasing temperatures. However, there is widespread evidence that contradicts the 'warmer is more arid' interpretation, leading to the 'global aridity paradox' (Roderick et al. 2015, WRR). Here we provide a comprehensive assessment of modeled changes in a broad set of dryness metrics (primarily based on a range of measures of water availability) over a large range of realistic atmospheric CO2 concentrations. We use an ensemble of simulations from of state-of-the-art climate models to analyse both equilibrium climate experiments and transient historical simulations and future projections. Our results show that dryness is, under conditions of increasing atmospheric CO2 concentrations and related global warming, generally decreasing at global scales. At regional scales we do, however, identify areas that undergo changes towards drier conditions, located primarily in subtropical climate regions and the Amazon Basin. Nonetheless, the majority of regions, especially in tropical and mid- to northern high latitudes areas, display wetting conditions in a warming world. Our results contradict previous findings and highlight the need to comprehensively assess all aspects of changes in hydroclimatological conditions at the land surface. Roderick, M. L., P. Greve, and G. D. Farquhar (2015), On the assessment of aridity with changes in atmospheric CO2, Water Resour. Res., 51, 5450-5463

Using EPA Tools and Data Services to Inform Changes to Design Storm Definitions for Wastewater Utilities based on Climate Model Projections

NASA Astrophysics Data System (ADS)

Tryby, M.; Fries, J. S.; Baranowski, C.

2014-12-01

Extreme precipitation events can cause significant impacts to drinking water and wastewater utilities, including facility damage, water quality impacts, service interruptions and potential risks to human health and the environment due to localized flooding and combined sewer overflows (CSOs). These impacts will become more pronounced with the projected increases in frequency and intensity of extreme precipitation events due to climate change. To model the impacts of extreme precipitation events, wastewater utilities often develop Intensity, Duration, and Frequency (IDF) rainfall curves and "design storms" for use in the U.S. Environmental Protection Agency's (EPA) Storm Water Management Model (SWMM). Wastewater utilities use SWMM for planning, analysis, and facility design related to stormwater runoff, combined and sanitary sewers, and other drainage systems in urban and non-urban areas. SWMM tracks (1) the quantity and quality of runoff made within each sub-catchment; and (2) the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period made up of multiple time steps. In its current format, EPA SWMM does not consider climate change projection data. Climate change may affect the relationship between intensity, duration, and frequency described by past rainfall events. Therefore, EPA is integrating climate projection data available in the Climate Resilience Evaluation and Awareness Tool (CREAT) into SWMM. CREAT is a climate risk assessment tool for utilities that provides downscaled climate change projection data for changes in the amount of rainfall in a 24-hour period for various extreme precipitation events (e.g., from 5-year to 100-year storm events). Incorporating climate change projections into SWMM will provide wastewater utilities with more comprehensive data they can use in planning for future storm events, thereby reducing the impacts to the utility and customers served from flooding and stormwater issues.

Potential Impacts of Climate Change on Native Plant Distributions in the Falkland Islands

PubMed Central

Upson, Rebecca; Williams, Jennifer J.; Wilkinson, Tim P.; Maclean, Ilya M. D.; McAdam, Jim H.; Moat, Justin F.

2016-01-01

The Falkland Islands are predicted to experience up to 2.2°C rise in mean annual temperature over the coming century, greater than four times the rate over the last century. Our study investigates likely vulnerabilities of a suite of range-restricted species whose distributions are associated with archipelago-wide climatic variation. We used present day climate maps calibrated using local weather data, 2020–2080 climate predictions from regional climate models, non-climate variables derived from a digital terrain model and a comprehensive database on local plant distributions. Weighted mean ensemble models were produced to assess changes in range sizes and overlaps between the current range and protected areas network. Target species included three globally threatened Falkland endemics, Nassauvia falklandica, Nastanthus falklandicus and Plantago moorei; and two nationally threatened species, Acaena antarctica and Blechnum cordatum. Our research demonstrates that temperature increases predicted for the next century have the potential to significantly alter plant distributions across the Falklands. Upland species, in particular, were found to be highly vulnerable to climate change impacts. No known locations of target upland species or the southwestern species Plantago moorei are predicted to remain environmentally suitable in the face of predicted climate change. We identify potential refugia for these species and associated gaps in the current protected areas network. Species currently restricted to the milder western parts of the archipelago are broadly predicted to expand their ranges under warmer temperatures. Our results emphasise the importance of implementing suitable adaptation strategies to offset climate change impacts, particularly site management. There is an urgent need for long-term monitoring and artificial warming experiments; the results of this study will inform the selection of the most suitable locations for these. Results are also helping inform management recommendations for the Falkland Islands Government who seek to better conserve their biodiversity and meet commitments to multi-lateral environmental agreements. PMID:27880846

Informing climate change adaptation in the Northeast and Midwest United States: The role of Climate Science Centers

NASA Astrophysics Data System (ADS)

Bryan, A. M.; Morelli, T. L.

2015-12-01

The Department of Interior Northeast Climate Science Center (NE CSC) is part of a federal network of eight Climate Science Centers created to provide scientific information and tools that managers and other parties interested in land, water, wildlife, and cultural resources can use to anticipate, monitor, and adapt to climate change. The NE CSC partners with other federal agencies, universities, and NGOs to facilitate stakeholder interaction and delivery of scientific products. For example, NE CSC researchers have partnered with the National Park Service to help managers at Acadia National Park adapt their infrastructure, operations, and ecosystems to rising seas and more extreme events. In collaboration with the tribal College of Menominee Nation and Michigan State University, the NE CSC is working with indigenous communities in Michigan and Wisconsin to co-develop knowledge of how to preserve their natural and cultural values in the face of climate change. Recently, in its largest collaborative initiative to date, the NE CSC led a cross-institutional effort to produce a comprehensive synthesis of climate change, its impacts on wildlife and their habitats, and available adaptation strategies across the entire Northeast and Midwest region; the resulting document was used by wildlife managers in 22 states to revise their Wildlife Action Plans (WAPs). Additionally, the NE CSC is working with the Wildlife Conservation Society to help inform moose conservation management. Other research efforts include hydrological modeling to inform culvert sizing under greater rainfall intensity, forest and landscape modeling to inform tree planting that mitigates the spread of invasive species, species and habitat modeling to help identify suitable locations for wildlife refugia. In addition, experimental research is being conducted to improve our understanding of how species such as brook trout are responding to climate change. Interacting with stakeholders during all phases of these projects ensures that the science produced meets their specific needs and allows them to make informed decisions to better adapt to our changing climate.

Potential Impacts of Climate Change on Native Plant Distributions in the Falkland Islands.

PubMed

Upson, Rebecca; Williams, Jennifer J; Wilkinson, Tim P; Clubbe, Colin P; Maclean, Ilya M D; McAdam, Jim H; Moat, Justin F

2016-01-01

The Falkland Islands are predicted to experience up to 2.2°C rise in mean annual temperature over the coming century, greater than four times the rate over the last century. Our study investigates likely vulnerabilities of a suite of range-restricted species whose distributions are associated with archipelago-wide climatic variation. We used present day climate maps calibrated using local weather data, 2020-2080 climate predictions from regional climate models, non-climate variables derived from a digital terrain model and a comprehensive database on local plant distributions. Weighted mean ensemble models were produced to assess changes in range sizes and overlaps between the current range and protected areas network. Target species included three globally threatened Falkland endemics, Nassauvia falklandica, Nastanthus falklandicus and Plantago moorei; and two nationally threatened species, Acaena antarctica and Blechnum cordatum. Our research demonstrates that temperature increases predicted for the next century have the potential to significantly alter plant distributions across the Falklands. Upland species, in particular, were found to be highly vulnerable to climate change impacts. No known locations of target upland species or the southwestern species Plantago moorei are predicted to remain environmentally suitable in the face of predicted climate change. We identify potential refugia for these species and associated gaps in the current protected areas network. Species currently restricted to the milder western parts of the archipelago are broadly predicted to expand their ranges under warmer temperatures. Our results emphasise the importance of implementing suitable adaptation strategies to offset climate change impacts, particularly site management. There is an urgent need for long-term monitoring and artificial warming experiments; the results of this study will inform the selection of the most suitable locations for these. Results are also helping inform management recommendations for the Falkland Islands Government who seek to better conserve their biodiversity and meet commitments to multi-lateral environmental agreements.

EPA Center for Corporate Climate Leadership

EPA Pesticide Factsheets

EPA's Center for Corporate Climate Leadership is a comprehensive resource to help organizations measure & manage GHG emissions. The Center provides technical tools, educational resources, opportunities for information sharing & highlights best practices.

A Framework for Prioritizing NOAA's Climate Data Portfolio to Improve Relevance and Value

NASA Astrophysics Data System (ADS)

Privette, J. L.; Hutchins, C.; McPherson, T.; Wunder, D.

2016-12-01

NOAA's National Centers for Environmental Information (NCEI) is the largest civilian environmental data archive in the world. NCEI operationally provides hundreds of long term homogeneous climate data records and assessments that describe Earth's atmosphere, oceans and land surface. For decades, these data have underpinned leading climate research and modeling efforts and provided key insights into weather and climate changes. Recently, NCEI has increased support for economic and societal sectors beyond climate research by emphasizing use-inspired product development and services. Accordingly, NCEI has begun comprehensively assessing customer needs and user applications. In parallel, NCEI is analyzing and adjusting its full product portfolio to best address those needs and applications. In this presentation, we will describe NCEI's new approaches to capturing needs, performing use analytics, and molding a more responsive portfolio. We will summarize the findings of a quantitative relevance- and cost-scoring analysis that suggests the relative effectiveness of NCEI science and service investments. Finally, we will describe NCEI's effort to review, document and validate customer-driven product requirements. Results will help guide future prioritization of measurements, research and development, and product services.

A Systematic Review of Global Drivers of Ant Elevational Diversity

PubMed Central

Szewczyk, Tim; McCain, Christy M.

2016-01-01

Ant diversity shows a variety of patterns across elevational gradients, though the patterns and drivers have not been evaluated comprehensively. In this systematic review and reanalysis, we use published data on ant elevational diversity to detail the observed patterns and to test the predictions and interactions of four major diversity hypotheses: thermal energy, the mid-domain effect, area, and the elevational climate model. Of sixty-seven published datasets from the literature, only those with standardized, comprehensive sampling were used. Datasets included both local and regional ant diversity and spanned 80° in latitude across six biogeographical provinces. We used a combination of simulations, linear regressions, and non-parametric statistics to test multiple quantitative predictions of each hypothesis. We used an environmentally and geometrically constrained model as well as multiple regression to test their interactions. Ant diversity showed three distinct patterns across elevations: most common were hump-shaped mid-elevation peaks in diversity, followed by low-elevation plateaus and monotonic decreases in the number of ant species. The elevational climate model, which proposes that temperature and precipitation jointly drive diversity, and area were partially supported as independent drivers. Thermal energy and the mid-domain effect were not supported as primary drivers of ant diversity globally. The interaction models supported the influence of multiple drivers, though not a consistent set. In contrast to many vertebrate taxa, global ant elevational diversity patterns appear more complex, with the best environmental model contingent on precipitation levels. Differences in ecology and natural history among taxa may be crucial to the processes influencing broad-scale diversity patterns. PMID:27175999

Quantifying the Climate Impacts of Land Use Change (Invited)

NASA Astrophysics Data System (ADS)

Anderson-Teixeira, K. J.; Snyder, P. K.; Twine, T. E.

2010-12-01

Climate change mitigation efforts that involve land use decisions call for comprehensive quantification of the climate services of terrestrial ecosystems. This is particularly imperative for analyses of the climate impact of bioenergy production, as land use change is often the single most important factor in determining bioenergy’s sustainability. However, current metrics of the climate services of terrestrial ecosystems used for policy applications—including biofuels life cycle analyses—account only for biogeochemical climate services (greenhouse gas regulation), ignoring biophysical climate regulation services (regulation of water and energy balances). Policies thereby run the risk of failing to advance the best climate solutions. Here, we present a quantitative metric that combines biogeochemical and biophysical climate services of terrestrial ecosystems, the ‘climate regulation value’ (CRV), which characterizes the climate benefit of maintaining an ecosystem over a multiple-year time frame. Using a combination of data synthesis and modeling, we calculate the CRV for a variety of natural and managed ecosystem types within the western hemisphere. Biogeochemical climate services are generally positive in unmanaged ecosystems (clearing the ecosystem has a warming effect), and may be positive or negative (clearing the ecosystem has a cooling effect) for managed ecosystems. Biophysical climate services may be either positive (e.g., tropical forests) or negative (e.g., high latitude forests). When averaged on a global scale, biogeochemical services usually outweigh biophysical services; however, biophysical climate services are not negligible. This implies that effective analysis of the climate impacts of bioenergy production must consider the integrated effects of biogeochemical and biophysical ecosystem climate services.

Early onset of industrial-era warming across the oceans and continents.

PubMed

Abram, Nerilie J; McGregor, Helen V; Tierney, Jessica E; Evans, Michael N; McKay, Nicholas P; Kaufman, Darrell S

2016-08-25

The evolution of industrial-era warming across the continents and oceans provides a context for future climate change and is important for determining climate sensitivity and the processes that control regional warming. Here we use post-ad 1500 palaeoclimate records to show that sustained industrial-era warming of the tropical oceans first developed during the mid-nineteenth century and was nearly synchronous with Northern Hemisphere continental warming. The early onset of sustained, significant warming in palaeoclimate records and model simulations suggests that greenhouse forcing of industrial-era warming commenced as early as the mid-nineteenth century and included an enhanced equatorial ocean response mechanism. The development of Southern Hemisphere warming is delayed in reconstructions, but this apparent delay is not reproduced in climate simulations. Our findings imply that instrumental records are too short to comprehensively assess anthropogenic climate change and that, in some regions, about 180 years of industrial-era warming has already caused surface temperatures to emerge above pre-industrial values, even when taking natural variability into account.

A dataset mapping the potential biophysical effects of vegetation cover change

NASA Astrophysics Data System (ADS)

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-02-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

A dataset mapping the potential biophysical effects of vegetation cover change

PubMed Central

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-01-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes. PMID:29461538

A Comprehensive Snow Density Model for Integrating Lidar-Derived Snow Depth Data into Spatial Snow Modeling

NASA Astrophysics Data System (ADS)

Marks, D. G.; Kormos, P.; Johnson, M.; Bormann, K. J.; Hedrick, A. R.; Havens, S.; Robertson, M.; Painter, T. H.

2017-12-01

Lidar-derived snow depths when combined with modeled or estimated snow density can provide reliable estimates of the distribution of SWE over large mountain areas. Application of this approach is transforming western snow hydrology. We present a comprehensive approach toward modeling bulk snow density that is reliable over a vast range of weather and snow conditions. The method is applied and evaluated over mountainous regions of California, Idaho, Oregon and Colorado in the western US. Simulated and measured snow density are compared at fourteen validation sites across the western US where measurements of snow mass (SWE) and depth are co-located. Fitting statistics for ten sites from three mountain catchments (two in Idaho, one in California) show an average Nash-Sutcliff model efficiency coefficient of 0.83, and mean bias of 4 kg m-3. Results illustrate issues associated with monitoring snow depth and SWE and show the effectiveness of the model, with a small mean bias across a range of snow and climate conditions in the west.

A Global Study of GPP focusing on Light Use Efficiency in a Random Forest Regression Model

NASA Astrophysics Data System (ADS)

Fang, W.; Wei, S.; Yi, C.; Hendrey, G. R.

2016-12-01

Light use efficiency (LUE) is at the core of mechanistic modeling of global gross primary production (GPP). However, most LUE estimates in global models are satellite-based and coarsely measured with emphasis on environmental variables. Others are from eddy covariance towers with much greater spatial and temporal data quality and emphasis on mechanistic processes, but in a limited number of sites. In this paper, we conducted a comprehensive global study of tower-based LUE from 237 FLUXNET towers, and scaled up LUEs from in-situ tower level to global biome level. We integrated key environmental and biological variables into the tower-based LUE estimates, at 0.5o x 0.5o grid-cell resolution, using a random forest regression (RFR) approach. We then developed an RFR-LUE-GPP model using the grid-cell LUE data, and compared it to a tower-LUE-GPP model by the conventional way of treating LUE as a series of biome-specific constants. In order to calibrate the LUE models, we developed a data-driven RFR-GPP model using a random forest regression method. Our results showed that LUE varies largely with latitude. We estimated a global area-weighted average of LUE at 1.21 gC m-2 MJ-1 APAR, which led to an estimated global GPP of 102.9 Gt C /year from 2000 to 2005. The tower-LUE-GPP model tended to overestimate forest GPP in tropical and boreal regions. Large uncertainties exist in GPP estimates over sparsely vegetated areas covered by savannas and woody savannas around the middle to low latitudes (i.g. 20oS to 40oS and 5oN to 15oN) due to lack of available data. Model results were improved by incorporating Köppen climate types to represent climate /meteorological information in machine learning modeling. This shed new light on the recognized issues of climate dependence of spring onset of photosynthesis and the challenges in modeling the biome GPP of evergreen broad leaf forests (EBF) accurately. The divergent responses of GPP to temperature and precipitation at mid-high latitudes and at mid-low latitudes echoed the necessity of modeling GPP separately by latitudes. This work provided a global distribution of LUE estimate, and developed a comprehensive algorithm modeling global terrestrial carbon with high spatial and temporal resolutions.

The status and challenge of global fire modelling

DOE PAGES

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; ...

2016-06-09

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

The status and challenge of global fire modelling

NASA Astrophysics Data System (ADS)

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao

2016-06-01

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

The status and challenge of global fire modelling

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

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

Strategies for Effective Implementation of Science Models into 6-9 Grade Classrooms on Climate, Weather, and Energy Topics

NASA Astrophysics Data System (ADS)

Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.

2011-12-01

As atmospheric scientists, we depend on Numerical Weather Prediction (NWP) models. We use them to predict weather patterns, to understand external forcing on the atmosphere, and as evidence to make claims about atmospheric phenomenon. Therefore, it is important that we adequately prepare atmospheric science students to use computer models. However, the public should also be aware of what models are in order to understand scientific claims about atmospheric issues, such as climate change. Although familiar with weather forecasts on television and the Internet, the general public does not understand the process of using computer models to generate a weather and climate forecasts. As a result, the public often misunderstands claims scientists make about their daily weather as well as the state of climate change. Since computer models are the best method we have to forecast the future of our climate, scientific models and modeling should be a topic covered in K-12 classrooms as part of a comprehensive science curriculum. According to the National Science Education Standards, teachers are encouraged to science models into the classroom as a way to aid in the understanding of the nature of science. However, there is very little description of what constitutes a science model, so the term is often associated with scale models. Therefore, teachers often use drawings or scale representations of physical entities, such as DNA, the solar system, or bacteria. In other words, models used in classrooms are often used as visual representations, but the purpose of science models is often overlooked. The implementation of a model-based curriculum in the science classroom can be an effective way to prepare students to think critically, problem solve, and make informed decisions as a contributing member of society. However, there are few resources available to help teachers implement science models into the science curriculum effectively. Therefore, this research project looks at strategies middle school science teachers use to implement science models into their classrooms. These teachers in this study took part in a week-long professional development designed to orient them towards appropriate use of science models for a unit on weather, climate, and energy concepts. The goal of this project is to describe the professional development and describe how teachers intend to incorporate science models into each of their individual classrooms.

PIMMS tools for capturing metadata about simulations

NASA Astrophysics Data System (ADS)

Pascoe, Charlotte; Devine, Gerard; Tourte, Gregory; Pascoe, Stephen; Lawrence, Bryan; Barjat, Hannah

2013-04-01

PIMMS (Portable Infrastructure for the Metafor Metadata System) provides a method for consistent and comprehensive documentation of modelling activities that enables the sharing of simulation data and model configuration information. The aim of PIMMS is to package the metadata infrastructure developed by Metafor for CMIP5 so that it can be used by climate modelling groups in UK Universities. PIMMS tools capture information about simulations from the design of experiments to the implementation of experiments via simulations that run models. PIMMS uses the Metafor methodology which consists of a Common Information Model (CIM), Controlled Vocabularies (CV) and software tools. PIMMS software tools provide for the creation and consumption of CIM content via a web services infrastructure and portal developed by the ES-DOC community. PIMMS metadata integrates with the ESGF data infrastructure via the mapping of vocabularies onto ESGF facets. There are three paradigms of PIMMS metadata collection: Model Intercomparision Projects (MIPs) where a standard set of questions is asked of all models which perform standard sets of experiments. Disciplinary level metadata collection where a standard set of questions is asked of all models but experiments are specified by users. Bespoke metadata creation where the users define questions about both models and experiments. Examples will be shown of how PIMMS has been configured to suit each of these three paradigms. In each case PIMMS allows users to provide additional metadata beyond that which is asked for in an initial deployment. The primary target for PIMMS is the UK climate modelling community where it is common practice to reuse model configurations from other researchers. This culture of collaboration exists in part because climate models are very complex with many variables that can be modified. Therefore it has become common practice to begin a series of experiments by using another climate model configuration as a starting point. Usually this other configuration is provided by a researcher in the same research group or by a previous collaborator with whom there is an existing scientific relationship. Some efforts have been made at the university department level to create documentation but there is a wide diversity in the scope and purpose of this information. The consistent and comprehensive documentation enabled by PIMMS will enable the wider sharing of climate model data and configuration information. The PIMMS methodology assumes an initial effort to document standard model configurations. Once these descriptions have been created users need only describe the specific way in which their model configuration is different from the standard. Thus the documentation burden on the user is specific to the experiment they are performing and fits easily into the workflow of doing their science. PIMMS metadata is independent of data and as such is ideally suited for documenting model development. PIMMS provides a framework for sharing information about failed model configurations for which data are not kept, the negative results that don't appear in scientific literature. PIMMS is a UK project funded by JISC, The University of Reading, The University of Bristol and STFC.

Assessment of Urbanization on the Integrated Land-Ocean-Atmosphere Environment in Coastal Metropolis in Preparation for HyspIRI

NASA Technical Reports Server (NTRS)

Sequera, Pedro; McDonald, Kyle C.; Gonzalez, Jorge; Arend, Mark; Krakauer, Nir; Bornstein, Robert; Luvll, Jeffrey

2012-01-01

The need for comprehensive studies of the relationships between past and projected changes of regional climate and human activity in comple x urban environments has been well established. The HyspIRI preparato ry airborne activities in California, associated science and applicat ions research, and eventually HyspIRI itself provide an unprecedented opportunity for development and implementation of an integrated data and modeling analysis system focused on coastal urban environments. We will utilize HyspIRI preparatory data collections in developing ne w remote sensing-based tools for investigating the integrated urban e nvironment, emphasizing weather, climate, and energy demands in compl ex coastal cities.

78 FR 36753 - North Atlantic Coast Comprehensive Study

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-19

... landscape system, considering future sea-level rise and climate change scenarios. In addition, the... management and climate change and sea-level rise considerations. Additional information and a study area map...

Deducing Climatic Elasticity to Assess Projected Climate Change Impacts on Streamflow Change across China

NASA Astrophysics Data System (ADS)

Liu, Jianyu; Zhang, Qiang; Zhang, Yongqiang; Chen, Xi; Li, Jianfeng; Aryal, Santosh K.

2017-10-01

Climatic elasticity has been widely applied to assess streamflow responses to climate changes. To fully assess impacts of climate under global warming on streamflow and reduce the error and uncertainty from various control variables, we develop a four-parameter (precipitation, catchment characteristics n, and maximum and minimum temperatures) climatic elasticity method named PnT, based on the widely used Budyko framework and simplified Makkink equation. We use this method to carry out the first comprehensive evaluation of the streamflow response to potential climate change for 372 widely spread catchments in China. The PnT climatic elasticity was first evaluated for a period 1980-2000, and then used to evaluate streamflow change response to climate change based on 12 global climate models under Representative Concentration Pathway 2.6 (RCP2.6) and RCP 8.5 emission scenarios. The results show that (1) the PnT climatic elasticity method is reliable; (2) projected increasing streamflow takes place in more than 60% of the selected catchments, with mean increments of 9% and 15.4% under RCP2.6 and RCP8.5 respectively; and (3) uncertainties in the projected streamflow are considerable in several regions, such as the Pearl River and Yellow River, with more than 40% of the selected catchments showing inconsistent change directions. Our results can help Chinese policy makers to manage and plan water resources more effectively, and the PnT climatic elasticity should be applied to other parts of the world.

The Portuguese Climate Portal

NASA Astrophysics Data System (ADS)

Gomes, Sandra; Deus, Ricardo; Nogueira, Miguel; Viterbo, Pedro; Miranda, Miguel; Antunes, Sílvia; Silva, Alvaro; Miranda, Pedro

2016-04-01

The Portuguese Local Warming Website (http://portaldoclima.pt) has been developed in order to support the society in Portugal in preparing for the adaptation to the ongoing and future effects of climate change. The climate portal provides systematic and easy access to authoritative scientific data ready to be used by a vast and diverse user community from different public and private sectors, key players and decision makers, but also to high school students, contributing to the increase in knowledge and awareness on climate change topics. A comprehensive set of regional climate variables and indicators are computed, explained and graphically presented. Variables and indicators were built in agreement with identified needs after consultation of the relevant social partners from different sectors, including agriculture, water resources, health, environment and energy and also in direct cooperation with the Portuguese National Strategy for Climate Change Adaptation (ENAAC) group. The visual interface allows the user to dynamically interact, explore, quickly analyze and compare, but also to download and import the data and graphics. The climate variables and indicators are computed from state-of-the-art regional climate model (RCM) simulations (e.g., CORDEX project), at high space-temporal detail, allowing to push the limits of the projections down to local administrative regions (NUTS3) and monthly or seasonal periods, promoting local adaptation strategies. The portal provides both historical data (observed and modelled for the 1971-2000 period) and future climate projections for different scenarios (modelled for the 2011-2100 period). A large effort was undertaken in order to quantify the impacts of the risk of extreme events, such as heavy rain and flooding, droughts, heat and cold waves, and fires. Furthermore the different climate scenarios and the ensemble of RCM models, with high temporal (daily) and spatial (~11km) detail, is taken advantage in order to quantify a plausible evolution of climate impacts and its uncertainties. Clear information on the data value and limitations is also provided. The portal is expected to become a reference tool for evaluation of impacts and vulnerabilities due to climate change, increased awareness and promotion of local adaptation and sustainable development in Portugal. The Portuguese Local Warming Website is part of the ADAPT programme, and is co-funded by the EEA financial mechanism and the Portuguese Carbon Fund.

Can Regional Climate Models Improve Warm Season Forecasts in the North American Monsoon Region?

NASA Astrophysics Data System (ADS)

Dominguez, F.; Castro, C. L.

2009-12-01

The goal of this work is to improve warm season forecasts in the North American Monsoon Region. To do this, we are dynamically downscaling warm season CFS (Climate Forecast System) reforecasts from 1982-2005 for the contiguous U.S. using the Weather Research and Forecasting (WRF) regional climate model. CFS is the global coupled ocean-atmosphere model used by the Climate Prediction Center (CPC), a branch of the National Center for Environmental Prediction (NCEP), to provide official U.S. seasonal climate forecasts. Recently, NCEP has produced a comprehensive long-term retrospective ensemble CFS reforecasts for the years 1980-2005. These reforecasts show that CFS model 1) has an ability to forecast tropical Pacific SSTs and large-scale teleconnection patterns, at least as evaluated for the winter season; 2) has greater skill in forecasting winter than summer climate; and 3) demonstrates an increase in skill when a greater number of ensembles members are used. The decrease in CFS skill during the warm season is due to the fact that the physical mechanisms of rainfall at this time are more related to mesoscale processes, such as the diurnal cycle of convection, low-level moisture transport, propagation and organization of convection, and surface moisture recycling. In general, these are poorly represented in global atmospheric models. Preliminary simulations for years with extreme summer climate conditions in the western and central U.S. (specifically 1988 and 1993) show that CFS-WRF simulations can provide a more realistic representation of convective rainfall processes. Thus a RCM can potentially add significant value in climate forecasting of the warm season provided the downscaling methodology incorporates the following: 1) spectral nudging to preserve the variability in the large scale circulation while still permitting the development of smaller-scale variability in the RCM; and 2) use of realistic soil moisture initial condition, in this case provided by the North American Regional Reanalysis. With these conditions, downscaled CFS-WRF reforecast simulations can produce realistic continental-scale patterns of warm season precipitation. This includes a reasonable representation of the North American monsoon in the southwest U.S. and northwest Mexico, which is notoriously difficult to represent in a global atmospheric model. We anticipate that this research will help lead the way toward substantially improved real time operational forecasts of North American summer climate with a RCM.

Modeling the Impacts of Global Climate and Regional Land Use Change on Regional Climate, Air Quality and Public Health in the New York Metropolitan Region

NASA Astrophysics Data System (ADS)

Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.

2002-12-01

There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human exposures and responses to heat stress and air quality differ as a function of socio-economic status and race/ethnicity across the region? The model systems used for this study are the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the Regional Atmospheric Modeling System (RAMS) and PennState/NCAR MM5 mesoscale meteorological models; the SLEUTH land use model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); the Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with Extensions (CAMx) models for simulating regional air quality; and exposure-risk coefficients for assessing population health impacts based on exposure to extreme heat, fine particulates (PM2.5) and ozone. Two different IPCC global emission scenarios and two different regional land use growth scenarios are considered in the simulations, spanning a range of possible futures. In addition to base simulations for selected time periods in the decade 1990 - 2000, the integrated model is used to simulate future scenarios in the 2020s, 2050s, and 2080s. Predictions from both the meteorological models and the air quality models are compared against available observations for the simulations in the 1990s to establish baseline model performance. A series of sensitivity tests will address whether changes in meteorology due to global climate change, changes in regional land use, or changes in emissions have the largest impact on predicted ozone and particulate matter concentrations.

Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae) habitat and population densities

PubMed Central

Kwan, Paul; Welch, Mitchell

2017-01-01

In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus. An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops. PMID:28875085

Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae) habitat and population densities.

PubMed

Al-Kindi, Khalifa M; Kwan, Paul; R Andrew, Nigel; Welch, Mitchell

2017-01-01

In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus . An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.

76 FR 36143 - Bombay Hook National Wildlife Refuge, Kent County, DE; Comprehensive Conservation Plan and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-21

.... During public scoping, we may identify additional issues. Climate Change and Interior Marsh Loss A growing body of evidence indicates that accelerating climate change, associated with increasing global.... Successful conservation strategies will require an understanding of climate change and the ability to predict...

The Iowa K-12 Climate Science Education Initiative: a comprehensive approach to meeting in-service teachers' stated needs for teaching climate literacy with NGSS

NASA Astrophysics Data System (ADS)

Stanier, C. O.; Spak, S.; Neal, T. A.; Herder, S.; Malek, A.; Miller, Z.

2017-12-01

The Iowa Board of Education voted unanimously in 2015 to adopt NGSS performance standards. The CGRER - College of Education Iowa K-12 Climate Science Education Initiative was established in 2016 to work directly with Iowa inservice teachers to provide what teachers need most to teach climate literacy and climate science content through investigational learning aligned with NGSS. Here we present teachers' requests for teaching climate with NGSS, and an approach to provide resources for place-based authentic inquiry on climate, developed, tested, and refined in partnership with inservice and preservice teachers. A survey of inservice middle school and high school science teachers was conducted at the 2016 Iowa Council of Teachers of Mathematics/Iowa Academy of Sciences - Iowa Science Teaching Section Fall Conference and online in fall 2016. Participants (n=383) were asked about their prior experience and education, the resources they use and need, their level of comfort in teaching climate science, perceived barriers, and how they address potential controversy. Teachers indicated preference for professional development on climate content and complete curricula packaged with lessons and interactive models aligned to Iowa standards, as well as training on instructional strategies to enhance students' ability to interpret scientific evidence. We identify trends in responses by teaching experience, climate content knowledge and its source, grade level, and urban and rural districts. Less than 20% of respondents reported controversy or negativity in teaching climate to date, and a majority were comfortable teaching climate science and climate change, with equal confidence in teaching climate and other STEM content through investigational activities. We present an approach and materials to meet these stated needs, created and tested in collaboration with Iowa teachers. We combine professional development and modular curricula with bundled standards, concepts, models, data, field activities, and sequences of individual and group investigational and student-driven inquiry prompts on climate science, climate change, and climate impacts. We identify key resource availability needed to teach place-based climate literacy aligned with NGSS as a standalone curriculum and through local impacts.

Global Climate Change: Using Field Studies to Prepare the Next Generation of Scientists

NASA Astrophysics Data System (ADS)

Arnold, T. C.; Hare, J.

2004-05-01

Global Climate Change is a new and invigorating concept in the pre-college classroom. To some it portends the altering of the Earth's climate by introducing anthropogenic influences and for others the natural progression of the Earth's systems. Regardless, climate change involves a plethora of environmental interactions and comprehension is a challenge for both teachers and students. This paper addresses a field studies program that prepares students to complete research projects associated with climate models affecting montane environments. It emphasizes a partnership between researchers from universities, government agencies, and public schools and their support of pre-college students in inquiry learning and research activities. Beginning in 1994 students from a Pennsylvania high school and schools in Scotland have engaged in biannual holistic studies of montane and glacial environments with the objective of completing investigations concerning the energy budgets of these environments. This paper will focus on 2000 and 2002, and the support and partnership of Dr. Jeff Hare and CIRES in designing, supporting, and providing professional interpretations,while assisting teachers and students toward the completion of recognized papers regarding climate studies. Introducing students to the employment and operation of complex field equipment will be discussed.

Hydrologic drivers of tree biodiversity: The impact of climate change (Invited)

NASA Astrophysics Data System (ADS)

Rodriguez-Iturbe, I.; Konar, M.; Muneepeerakul, R.; Azaele, S.; Bertuzzo, E.; Rinaldo, A.

2009-12-01

Biodiversity of forests is of major importance for society. The possible impact of climate change on the characteristics of tree diversity is a topic of crucial importance with relevant implications for conservation campaigns and resource management. Here we present the main results of the expected biodiversity changes in the Mississippi-Missouri River Basin (MMRS) and two of its subregions under different scenarios of possible climate change. A mechanistic neutral metapopulation model is developed to study the main drivers of large scale biodiversity signatures in the MMRS system. The region is divided into 824 Direct Tributary Areas (DTAs), each one characterized by its own habitat capacity. Data for the spatial occurrence of the 231 species present in the system is taken from the US Forest Service Inventory and Analysis Database. The model has permeable boundaries to account for immigration from the regions surrounding the MMRS. The model accounts for key aspects of ecological dynamics (e.g., birth, death, speciation, and migration) and is fundamentally driven by the mean annual precipitation characteristic of each of the DTAs in the system. It is found that such a simple model, with only four parameters, yields an excellent representation of the observed local species richness (LSR), between-community (β) diversity, and species rank-occupancy function. The mean annual rainfall of each DTA is then changed according to the climate scenarios and new habitat capacities are thus obtained throughout the MMRS and its subregions. The resulting large-scale biodiversity signatures are computed and compared with those of the present scenario, showing that there are very important changes arising from the climate change conditions. For the dry scenarios, it is shown that there is a considerable decrease of species richness, both at local and regional scales, and a contraction of species' geographic ranges. These findings link the hydrologic and ecological dynamics of the MMRS under climate change conditions and are important for a comprehensive evaluation of the climate change impacts over the United States.

Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections

NASA Astrophysics Data System (ADS)

Sun, S.; Sun, G.; Cohen, E.; McNulty, S. G.; Caldwell, P.; Duan, K.; Zhang, Y.

2015-12-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) dynamically downscaled climate projections of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12 digit Hydrologic Unit Code level) in the conterminous US (CONUS), and evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or 2-digit HUCs. Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8 °C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 g C m-2 yr-1 (9 %) increase in GPP. Response to climate change was highly variable across the 82, 773 watersheds, but in general, the majority would see consistent increases in all variables evaluated. Over half of the 82 773 watersheds, mostly found in the northeast and the southern part of the southwest would have an increase in annual Q (>100 mm yr-1 or 20 %). This study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results will be useful for policy-makers and land managers in formulating appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

Improve projections of changes in southern African summer rainfall through comprehensive multi-timescale empirical statistical downscaling

NASA Astrophysics Data System (ADS)

Dieppois, B.; Pohl, B.; Eden, J.; Crétat, J.; Rouault, M.; Keenlyside, N.; New, M. G.

2017-12-01

The water management community has hitherto neglected or underestimated many of the uncertainties in climate impact scenarios, in particular, uncertainties associated with decadal climate variability. Uncertainty in the state-of-the-art global climate models (GCMs) is time-scale-dependant, e.g. stronger at decadal than at interannual timescales, in response to the different parameterizations and to internal climate variability. In addition, non-stationarity in statistical downscaling is widely recognized as a key problem, in which time-scale dependency of predictors plays an important role. As with global climate modelling, therefore, the selection of downscaling methods must proceed with caution to avoid unintended consequences of over-correcting the noise in GCMs (e.g. interpreting internal climate variability as a model bias). GCM outputs from the Coupled Model Intercomparison Project 5 (CMIP5) have therefore first been selected based on their ability to reproduce southern African summer rainfall variability and their teleconnections with Pacific sea-surface temperature across the dominant timescales. In observations, southern African summer rainfall has recently been shown to exhibit significant periodicities at the interannual timescale (2-8 years), quasi-decadal (8-13 years) and inter-decadal (15-28 years) timescales, which can be interpret as the signature of ENSO, the IPO, and the PDO over the region. Most of CMIP5 GCMs underestimate southern African summer rainfall variability and their teleconnections with Pacific SSTs at these three timescales. In addition, according to a more in-depth analysis of historical and pi-control runs, this bias is might result from internal climate variability in some of the CMIP5 GCMs, suggesting potential for bias-corrected prediction based empirical statistical downscaling. A multi-timescale regression based downscaling procedure, which determines the predictors across the different timescales, has thus been used to simulate southern African summer rainfall. This multi-timescale procedure shows much better skills in simulating decadal timescales of variability compared to commonly used statistical downscaling approaches.

Managed relocation as an adaptation strategy for mitigating climate change threats to the persistence of an endangered lizard.

PubMed

Fordham, Damien A; Watts, Michael J; Delean, Steven; Brook, Brook W; Heard, Lee M B; Bull, C M

2012-09-01

The distributional ranges of many species are contracting with habitat conversion and climate change. For vertebrates, informed strategies for translocations are an essential option for decisions about their conservation management. The pygmy bluetongue lizard, Tiliqua adelaidensis, is an endangered reptile with a highly restricted distribution, known from only a small number of natural grassland fragments in South Australia. Land-use changes over the last century have converted perennial native grasslands into croplands, pastures and urban areas, causing substantial contraction of the species' range due to loss of essential habitat. Indeed, the species was thought to be extinct until its rediscovery in 1992. We develop coupled-models that link habitat suitability with stochastic demographic processes to estimate extinction risk and to explore the efficacy of potential climate adaptation options. These coupled-models offer improvements over simple bioclimatic envelope models for estimating the impacts of climate change on persistence probability. Applying this coupled-model approach to T. adelaidensis, we show that: (i) climate-driven changes will adversely impact the expected minimum abundance of populations and could cause extinction without management intervention, (ii) adding artificial burrows might enhance local population density, however, without targeted translocations this measure has a limited effect on extinction risk, (iii) managed relocations are critical for safeguarding lizard population persistence, as a sole or joint action and (iv) where to source and where to relocate animals in a program of translocations depends on the velocity, extent and nonlinearities in rates of climate-induced habitat change. These results underscore the need to consider managed relocations as part of any multifaceted plan to compensate the effects of habitat loss or shifting environmental conditions on species with low dispersal capacity. More broadly, we provide the first step towards a more comprehensive framework for integrating extinction risk, managed relocations and climate change information into range-wide conservation management. © 2012 Blackwell Publishing Ltd.

Developing a framework to assess the water quality and quantity impacts of climate change, shifting land use, and urbanization in a Midwestern agricultural landscape

NASA Astrophysics Data System (ADS)

Loheide, S. P.; Booth, E. G.; Kucharik, C. J.; Carpenter, S. R.; Gries, C.; Katt-Reinders, E.; Rissman, A. R.; Turner, M. G.

2011-12-01

Dynamic hydrological processes play a critical role in the structure and functioning of agricultural watersheds undergoing urbanization. Developing a predictive understanding of the complex interaction between agricultural productivity, ecosystem health, water quality, urban development, and public policy requires an interdisciplinary effort that investigates the important biophysical and social processes of the system. Our research group has initiated such a framework that includes a coordinated program of integrated scenarios, model experiments to assess the effects of changing drivers on a broad set of ecosystem services, evaluations of governance and leverage points, outreach and public engagement, and information management. Our geographic focus is the Yahara River watershed in south-central Wisconsin, which is an exemplar of water-related issues in the Upper Midwest. This research addresses three specific questions. 1) How do different patterns of land use, land cover, land management, and water resources engineering practices affect the resilience and sensitivity of ecosystem services under a changing climate? 2) How can regional governance systems for water and land use be made more resilient and adaptive to meet diverse human needs? 3) In what ways are regional human-environment systems resilient and in what ways are they vulnerable to potential changes in climate and water resources? A comprehensive program of model experiments and biophysical measurements will be utilized to evaluate changes in five freshwater ecosystem services (flood regulation, groundwater recharge, surface water quality, groundwater quality, and lake recreation) and five related ecosystem services (food crop yields, bioenergy crop yields, carbon storage in soil, albedo, and terrestrial recreation). Novel additions to existing biophysical models will allow us to simulate all components of the hydrological cycle as well as agricultural productivity, nitrogen and phosphorus transport, and lake water quality. The integrated model will be validated using a comprehensive observational database that includes soil moisture, evapotranspiration, stomatal conductance, streamflow, stream and lake water quality, and crop yields and productivity. Integrated scenarios will be developed to synthesize decision-maker perspectives, alternative approaches to resource governance, plausible trends in demographic and economic drivers, and model projections under alternate climate and land use regimes to understand future conditions of the watershed and its ecosystem services. The quantitative data and integrated scenarios will then be linked to evaluate governance of water and land use.

Modelling impacts of second generation bioenergy production on Ecosystem Services in Europe

NASA Astrophysics Data System (ADS)

Henner, Dagmar N.; Smith, Pete; Davies, Christian; McNamara, Niall P.

2015-04-01

Bioenergy crops are an important source of renewable energy and are a possible mechanism to mitigate global climate warming, by replacing fossil fuel energy with higher greenhouse gas emissions. There is, however, uncertainty about the impacts of the growth of bioenergy crops on ecosystem services. This uncertainty is further enhanced by the unpredictable climate change currently going on. The goal of this project is to develop a comprehensive model that covers as many ecosystem services as possible at a Continental level including biodiversity, water, GHG emissions, soil, and cultural services. The distribution and production of second generation energy crops, such as Miscanthus, Short Rotation Coppice (SRC) and Short Rotation Forestry (SRF), is currently being modelled, and ecosystem models will be used to examine the impacts of these crops on ecosystem services. The project builds on models of energy crop production, biodiversity, soil impacts, greenhouse gas emissions and other ecosystem services, and on work undertaken in the UK on the ETI-funded ELUM project (www.elum.ac.uk). In addition, methods like water footprint tools, tourism value maps and ecosystem valuation tools and models (e.g. InVest, TEEB database, GREET LCA Model, World Business Council for Sustainable Development corporate ecosystem valuation, Millennium Ecosystem Assessment and the Ecosystem Services Framework) will be utilised. Research will focus on optimisation of land use change feedbacks on ecosystem services and biodiversity, and weighting of the importance of the individual ecosystem services. Energy crops will be modelled using low, medium and high climate change scenarios for the years between 2015 and 2050. We will present first results for GHG emissions and soil organic carbon change after different land use change scenarios (e.g. arable to Miscanthus, forest to SRF), and with different climate warming scenarios. All this will be complemented by the presentation of a matrix including all the factors and ecosystem services influenced by land use change to bioenergy crop production under different climate change scenarios.

What does the 2°C target imply for a global climate agreement in 2020? The limits study on Durban Platform scenarios

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

KRIEGLER, ELMAR; TAVONI, MASSIMO; ABOUMAHBOUB, TINO

This paper provides a novel and comprehensive model-based assessment of possible outcomes of the Durban Platform negotiations with a focus on emissions reduction requirements, the consistency with the 2°C target and global economic impacts. The Durban Platform scenarios investigated in the LIMITS study — all assuming the implementation of comprehensive global emission reductions after 2020, but assuming different 2020 emission reduction levels as well as different long-term concentration targets — exhibit a probability of exceeding the 2°C limit of 22–41% when reaching 450 (450–480) ppm CO 2e, and 35–59% when reaching 500 (480–520) ppm CO 2e in 2100. Forcing andmore » temperature show a peak and decline pattern for both targets. Consistency of the resulting temperature trajectory with the 2°C target is a societal choice, and may be based on the maximum exceedance probability at the time of the peak and the long run exceedance probability, e.g., in the year 2100. The challenges of implementing a long-term target after a period of fragmented near-term climate policy can be significant as reflected in steep reductions of emissions intensity and transitional and long-term economic impacts. In particular, the challenges of adopting the target are significantly higher in 2030 than in 2020, both in terms of required emissions intensity decline rates and economic impacts. Finally, we conclude that an agreement on comprehensive emissions reductions to be implemented from 2020 onwards has particular significance for meeting long-term climate policy objectives.« less

Build a Catastrophe: Using Digital World and Policy Models to Engage Political Science Students with Climate Change

NASA Astrophysics Data System (ADS)

Horodyskyj, L.; Lennon, T.; Mead, C.; Anbar, A. D.

2017-12-01

Climate change is a problem that involves science, economics, and politics. Particularly in the United States, political resistance to addressing climate change has been exacerbated by a concerted misinformation campaign against the basic science, a negative response to how the proposed solutions to climate change intersect with values. Scientists often propose more climate science education as a solution to the problem, but preliminary studies indicate that more science education does not necessarily reduce polarization on the topic (Kahan et al. 2012). Is there a way that we can better engage non-science students in topics related to climate change that improve their comprehension of the problem and its implications, overcoming polarization? In an existing political science course, "Do You Want to Build a Nation?", we are testing a new digital world-building model based on resource development and consequent environmental and societal impacts. Students spend half the class building their nations based on their assigned ideology (i.e., socialist, absolute monarchy, libertarian) and the second half of the class negotiating with other nations to resolve global issues while remaining true to their ideologies. The course instructor, co-author Lennon, and ASU's Center for Education Through eXploration have collaborated to design a digital world model based on resources linked to an adaptive decision-making environment that translates student policies into modifications to the digital world. The model tracks students' exploration and justification of their nation's policy choices. In the Fall 2017 offering of the course, we will investigate how this digital world model and scenarios built around it affect student learning outcomes. Specifically, we anticipate improved understanding of the policy trade-offs related to energy development, better understanding of the ways that different ideologies approach solutions to climate change, and that both will result in more realistic diplomatic negotiations in the latter half of the course. We will report on the technical details of how the digital world model and scenarios are constructed as well as how students responded to the scenario.

Agriculture in West Africa in the Twenty-First Century: Climate Change and Impacts Scenarios, and Potential for Adaptation

PubMed Central

Sultan, Benjamin; Gaetani, Marco

2016-01-01

West Africa is known to be particularly vulnerable to climate change due to high climate variability, high reliance on rain-fed agriculture, and limited economic and institutional capacity to respond to climate variability and change. In this context, better knowledge of how climate will change in West Africa and how such changes will impact crop productivity is crucial to inform policies that may counteract the adverse effects. This review paper provides a comprehensive overview of climate change impacts on agriculture in West Africa based on the recent scientific literature. West Africa is nowadays experiencing a rapid climate change, characterized by a widespread warming, a recovery of the monsoonal precipitation, and an increase in the occurrence of climate extremes. The observed climate tendencies are also projected to continue in the twenty-first century under moderate and high emission scenarios, although large uncertainties still affect simulations of the future West African climate, especially regarding the summer precipitation. However, despite diverging future projections of the monsoonal rainfall, which is essential for rain-fed agriculture, a robust evidence of yield loss in West Africa emerges. This yield loss is mainly driven by increased mean temperature while potential wetter or drier conditions as well as elevated CO2 concentrations can modulate this effect. Potential for adaptation is illustrated for major crops in West Africa through a selection of studies based on process-based crop models to adjust cropping systems (change in varieties, sowing dates and density, irrigation, fertilizer management) to future climate. Results of the cited studies are crop and region specific and no clear conclusions can be made regarding the most effective adaptation options. Further efforts are needed to improve modeling of the monsoon system and to better quantify the uncertainty in its changes under a warmer climate, in the response of the crops to such changes and in the potential for adaptation. PMID:27625660

Agriculture in West Africa in the Twenty-First Century: Climate Change and Impacts Scenarios, and Potential for Adaptation.

PubMed

Sultan, Benjamin; Gaetani, Marco

2016-01-01

West Africa is known to be particularly vulnerable to climate change due to high climate variability, high reliance on rain-fed agriculture, and limited economic and institutional capacity to respond to climate variability and change. In this context, better knowledge of how climate will change in West Africa and how such changes will impact crop productivity is crucial to inform policies that may counteract the adverse effects. This review paper provides a comprehensive overview of climate change impacts on agriculture in West Africa based on the recent scientific literature. West Africa is nowadays experiencing a rapid climate change, characterized by a widespread warming, a recovery of the monsoonal precipitation, and an increase in the occurrence of climate extremes. The observed climate tendencies are also projected to continue in the twenty-first century under moderate and high emission scenarios, although large uncertainties still affect simulations of the future West African climate, especially regarding the summer precipitation. However, despite diverging future projections of the monsoonal rainfall, which is essential for rain-fed agriculture, a robust evidence of yield loss in West Africa emerges. This yield loss is mainly driven by increased mean temperature while potential wetter or drier conditions as well as elevated CO2 concentrations can modulate this effect. Potential for adaptation is illustrated for major crops in West Africa through a selection of studies based on process-based crop models to adjust cropping systems (change in varieties, sowing dates and density, irrigation, fertilizer management) to future climate. Results of the cited studies are crop and region specific and no clear conclusions can be made regarding the most effective adaptation options. Further efforts are needed to improve modeling of the monsoon system and to better quantify the uncertainty in its changes under a warmer climate, in the response of the crops to such changes and in the potential for adaptation.

Hydrological regime modifications induced by climate change in Mediterranean area

NASA Astrophysics Data System (ADS)

Pumo, Dario; Caracciolo, Domenico; Viola, Francesco; Valerio Noto, Leonardo

2015-04-01

The knowledge of river flow regimes has a capital importance for a variety of practical applications, in water resource management, including optimal and sustainable use. Hydrological regime is highly dependent on climatic factors, among which the most important is surely the precipitation, in terms of frequency, seasonal distribution and intensity of rainfall events. The streamflow frequency regime of river basins are often summarized by flow duration curves (FDCs), that offer a simple and comprehensive graphical view of the overall historical variability associated with streamflow, and characterize the ability of the basin to provide flows of various magnitudes. Climate change is likely to lead shifts in the hydrological regime, and, consequently, in the FDCs. Staring from this premise, the primary objective of the present study is to explore the effects of potential climate changes on the hydrological regime of some small Mediterranean basins. To this aim it is here used a recent hydrological model, the ModABa model (MODel for Annual flow duration curves assessment in ephemeral small BAsins), for the probabilistic characterization of the daily streamflows in small catchments. The model has been calibrated and successively validated in a unique small catchment, where it has shown a satisfactory accuracy in reproducing the empirical FDC starting from easily derivable parameters arising from basic ecohydrological knowledge of the basin and commonly available climatic data such as daily precipitation and temperatures. Thus, this work also represents a first attempt to apply the ModABa to basins different from that used for its preliminary design in order to testing its generality. Different case studies are selected within the Sicily region; the model is first calibrated at the sites and then forced by future climatic scenarios, highlighting the principal differences emerging from the current scenario and future FDCs. The future climate scenarios are generated using a stochastic downscaling technique based on the weather generator, AWE-GEN. This methodology allows for the downscaling of an ensemble of climate model outputs deriving the frequency distribution functions of factors of change for several statistics of temperature and precipitation from outputs of General Circulation Models (GCMs). The stochastic downscaling is carried out using simulations of GCMs adopted in the IPCC 5AR, for the future periods of 2046-2065 and 2081-2100.

The distribution and abundance ofa nuisance native alga, Didymosphenia geminata,in streams of Glacier National Park: Climate drivers and management implications

USGS Publications Warehouse

Muhlfeld, Clint C.; Jones, Leslie A.; E. William Schweiger,; Isabel W. Ashton,; Loren L. Bahls,

2011-01-01

Didymosphenia geminata (didymo) is a freshwater alga native to North America, including Glacier National Park, Montana. It has long been considered a cold-water species, but has recently spread to lower latitudes and warmer waters, and increasingly forms large blooms that cover streambeds. We used a comprehensive monitoring data set from the National Park Service (NPS) and USGS models of stream temperatures to explore the drivers of didymo abundance in Glacier National Park. We estimate that approximately 64% of the stream length in the park contains didymo, with around 5% in a bloom state. Results suggest that didymo abundance likely increased over the study period (2007–2009), with blooms becoming more common. Our models suggest that didymo abundance is positively related to summer stream temperatures and negatively related to total nitrogen and the distance downstream from lakes. Regional climate model simulations indicate that stream temperatures in the park will likely continue to increase over the coming decades, which may increase the extent and severity of didymo blooms. As a result, didymo may be a useful indicator of thermal and hydrological modification associated with climate warming, especially in a relatively pristine system like Glacier where proximate human-related disturbances are absent or reduced. Glacier National Park plays an important role as a sentinel for climate change and associated education across the Rocky Mountain region.

The distribution and abundance of a nuisance native alga, Didymosphen Didymosphenia geminata, in streams of Glacier National Park: Climate drivers and management implications

USGS Publications Warehouse

William, Schweiger E.; Ashton, I.W.; Muhlfeld, C.C.; Jones, L.A.; Bahls, L.L.

2011-01-01

Didymosphenia geminata (didymo) is a freshwater alga native to North America, including Glacier National Park, Montana. It has long been considered a cold-water species, but has recently spread to lower latitudes and warmer waters, and increasingly forms large blooms that cover streambeds. We used a comprehensive monitoring data set from the National Park Service (NPS) and USGS models of stream temperatures to explore the drivers of didymo abundance in Glacier National Park. We estimate that approximately 64% of the stream length in the park contains didymo, with around 5% in a bloom state. Results suggest that didymo abundance likely increased over the study period (2007-2009), with blooms becoming more common. Our models suggest that didymo abundance is positively related to summer stream temperatures and negatively related to total nitrogen and the distance downstream from lakes. Regional climate model simulations indicate that stream temperatures in the park will likely continue to increase over the coming decades, which may increase the extent and severity of didymo blooms. As a result, didymo may be a useful indicator of thermal and hydrological modification associated with climate warming, especially in a relatively pristine system like Glacier where proximate human-related disturbances are absent or reduced. Glacier National Park plays an important role as a sentinel for climate change and associated education across the Rocky Mountain region.

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

NASA Technical Reports Server (NTRS)

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

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

DOE PAGES

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

2016-08-24

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

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

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

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

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

Linking Satellite Remote Sensing Based Environmental Predictors to Disease: AN Application to the Spatiotemporal Modelling of Schistosomiasis in Ghana

NASA Astrophysics Data System (ADS)

Wrable, M.; Liss, A.; Kulinkina, A.; Koch, M.; Biritwum, N. K.; Ofosu, A.; Kosinski, K. C.; Gute, D. M.; Naumova, E. N.

2016-06-01

90% of the worldwide schistosomiasis burden falls on sub-Saharan Africa. Control efforts are often based on infrequent, small-scale health surveys, which are expensive and logistically difficult to conduct. Use of satellite imagery to predictively model infectious disease transmission has great potential for public health applications. Transmission of schistosomiasis requires specific environmental conditions to sustain freshwater snails, however has unknown seasonality, and is difficult to study due to a long lag between infection and clinical symptoms. To overcome this, we employed a comprehensive 8-year time-series built from remote sensing feeds. The purely environmental predictor variables: accumulated precipitation, land surface temperature, vegetative growth indices, and climate zones created from a novel climate regionalization technique, were regressed against 8 years of national surveillance data in Ghana. All data were aggregated temporally into monthly observations, and spatially at the level of administrative districts. The result of an initial mixed effects model had 41% explained variance overall. Stratification by climate zone brought the R2 as high as 50% for major zones and as high as 59% for minor zones. This can lead to a predictive risk model used to develop a decision support framework to design treatment schemes and direct scarce resources to areas with the highest risk of infection. This framework can be applied to diseases sensitive to climate or to locations where remote sensing would be better suited than health surveys.

VOC Reactivity and the Ozone Climate Penalty: Modeled Impacts of Updated Aromatic and Monoterpene Chemistry on the Ozone-temperature Connection

NASA Astrophysics Data System (ADS)

Porter, W. C.; Heald, C. L.; Safieddine, S.

2016-12-01

Rising temperatures associated with global warming can increase concentrations of tropospheric ozone (O3) in many regions worldwide, a correlation often described as the "ozone climate penalty". This effect is driven by a variety of underlying chemical, physical, and biological mechanisms, including temperature-dependent reaction rates, emissions of volatile organic compounds (VOCs) from trees and other plant life, and correlations with other meteorological variables. While many of the most important O3-producing VOCs, such as isoprene, are represented in typical chemical transport models such as GEOS-Chem, others - including aromatics from fires and human activity and monoterpenes from natural sources - are not always included in gas-phase chemistry. Here we examine the impact of increased VOC reactivity on the ozone climate penalty due to a more comprehensive treatment of aromatics and monoterpenes in the chemical transport model GEOS-Chem, finding regional impacts not only on daily O3 levels themselves, but also on the O3/temperature relationship. While many uncertainties related to the emissions and chemistry of these species remain, the impact of their inclusion on both current simulations and future projections indicates their importance towards the overall goal of more accurately modeled surface O3.

Predicting the geographical distribution of two invasive termite species from occurrence data.

PubMed

Tonini, Francesco; Divino, Fabio; Lasinio, Giovanna Jona; Hochmair, Hartwig H; Scheffrahn, Rudolf H

2014-10-01

Predicting the potential habitat of species under both current and future climate change scenarios is crucial for monitoring invasive species and understanding a species' response to different environmental conditions. Frequently, the only data available on a species is the location of its occurrence (presence-only data). Using occurrence records only, two models were used to predict the geographical distribution of two destructive invasive termite species, Coptotermes gestroi (Wasmann) and Coptotermes formosanus Shiraki. The first model uses a Bayesian linear logistic regression approach adjusted for presence-only data while the second one is the widely used maximum entropy approach (Maxent). Results show that the predicted distributions of both C. gestroi and C. formosanus are strongly linked to urban development. The impact of future scenarios such as climate warming and population growth on the biotic distribution of both termite species was also assessed. Future climate warming seems to affect their projected probability of presence to a lesser extent than population growth. The Bayesian logistic approach outperformed Maxent consistently in all models according to evaluation criteria such as model sensitivity and ecological realism. The importance of further studies for an explicit treatment of residual spatial autocorrelation and a more comprehensive comparison between both statistical approaches is suggested.

Will climate change increase irrigation requirements in agriculture of Central Europe? A simulation study for Northern Germany.

PubMed

Riediger, Jan; Breckling, Broder; Nuske, Robert S; Schröder, Winfried

2014-01-01

By example of a region in Northern Germany (County of Uelzen), this study investigates whether climate change is likely to require adaption of agricultural practices such as irrigation in Central Europe. Due to sandy soils with low water retention capacity and occasional insufficient rainfall, irrigation is a basic condition for agricultural production in the county of Uelzen. Thus, in the framework of the comprehensive research cluster Nachhaltiges Landmanagement im Norddeutschen Tiefland ( NaLaMa-nT ), we investigated whether irrigation might need to be adapted to changing climatic conditions. To this end, results from regionalised climate change modelling were coupled with soil- and crop-specific evapotranspiration models to calculate potential amounts of irrigation to prevent crop failures. Three different runs of the climate change scenario RCP 8.5 were used for the time period until 2070. The results show that the extent of probable necessary irrigation will likely increase in the future. For the scenario run with the highest temperature rise, the results suggest that the amount of ground water presently allowed to be extracted for irrigation might not be sufficient in the future to retain common agricultural pattern. The investigation at hand exemplifies data requirements and methods to estimate irrigation needs under climate change conditions. Restriction of ground water withdrawal by German environmental regulation may require an adaptation of crop selection and alterations in agricultural practice also in regions with comparable conditions.

Climate Change and Conservation Planning in California: The San Francisco Bay Area Upland Habitat Goals Approach

NASA Astrophysics Data System (ADS)

Branciforte, R.; Weiss, S. B.; Schaefer, N.

2008-12-01

Climate change threatens California's vast and unique biodiversity. The Bay Area Upland Habitat Goals is a comprehensive regional biodiversity assessment of the 9 counties surrounding San Francisco Bay, and is designing conservation land networks that will serve to protect, manage, and restore that biodiversity. Conservation goals for vegetation, rare plants, mammals, birds, fish, amphibians, reptiles, and invertebrates are set, and those goals are met using the optimization algorithm MARXAN. Climate change issues are being considered in the assessment and network design in several ways. The high spatial variability at mesoclimatic and topoclimatic scales in California creates high local biodiversity, and provides some degree of local resiliency to macroclimatic change. Mesoclimatic variability from 800 m scale PRISM climatic norms is used to assess "mesoclimate spaces" in distinct mountain ranges, so that high mesoclimatic variability, especially local extremes that likely support range limits of species and potential climatic refugia, can be captured in the network. Quantitative measures of network resiliency to climate change include the spatial range of key temperature and precipitation variables within planning units. Topoclimatic variability provides a finer-grained spatial patterning. Downscaling to the topoclimatic scale (10-50 m scale) includes modeling solar radiation across DEMs for predicting maximum temperature differentials, and topographic position indices for modeling minimum temperature differentials. PRISM data are also used to differentiate grasslands into distinct warm and cool types. The overall conservation strategy includes local and regional connectivity so that range shifts can be accommodated.

Health impact assessment of global climate change: expanding on comparative risk assessment approaches for policy making.

PubMed

Patz, Jonathan; Campbell-Lendrum, Diarmid; Gibbs, Holly; Woodruff, Rosalie

2008-01-01

Climate change is projected to have adverse impacts on public health. Cobenefits may be possible from more upstream mitigation of greenhouse gases causing climate change. To help measure such cobenefits alongside averted disease-specific risks, a health impact assessment (HIA) framework can more comprehensively serve as a decision support tool. HIA also considers health equity, clearly part of the climate change problem. New choices for energy must be made carefully considering such effects as additional pressure on the world's forests through large-scale expansion of soybean and oil palm plantations, leading to forest clearing, biodiversity loss and disease emergence, expulsion of subsistence farmers, and potential increases in food prices and emissions of carbon dioxide to the atmosphere. Investigators must consider the full range of policy options, supported by more comprehensive, flexible, and transparent assessment methods.

Diverging Responses of Tropical Andean Biomes under Future Climate Conditions

PubMed Central

Tovar, Carolina; Arnillas, Carlos Alberto; Cuesta, Francisco; Buytaert, Wouter

2013-01-01

Observations and projections for mountain regions show a strong tendency towards upslope displacement of their biomes under future climate conditions. Because of their climatic and topographic heterogeneity, a more complex response is expected for biodiversity hotspots such as tropical mountain regions. This study analyzes potential changes in the distribution of biomes in the Tropical Andes and identifies target areas for conservation. Biome distribution models were developed using logistic regressions. These models were then coupled to an ensemble of 8 global climate models to project future distribution of the Andean biomes and their uncertainties. We analysed projected changes in extent and elevational range and identified regions most prone to change. Our results show a heterogeneous response to climate change. Although the wetter biomes exhibit an upslope displacement of both the upper and the lower boundaries as expected, most dry biomes tend to show downslope expansion. Despite important losses being projected for several biomes, projections suggest that between 74.8% and 83.1% of the current total Tropical Andes will remain stable, depending on the emission scenario and time horizon. Between 3.3% and 7.6% of the study area is projected to change, mostly towards an increase in vertical structure. For the remaining area (13.1%–17.4%), there is no agreement between model projections. These results challenge the common believe that climate change will lead to an upslope displacement of biome boundaries in mountain regions. Instead, our models project diverging responses, including downslope expansion and large areas projected to remain stable. Lastly, a significant part of the area expected to change is already affected by land use changes, which has important implications for management. This, and the inclusion of a comprehensive uncertainty analysis, will help to inform conservation strategies in the Tropical Andes, and to guide similar assessments for other tropical mountains. PMID:23667651

The potential effects of climate change on the distribution and productivity of Cunninghamia lanceolata in China.

PubMed

Liu, Yupeng; Yu, Deyong; Xun, Bin; Sun, Yun; Hao, Ruifang

2014-01-01

Climate changes may have immediate implications for forest productivity and may produce dramatic shifts in tree species distributions in the future. Quantifying these implications is significant for both scientists and managers. Cunninghamia lanceolata is an important coniferous timber species due to its fast growth and wide distribution in China. This paper proposes a methodology aiming at enhancing the distribution and productivity of C. lanceolata against a background of climate change. First, we simulated the potential distributions and establishment probabilities of C. lanceolata based on a species distribution model. Second, a process-based model, the PnET-II model, was calibrated and its parameterization of water balance improved. Finally, the improved PnET-II model was used to simulate the net primary productivity (NPP) of C. lanceolata. The simulated NPP and potential distribution were combined to produce an integrated indicator, the estimated total NPP, which serves to comprehensively characterize the productivity of the forest under climate change. The results of the analysis showed that (1) the distribution of C. lanceolata will increase in central China, but the mean probability of establishment will decrease in the 2050s; (2) the PnET-II model was improved, calibrated, and successfully validated for the simulation of the NPP of C. lanceolata in China; and (3) all scenarios predicted a reduction in total NPP in the 2050s, with a markedly lower reduction under the a2 scenario than under the b2 scenario. The changes in NPP suggested that forest productivity will show a large decrease in southern China and a mild increase in central China. All of these findings could improve our understanding of the impact of climate change on forest ecosystem structure and function and could provide a basis for policy-makers to apply adaptive measures and overcome the unfavorable influences of climate change.

Impact of climate change on groundwater resources in Southern Austria

NASA Astrophysics Data System (ADS)

Reszler, C.; Harum, T.; Poltnig, W.; Saccon, P.; Reichl, P.; Ruch, C.; Kopeinig, C.; Freundl, G.; Schlamberger, J.; Zessar, H.; Suette, G.

2012-04-01

Groundwater is the most important source for drinking water in Austria. In some parts of Southern Austria water resources already are very vulnerable to unfavourable climate conditions. This paper summarizes case studies of estimating the impact of climate change on groundwater recharge and groundwater flow in Southern Austria in the frame of the ETC-Alpine Space project ALP-WATER-SCARCE. In several pilot regions a distributed hydrological model was set up to simulate groundwater recharge and groundwater flow for a period of 10 to 30 years. The pilot sites range from mountainous catchments with steep hillslopes to Alpine valleys and flatlands with pore aquifers. In the model period comprehensive land data and meteorological data were used, and the models were calibrated to available stream gauge data. Additional low flow monitoring in the frame of the project also allowed for a more detailed regional analysis in some catchments. The simulations were firstly used to extend runoff and groundwater recharge depths on an annual basis up to 200 years into the past by regression analysis with long time meteorological parameters (HISTALP). The historical view shows that groundwater flow and recharge in most of the pilot regions decreased since the beginning of the 20th century, which is mainly the effect of climate change. Changes of land use are of minor relevance in most of the regions. Second, by the calibrated model scenarios were simulated to quantify the impact of a possible future change in the climatic conditions on water resources. The scenarios were generated by altering the model input by a "Delta-Change", under consideration of the historical development. These scenarios can be interpreted as "what if"-scenarios to quantify the sensitivity of the hydrological systems on these climatic variables. The results are compared with actual and projected water uses as a basis for regional water resources management.

Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes: Part I. Comprehensive model evaluation and trend analysis for 2006 and 2011

DOE PAGES

Chen, Ying; Zhang, Yang; Fan, Jiwen; ...

2015-08-18

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at themore » surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2, SO 2, PM 2.5, and PM 10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.« less

Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part I. Comprehensive Model Evaluation and Trend Analysis for 2006 and 2011

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

Chen, Ying; Zhang, Yang; Fan, Jiwen

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at themore » surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2, SO 2, PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.« less

Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes: Part I. Comprehensive model evaluation and trend analysis for 2006 and 2011

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

Chen, Ying; Zhang, Yang; Fan, Jiwen

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at themore » surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2, SO 2, PM 2.5, and PM 10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.« less

Climate and environmental change drives Ixodes ricinus geographical expansion at the northern range margin

PubMed Central

2014-01-01

Background Global environmental change is causing spatial and temporal shifts in the distribution of species and the associated diseases of humans, domesticated animals and wildlife. In the on-going debate on the influence of climate change on vectors and vector-borne diseases, there is a lack of a comprehensive interdisciplinary multi-factorial approach utilizing high quality spatial and temporal data. Methods We explored biotic and abiotic factors associated with the latitudinal and altitudinal shifts in the distribution of Ixodes ricinus observed during the last three decades in Norway using antibodies against Anaplasma phagocytophilum in sheep as indicators for tick presence. Samples obtained from 2963 sheep from 90 farms in 3 ecologically different districts during 1978 – 2008 were analysed. We modelled the presence of antibodies against A. phagocytophilum to climatic-, environmental and demographic variables, and abundance of wild cervids and domestic animals, using mixed effect logistic regressions. Results Significant predictors were large diurnal fluctuations in ground surface temperature, spring precipitation, duration of snow cover, abundance of red deer and farm animals and bush encroachment/ecotones. The length of the growth season, mean temperature and the abundance of roe deer were not significant in the model. Conclusions Our results highlight the need to consider climatic variables year-round to disentangle important seasonal variation, climatic threshold changes, climate variability and to consider the broader environmental change, including abiotic and biotic factors. The results offer novel insight in how tick and tick-borne disease distribution might be modified by future climate and environmental change. PMID:24401487

A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems

USGS Publications Warehouse

Collins, Scott L.; Belnap, Jayne; Grimm, N. B.; Rudgers, J. A.; Dahm, Clifford N.; D'Odorico, P.; Litvak, M.; Natvig, D. O.; Peters, Douglas C.; Pockman, W. T.; Sinsabaugh, R. L.; Wolf, B. O.

2014-01-01

Ecological processes in arid lands are often described by the pulse-reserve paradigm, in which rain events drive biological activity until moisture is depleted, leaving a reserve. This paradigm is frequently applied to processes stimulated by one or a few precipitation events within a growing season. Here we expand the original framework in time and space and include other pulses that interact with rainfall. This new hierarchical pulse-dynamics framework integrates space and time through pulse-driven exchanges, interactions, transitions, and transfers that occur across individual to multiple pulses extending from micro to watershed scales. Climate change will likely alter the size, frequency, and intensity of precipitation pulses in the future, and arid-land ecosystems are known to be highly sensitive to climate variability. Thus, a more comprehensive understanding of arid-land pulse dynamics is needed to determine how these ecosystems will respond to, and be shaped by, increased climate variability.

Did Aboriginal vegetation burning affect the Australian summer monsoon?

NASA Astrophysics Data System (ADS)

Balcerak, Ernie

2011-08-01

For thousands of years, Aboriginal Australians burned forests, creating grasslands. Some studies have suggested that in addition to changing the landscape, these burning practices also affected the timing and intensity of the Australian summer monsoon. Different vegetation types can alter evaporation, roughness, and surface reflectivity, leading to changes in the weather and climate. On the basis of an ensemble of experiments with a global climate model, Notaro et al. conducted a comprehensive evaluation of the effects of decreased vegetation cover on the summer monsoon in northern Australia. They found that although decreased vegetation cover would have had only minor effects during the height of the monsoon season, during the premonsoon season, burning-induced vegetation loss would have caused significant decreases in precipitation and increases in temperature. Thus, by burning forests, Aboriginals altered the local climate, effectively extending the dry season and delaying the start of the monsoon season. (Geophysical Research Letters, doi:10.1029/2011GL047774, 2011)

Interacting effects of climate change and habitat fragmentation on drought-sensitive butterflies

NASA Astrophysics Data System (ADS)

Oliver, Tom H.; Marshall, Harry H.; Morecroft, Mike D.; Brereton, Tom; Prudhomme, Christel; Huntingford, Chris

2015-10-01

Climate change is expected to increase the frequency of some climatic extremes. These may have drastic impacts on biodiversity, particularly if meteorological thresholds are crossed, leading to population collapses. Should this occur repeatedly, populations may be unable to recover, resulting in local extinctions. Comprehensive time series data on butterflies in Great Britain provide a rare opportunity to quantify population responses to both past severe drought and the interaction with habitat area and fragmentation. Here, we combine this knowledge with future projections from multiple climate models, for different Representative Concentration Pathways (RCPs), and for simultaneous modelled responses to different landscape characteristics. Under RCP8.5, which is associated with `business as usual’ emissions, widespread drought-sensitive butterfly population extinctions could occur as early as 2050. However, by managing landscapes and particularly reducing habitat fragmentation, the probability of persistence until mid-century improves from around zero to between 6 and 42% (95% confidence interval). Achieving persistence with a greater than 50% chance and right through to 2100 is possible only under both low climate change (RCP2.6) and semi-natural habitat restoration. Our data show that, for these drought-sensitive butterflies, persistence is achieved more effectively by restoring semi-natural landscapes to reduce fragmentation, rather than simply focusing on increasing habitat area, but this will only be successful in combination with substantial emission reductions.

Allowable carbon emissions lowered by multiple climate targets.

PubMed

Steinacher, Marco; Joos, Fortunat; Stocker, Thomas F

2013-07-11

Climate targets are designed to inform policies that would limit the magnitude and impacts of climate change caused by anthropogenic emissions of greenhouse gases and other substances. The target that is currently recognized by most world governments places a limit of two degrees Celsius on the global mean warming since preindustrial times. This would require large sustained reductions in carbon dioxide emissions during the twenty-first century and beyond. Such a global temperature target, however, is not sufficient to control many other quantities, such as transient sea level rise, ocean acidification and net primary production on land. Here, using an Earth system model of intermediate complexity (EMIC) in an observation-informed Bayesian approach, we show that allowable carbon emissions are substantially reduced when multiple climate targets are set. We take into account uncertainties in physical and carbon cycle model parameters, radiative efficiencies, climate sensitivity and carbon cycle feedbacks along with a large set of observational constraints. Within this framework, we explore a broad range of economically feasible greenhouse gas scenarios from the integrated assessment community to determine the likelihood of meeting a combination of specific global and regional targets under various assumptions. For any given likelihood of meeting a set of such targets, the allowable cumulative emissions are greatly reduced from those inferred from the temperature target alone. Therefore, temperature targets alone are unable to comprehensively limit the risks from anthropogenic emissions.

Effects of climate change and seed dispersal on airborne ragweed pollen loads in Europe

NASA Astrophysics Data System (ADS)

Hamaoui-Laguel, Lynda; Vautard, Robert; Liu, Li; Solmon, Fabien; Viovy, Nicolas; Khvorostyanov, Dmitry; Essl, Franz; Chuine, Isabelle; Colette, Augustin; Semenov, Mikhail A.; Schaffhauser, Alice; Storkey, Jonathan; Thibaudon, Michel; Epstein, Michelle M.

2015-08-01

Common ragweed (Ambrosia artemisiifolia) is an invasive alien species in Europe producing pollen that causes severe allergic disease in susceptible individuals. Ragweed plants could further invade European land with climate and land-use changes. However, airborne pollen evolution depends not only on plant invasion, but also on pollen production, release and atmospheric dispersion changes. To predict the effect of climate and land-use changes on airborne pollen concentrations, we used two comprehensive modelling frameworks accounting for all these factors under high-end and moderate climate and land-use change scenarios. We estimate that by 2050 airborne ragweed pollen concentrations will be about 4 times higher than they are now, with a range of uncertainty from 2 to 12 largely depending on the seed dispersal rate assumptions. About a third of the airborne pollen increase is due to on-going seed dispersal, irrespective of climate change. The remaining two-thirds are related to climate and land-use changes that will extend ragweed habitat suitability in northern and eastern Europe and increase pollen production in established ragweed areas owing to increasing CO2. Therefore, climate change and ragweed seed dispersal in current and future suitable areas will increase airborne pollen concentrations, which may consequently heighten the incidence and prevalence of ragweed allergy.

Chapter 2: Effects of climatic variability and change. In Effects of Climate Variability and Change on Forest Ecosystems: A Comprehensive Science Synthesis for the U.S. Forest Sector; General Technical Report PNW-GTR-870, Washington DC

EPA Science Inventory

Climate profoundly shapes forests. Forest species composition, productivity, availability of goods and services, disturbance regimes, and location on the landscape are all regulated by climate. Much research attention has focused on the problem of predicting the response of fores...

An Integrative Wave Model for the Marginal Ice Zone based on a Rheological Parameterization

DTIC Science & Technology

2013-09-30

climate in the present and future Arctic seas. OBJECTIVES 1. To build a comprehensive wave-ice interaction mathematical framework for a wide...group (e.g. Fox and Squire, 1994, Meylan and Squire, 1996, Bennetts and Squire, 2009) is also applicable to the case of ice floes imbedded in a frazil...environmental protection purposes: such as navigation route planning, offshore structure design in the Arctic , and coastal erosion prevention. They

Simulation of comprehensive chemistry and atmospheric methane lifetime in the LGM with EMAC

NASA Astrophysics Data System (ADS)

Gromov, Sergey; Steil, Benedikt

2017-04-01

Past records of atmospheric methane (CH4) abundance/isotope composition may provide a substantial insight on C exchanges in the Earth System (ES). When simulated in the climate models, CH4 helps to identify climate parameters transitions via triggering of its different (natural) sources, with a proviso that its sinks are adequately represented in the model. The latter are still a matter of large uncertainty in the studies focussing on the interpretation of CH4 evolution throughout Last Glacial Maximum (LGM), judging the conferred span of tropospheric CH4 lifetime (λ) of 3-16 yr [1-4]. In this study, we attempt to: (i) deliver the most adequate estimate of the LGM atmospheric sink of CH4 in the EMAC AC-GCM [5] equipped with the comprehensive representation of atmospheric chemistry [6], (ii) reveal the ES and CH4 emission parameters that are most influential for λ and (iii) based on these findings, suggest a parameterisation for λ that may be consistently used in climate models. In pursuing (i) we have tuned the EMAC model for simulating LGM atmospheric chemistry state, including careful revisiting of the trace gases emissions from the biosphere, biomass burning/lightning source, etc. The latter affect the key simulated component bound with λ, viz. the abundance and distribution of the hydroxyl radicals (OH) which, upon reacting with CH4, constitute its main tropospheric sink. Our preliminary findings suggest that OH is buffered in the atmosphere in a similar fashion to preindustrial climate, which in line with the recent studies employing comprehensive chemistry mechanisms (e.g., [3]). The analysis in (ii) suggests that tropospheric λ values may be qualitatively described as a convolution of values typical for zonal domain with high and low photolytic recycling rates (i.e. tropics and extra-tropics), as in the latter a dependence of the zonal average λ value on the CH4 emission strength exists. We further use the extensive diagnostic in EMAC to infer the sensitivity of zonal OH to changes in various component of the ES, e.g. in stratospheric O3 input and dynamics. Finally, we discuss the potential set of parameters required for efficient λ and/or OH parameterisation implementation in models dealing with (transient) climate simulations. References 1. Fischer, H., et al.: Changing boreal methane sources and constant biomass burning during the last termination, Nature, 452, 864-867, doi: 10.1038/nature06825, 2008. 2. Kaplan, J. O., Folberth, G.,and Hauglustaine, D. A.: Role of methane and biogenic volatile organic compound sources in late glacial and Holocene fluctuations of atmospheric methane concentrations, Global Biogeochemical Cycles, 20, n/a-n/a, doi: 10.1029/2005GB002590, 2006. 3. Murray, L. T., et al.: Factors controlling variability in the oxidative capacity of the troposphere since the Last Glacial Maximum, Atmos. Chem. Phys., 14, 3589-3622, doi: 10.5194/acp-14-3589-2014, 2014. 4. Valdes, P. J., Beerling, D. J.,and Johnson, C. E.: The ice age methane budget, Geophysical Research Letters, 32, n/a-n/a, doi: 10.1029/2004GL021004, 2005. 5. Jöckel, P., et al.: Development cycle 2 of the Modular Earth Submodel System (MESSy2), Geosci. Model Dev., 3, 717-752, doi: 10.5194/gmd-3-717-2010, 2010. 6. Lelieveld, J., et al.: Global tropospheric hydroxyl distribution, budget and reactivity, Atmos. Chem. Phys., 16, 12477-12493, doi: 10.5194/acp-16-12477-2016, 2016.

Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

NASA Astrophysics Data System (ADS)

Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Christensen, Hannah M.; Juricke, Stephan; Subramanian, Aneesh; Watson, Peter A. G.; Weisheimer, Antje; Palmer, Tim N.

2017-03-01

The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), together with coupled transient runs (1850-2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate - specifically the Madden-Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

Climate Change and a Global City: An Assessment of the Metropolitan East Coast Region

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia; Solecki, William

1999-01-01

The objective of the research is to derive an assessment of the potential climate change impacts on a global city - in this case the 31 county region that comprises the New York City metropolitan area. This study comprises one of the regional components that contribute to the ongoing U.S. National Assessment: The Potential Consequences of Climate Variability and Change and is an application of state-of-the-art climate change science to a set of linked sectoral assessment analyses for the Metro East Coast (MEC) region. We illustrate how three interacting elements of global cities react and respond to climate variability and change with a broad conceptual model. These elements include: people (e.g., socio- demographic conditions), place (e.g., physical systems), and pulse (e.g., decision-making and economic activities). The model assumes that a comprehensive assessment of potential climate change can be derived from examining the impacts within each of these elements and at their intersections. Thus, the assessment attempts to determine the within-element and the inter-element effects. Five interacting sector studies representing the three intersecting elements are evaluated. They include the Coastal Zone, Infrastructure, Water Supply, Public Health, and Institutional Decision-making. Each study assesses potential climate change impacts on the sector and on the intersecting elements, through the analysis of the following parts: 1. Current conditions of sector in the region; 2. Lessons and evidence derived from past climate variability; 3. Scenario predictions affecting sector; potential impacts of scenario predictions; 4. Knowledge/information gaps and critical issues including identification of additional research questions, effectiveness of modeling efforts, equity of impacts, potential non-local interactions, and policy recommendations; and 5. Identification of coping strategies - i.e., resilience building, mitigation strategies, new technologies, education that affects decision-making, and better preparedness for contingencies.

Development and Implementation of a Comprehensive Radiometric Validation Protocol for the CERES Earth Radiation Budget Climate Record Sensors

NASA Technical Reports Server (NTRS)

Priestley, K. J.; Matthews, G.; Thomas, S.

2006-01-01

The CERES Flight Models 1 through 4 instruments were launched aboard NASA's Earth Observing System (EOS) Terra and Aqua Spacecraft into 705 Km sun-synchronous orbits with 10:30 a.m. and 1:30 p.m. equatorial crossing times. These instruments supplement measurements made by the CERES Proto Flight Model (PFM) instrument launched aboard NASA's Tropical Rainfall Measuring Mission (TRMM) into a 350 Km, 38-degree mid-inclined orbit. CERES Climate Data Records consist of geolocated and calibrated instantaneous filtered and unfiltered radiances through temporally and spatially averaged TOA, Surface and Atmospheric fluxes. CERES filtered radiance measurements cover three spectral bands including shortwave (0.3 to 5 microns), total (0.3 to 100 microns) and an atmospheric window channel (8 to 12 microns). The CERES Earth Radiation Budget measurements represent a new era in radiation climate data, realizing a factor of 2 to 4 improvement in calibration accuracy and stability over the previous ERBE climate records, while striving for the next goal of 0.3-percent per decade absolute stability. The current improvement is derived from two sources: the incorporation of lessons learned from the ERBE mission in the design of the CERES instruments and the development of a rigorous and comprehensive radiometric validation protocol consisting of individual studies covering different spatial, spectral and temporal time scales on data collected both pre and post launch. Once this ensemble of individual perspectives is collected and organized, a cohesive and highly rigorous picture of the overall end-to-end performance of the CERES instrument's and data processing algorithms may be clearly established. This approach has resulted in unprecedented levels of accuracy for radiation budget instruments and data products with calibration stability of better than 0.2-percent and calibration traceability from ground to flight of 0.25-percent. The current work summarizes the development, philosophy and implementation of the protocol designed to rigorously quantify the quality of the data products as well as the level of agreement between the CERES TRMM, Terra and Aqua climate data records.

Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

NASA Technical Reports Server (NTRS)

Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.

2013-01-01

Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

Effects of adjusting cropping systems on utilization efficiency of climatic resources in Northeast China under future climate scenarios

NASA Astrophysics Data System (ADS)

Guo, Jianping; Zhao, Junfang; Xu, Yanhong; Chu, Zheng; Mu, Jia; Zhao, Qian

Quantitatively evaluating the effects of adjusting cropping systems on the utilization efficiency of climatic resources under climate change is an important task for assessing food security in China. To understand these effects, we used daily climate variables obtained from the regional climate model RegCM3 from 1981 to 2100 under the A1B scenario and crop observations from 53 agro-meteorological experimental stations from 1981 to 2010 in Northeast China. Three one-grade zones of cropping systems were divided by heat, water, topography and crop-type, including the semi-arid areas of the northeast and northwest (III), the one crop area of warm-cool plants in semi-humid plain or hilly regions of the northeast (IV), and the two crop area in irrigated farmland in the Huanghuaihai Plain (VI). An agro-ecological zone model was used to calculate climatic potential productivities. The effects of adjusting cropping systems on climate resource utilization in Northeast China under the A1B scenario were assessed. The results indicated that from 1981 to 2100 in the III, IV and VI areas, the planting boundaries of different cropping systems in Northeast China obviously shifted toward the north and the east based on comprehensively considering the heat and precipitation resources. However, due to high temperature stress, the climatic potential productivity of spring maize was reduced in the future. Therefore, adjusting the cropping system is an effective way to improve the climatic potential productivity and climate resource utilization. Replacing the one crop in one year model (spring maize) by the two crops in one year model (winter wheat and summer maize) significantly increased the total climatic potential productivity and average utilization efficiencies. During the periods of 2011-2040, 2041-2070 and 2071-2100, the average total climatic potential productivities of winter wheat and summer maize increased by 9.36%, 11.88% and 12.13% compared to that of spring maize, respectively. Additionally, compared with spring maize, the average utilization efficiencies of thermal resources of winter wheat and summer maize dramatically increased by 9.2%, 12.1% and 12.0%, respectively. The increases in the average utilization efficiencies of precipitation resources of winter wheat and summer maize were 1.78 kg hm-2 mm-1, 2.07 kg hm-2 mm-1 and 1.92 kg hm-2 mm-1 during 2011-2040, 2041-2070 and 2071-2100, respectively. Our findings highlight that adjusting cropping systems can dominantly contribute to utilization efficiency increases of agricultural climatic resources in Northeast China in the future.

Cover crops as a gateway to greater conservation in Iowa?: Integrating crop models, field trials, economics and farmer perspectives regarding soil resilience in light of climate change

NASA Astrophysics Data System (ADS)

Roesch-McNally, G. E.; Basche, A.; Tyndall, J.; Arbuckle, J. G.; Miguez, F.; Bowman, T.

2014-12-01

Scientists predict a number of climate changes for the US Midwest with expected declines in crop productivity as well as eco-hydrological impacts. More frequent extreme rain events particularly in the spring may well increase saturated soils thus complicating agronomic interests and also exacerbate watershed scale impairments (e.g., sediment, nutrient loss). In order to build more resilient production systems in light of climate change, farmers will increasingly need to implement conservation practices (singularly or more likely in combination) that enable farmers to manage profitable businesses yet mitigate consequential environmental impacts that have both in-field and off-farm implications. Cover crops are empirically known to promote many aspects of soil and water health yet even the most aggressive recent estimates show that only 1-2% of the total acreage in Iowa have been planted to cover crops. In order to better understand why farmers are reluctant to adopt cover crops across Iowa we combined agronomic and financial data from long-term field trials, working farm trials and model simulations so as to present comprehensive data-driven information to farmers in focus group discussions in order to understand existing barriers, perceived benefits and responses to the information presented. Four focus groups (n=29) were conducted across Iowa in four geographic regions. Focus group discussions help explore the nuance of farmers' responses to modeling outputs and their real-life agronomic realities, thus shedding light on the social and psychological barriers with cover crop utilization. Among the key insights gained, comprehensive data-driven research can influence farmer perspectives on potential cover crop impacts to cash crop yields, experienced costs are potentially quite variable, and having field/farm benefits articulated in economic terms are extremely important when farmers weigh the opportunity costs associated with adopting new practices. Our work represents multidisciplinary collaboration necessary to gain greater understanding of what it will take for farmers to cover the ground to prevent erosion and nutrient losses in the context of a changing climate.

Past, present and future distributions of an Iberian Endemic, Lepus granatensis: ecological and evolutionary clues from species distribution models.

PubMed

Acevedo, Pelayo; Melo-Ferreira, José; Real, Raimundo; Alves, Paulo Célio

2012-01-01

The application of species distribution models (SDMs) in ecology and conservation biology is increasing and assuming an important role, mainly because they can be used to hindcast past and predict current and future species distributions. However, the accuracy of SDMs depends on the quality of the data and on appropriate theoretical frameworks. In this study, comprehensive data on the current distribution of the Iberian hare (Lepus granatensis) were used to i) determine the species' ecogeographical constraints, ii) hindcast a climatic model for the last glacial maximum (LGM), relating it to inferences derived from molecular studies, and iii) calibrate a model to assess the species future distribution trends (up to 2080). Our results showed that the climatic factor (in its pure effect and when it is combined with the land-cover factor) is the most important descriptor of the current distribution of the Iberian hare. In addition, the model's output was a reliable index of the local probability of species occurrence, which is a valuable tool to guide species management decisions and conservation planning. Climatic potential obtained for the LGM was combined with molecular data and the results suggest that several glacial refugia may have existed for the species within the major Iberian refugium. Finally, a high probability of occurrence of the Iberian hare in the current species range and a northward expansion were predicted for future. Given its current environmental envelope and evolutionary history, we discuss the macroecology of the Iberian hare and its sensitivity to climate change.

Modeling the Effects of Hydrogeomorphology and Climactic Factors on Nitrogen, Phosphorus, and Greenhouse Gas Dynamics in Riparian Zones.

NASA Astrophysics Data System (ADS)

Hassanzadeh, Y.; Vidon, P.; Gold, A.; Pradhanang, S. M.; Addy, K.

2017-12-01

Vegetated riparian zones are often considered for use as best management practices to mitigate the impacts of agriculture on water quality. However, riparian zones can also be a source of greenhouse gases and their influence on water quality varies depending on landscape hydrogeomorphic characteristics and climate. Methods used to evaluate riparian zone functions include conceptual models, and spatially explicit and process based models (REMM), but very few attempts have been made to connect riparian zone characteristics with function using easily accessible landscape scale data. Here, we present comprehensive statistical models that can be used to assess riparian zone functions with easily obtainable landscape-scale hydrogeomorphic attributes and climate data. Models were developed from a database spanning 88 years and 36 sites. Statistical methods including principal component analysis and stepwise regression were used to reduced data dimensionality and identify significant predictors. Models were validated using additional data collected from scientific literature. The 8 models developed connect landscape characteristics to nitrogen and phosphorus concentration and removal (1-4), greenhouse gas emissions (5-7), and water table depth (8). Results show the range of influence that various climate and landscape characteristics have on riparian zone functions, and the tradeoffs that exist with regards to nitrogen, phosphorous, and greenhouse gases. These models will help reduce the need for extensive field measurements and help scientists and land managers make more informed decisions regarding the use of riparian zones for water quality management.

Between Too Little and Too Late: Political Opportunity Costs in Climate Policy Analysis

NASA Astrophysics Data System (ADS)

Gilligan, J. M.; Vandenbergh, M. P.

2014-12-01

Discussion of climate policy has focused almost exclusively on comprehensive regulatory instruments to price emissions with tradeable permits or emissions taxes. More recently, a number of proposals have been advanced to abandon comprehensive emissions pricing in favor of focusing exclusively on clean-energy innovation. Neither approach adequately accounts for the combination of timing and scale. Advocates of emissions pricing are persuasive that this is the most likely way to reduce emissions sufficiently to stabilize greenhouse gas (GHG) concentrations at desirable levels. However, as innovation advocates point out, the political climate is inhospitable to such sweeping regulations and it is unlikely that comprehensive carbon pricing can be enacted and implemented in the next decade. However, clean-energy innovation by itself is a high-stakes gamble that may fail to reduce emissions sufficiently to stabilize GHG concentrations, and may reduce support for the kind of comprehensive pricing measures that could stabilize GHG concentrations.We propose that analysis of climate policies take account of the opportunity costs associated with the process of enacting a proposed policy: If one measure is much more controversial than another, how does the difference in time necessary to persuade the public and legislators to adopt them affect their ultimate impact? As General Patton is reputed to have said, "A good solution applied with vigor now is better than a perfect solution applied ten minutes later." Similarly, it is important to consider whether adopting one measure would build or erode support for complementary ones. As an example, we consider the largely neglected role of nonregulatory measures, such as private governance and household-level behavior change, as examples of actions that could buy time by producing rapid, although modest, impacts without eroding support for more comprehensive measures later on.

The 1430s: a cold period of extraordinary internal climate variability during the early Spörer Minimum with social and economic impacts in north-western and central Europe

NASA Astrophysics Data System (ADS)

Camenisch, Chantal; Keller, Kathrin M.; Salvisberg, Melanie; Amann, Benjamin; Bauch, Martin; Blumer, Sandro; Brázdil, Rudolf; Brönnimann, Stefan; Büntgen, Ulf; Campbell, Bruce M. S.; Fernández-Donado, Laura; Fleitmann, Dominik; Glaser, Rüdiger; González-Rouco, Fidel; Grosjean, Martin; Hoffmann, Richard C.; Huhtamaa, Heli; Joos, Fortunat; Kiss, Andrea; Kotyza, Oldřich; Lehner, Flavio; Luterbacher, Jürg; Maughan, Nicolas; Neukom, Raphael; Novy, Theresa; Pribyl, Kathleen; Raible, Christoph C.; Riemann, Dirk; Schuh, Maximilian; Slavin, Philip; Werner, Johannes P.; Wetter, Oliver

2016-12-01

Changes in climate affected human societies throughout the last millennium. While European cold periods in the 17th and 18th century have been assessed in detail, earlier cold periods received much less attention due to sparse information available. New evidence from proxy archives, historical documentary sources and climate model simulations permit us to provide an interdisciplinary, systematic assessment of an exceptionally cold period in the 15th century. Our assessment includes the role of internal, unforced climate variability and external forcing in shaping extreme climatic conditions and the impacts on and responses of the medieval society in north-western and central Europe.Climate reconstructions from a multitude of natural and anthropogenic archives indicate that the 1430s were the coldest decade in north-western and central Europe in the 15th century. This decade is characterised by cold winters and average to warm summers resulting in a strong seasonal cycle in temperature. Results from comprehensive climate models indicate consistently that these conditions occurred by chance due to the partly chaotic internal variability within the climate system. External forcing like volcanic eruptions tends to reduce simulated temperature seasonality and cannot explain the reconstructions. The strong seasonal cycle in temperature reduced food production and led to increasing food prices, a subsistence crisis and a famine in parts of Europe. Societies were not prepared to cope with failing markets and interrupted trade routes. In response to the crisis, authorities implemented numerous measures of supply policy and adaptation such as the installation of grain storage capacities to be prepared for future food production shortfalls.

Organizational Climate: The Overlooked Dimension of Institutional Effectiveness. AIR 1999 Annual Forum Paper.

ERIC Educational Resources Information Center

Brown, J. David; VanWagoner, Randall J.

This paper reports on an ongoing organizational climate assessment used as one of 10 indicators of institutional effectiveness at a midsize suburban community college. Organizational climate is thought to allow more precise specifications than the overall organizational culture and facilitates, a more comprehensive comparison of change in both…

Climate-related genetic variation in drought-resistance of Douglas-fir ( Pseudotsuga menziesii )

Treesearch

Sheel Bansal; Constance A. Harrington; Peter J. Gould; J. Bradley St.Clair

2014-01-01

There is a general assumption that intraspecific populations originating from relatively arid climates will be better adapted to cope with the expected increase in drought from climate change. For ecologically and economically important species, more comprehensive, genecological studies that utilize large distributions of populations and direct measures of traits...

A Comprehensive Climate Science and Solutions Education Curriculum

NASA Astrophysics Data System (ADS)

Byrne, J. M.; Cook, J.; Little, L. J.; Peacock, K.; Sinclair, P.; Zeller, C.

2016-12-01

We are creating a broadly based curriculum for a multidisciplinary University/College course on climate change science and solutions. Climate change is a critical topic for all members of society and certainly for all students in postsecondary education. The curriculum will feature a wide range of topic presentations on the (i) science of climate change; and (ii) multidisciplinary solutions to climate change challenges. The end result will be an online textbook featuring short contributions from session participants and other invited specialists. First authors in this AGU Education Session will provide a 20-minute comprehensive lecture that will be recorded and shared as part of the online textbook. The recorded talks will be merged with author provided PowerPoint slides and appropriate high definition video footage to support the discussion, where possible. Authors will be asked to sign a waiver allowing the video recording to be part of the online textbook. Access to the videos and textbook chapters will be provided online to students registered in recognized university classes on climate change science and solutions for a modest fee.

A comparison and appraisal of a comprehensive range of human thermal climate indices

NASA Astrophysics Data System (ADS)

de Freitas, C. R.; Grigorieva, E. A.

2017-03-01

Numerous human thermal climate indices have been proposed. It is a manifestation of the perceived importance of the thermal environment within the scientific community and a desire to quantify it. Schemes used differ in approach according to the number of variables taken into account, the rationale employed, and the particular design for application. They also vary considerably in type and quality, method used to express output, as well as in several other aspects. In light of this, a three-stage project was undertaken to deliver a comprehensive documentation, classification, and overall evaluation of the full range of existing human thermal climate indices. The first stage of the project produced a comprehensive register of as many thermal indices as could be found, 165 in all. The second stage devised a sorting scheme of these human thermal climate indices that grouped them according to eight primary classification categories. This, the third stage of the project, evaluates the indices. Six evaluation criteria, namely validity, usability, transparency, sophistication, completeness, and scope, are used collectively as evaluation criteria to rate each index scheme. The evaluation criteria are used to assign a score that varies between 1 and 5, 5 being the highest. The indices with the highest in each of the eight primary classification categories are discussed. The work is the final stage of a study of the all human thermal climatic indices that could be found in literature. Others have considered the topic, but this study is the first detailed, genuinely comprehensive, and systematic comparison. The results make it simpler to locate and compare indices. It is now easier for users to reflect on the merits of all available thermal indices and decide which is most suitable for a particular application or investigation.

The socialization of dominance: peer group contextual effects on homophobic and dominance attitudes.

PubMed

Poteat, V Paul; Espelage, Dorothy L; Green, Harold D

2007-06-01

Using the framework of social dominance theory, the current investigation tested for the contextual effects of adolescent peer groups on individuals' homophobic and social dominance attitudes. Results from multilevel models indicated that significant differences existed across peer groups on homophobic attitudes. In addition, these differences were accounted for on the basis of the hierarchy-enhancing or -attenuating climate of the group. A group socialization effect on individuals' social dominance attitudes over time was also observed. Furthermore, the social climate of the peer group moderated the stability of individuals' social dominance attitudes. Findings support the need to examine more proximal and informal group affiliations and earlier developmental periods in efforts to build more comprehensive theoretical models explaining when and how prejudiced and dominance attitudes are formed and the way in which they are perpetuated. (c) 2007 APA, all rights reserved.

New Developments in NOAA's Comprehensive Large Array-Data Stewardship System

NASA Astrophysics Data System (ADS)

Ritchey, N. A.; Morris, J. S.; Carter, D. J.

2012-12-01

The Comprehensive Large Array-data Stewardship System (CLASS) is part of the NOAA strategic goal of Climate Adaptation and Mitigation that gives focus to the building and sustaining of key observational assets and data archives critical to maintaining the global climate record. Since 2002, CLASS has been NOAA's enterprise solution for ingesting, storing and providing access to a host of near real-time remote sensing streams such as the Polar and Geostationary Operational Environmental Satellites (POES and GOES) and the Defense Meteorological Satellite Program (DMSP). Since October, 2011 CLASS has also been the dedicated Archive Data Segment (ADS) of the Suomi National Polar-orbiting Partnership (S-NPP). As the ADS, CLASS receives raw and processed S-NPP records for archival and distribution to the broad user community. Moving beyond just remote sensing and model data, NOAA has endorsed a plan to migrate all archive holdings from NOAA's National Data Centers into CLASS while retiring various disparate legacy data storage systems residing at the National Climatic Data Center (NCDC), National Geophysical Data Center (NGDC) and the National Oceanographic Data Center (NODC). In parallel to this data migration, CLASS is evolving to a service-oriented architecture utilizing cloud technologies for dissemination in addition to clearly defined interfaces that allow better collaboration with partners. This evolution will require implementation of standard access protocols and metadata which will lead to cost effective data and information preservation.

Ecohydrologic Changes due to Tree Expansion into Tundra in the Polar Urals, Russia

NASA Astrophysics Data System (ADS)

Ivanov, V. Y.; Wang, J.; El Sharif, H. A.; Liu, D.; Sheshukov, A. Y.; Mazepa, V.; Shiyatov, S.; Sokolov, A.

2017-12-01

The Arctic has been warming at an accelerating rate over the last several decades and the changing climate has caused the invasion of trees and shrubs into tundra across the polar regions of Alaska, Canada, and Russia. These vegetation changes may have the potential to impact regional hydrology and climate. This study aims to develop mechanistic and quantitative understanding of implications of forest encroachment into tundra. Specifically, for several areas with well-documented larch and spruce expansion in the Polar Urals and southern Yamal Peninsula of Russia over 1960-2010s, we hypothesize that the encroachment process alters the seasonality of energy budget characterized by enhanced total evapotranspiration and concomitant subsurface warming. We are collecting a comprehensive set of field observational data on micrometeorology, snow conditions, radiative fluxes, tree sap flows, soil temperature, moisture, and heat fluxes, and active layer thickness. A novel model of maximum entropy production (MEP) is used to derive the surface energy budgets as the partition of radiative fluxes into turbulent and conductive heat fluxes across the ecotone interface. We are presenting preliminary findings that illustrate the identified differences of seasonal snow and heat budget regimes for two contrasting sites: one of which has experienced a recent tree encroachment, while for the other this process has not yet occurred. Observed and modeled heat fluxes are used to inform a comprehensive physical model to study the impact of vegetation encroachment process on the permafrost dynamics.

The Feasibility of Avoiding Future Climate Impacts: Results from the AVOID Programmes

NASA Astrophysics Data System (ADS)

Lowe, J. A.; Warren, R.; Arnell, N.; Buckle, S.

2014-12-01

The AVOID programme and its successor, AVOID2, have focused on answering three core questions: how do we characterise potentially dangerous climate change and impacts, which emissions pathways can avoid at least some of these impacts, and how feasible are the future reductions needed to significantly deviate from a business-as-usual future emissions pathway. The first AVOID project succeeded in providing the UK Government with evidence to inform its position on climate change. A key part of the work involved developing a range of global emissions pathways and estimating and understanding the corresponding global impacts. This made use of a combination of complex general circulation models, simple climate models, pattern-scaling and state-of-the art impacts models. The results characterise the range of avoidable impacts across the globe in several key sectors including river and coastal flooding, cooling and heating energy demand, crop productivity and aspects of biodiversity. The avoided impacts between a scenario compatible with a 4ºC global warming and one with a 2ºC global warming were found to be highly sector dependent and avoided fractions typically ranged between 20% and 70%. A further key aspect was characterising the magnitude of the uncertainty involved, which is found to be very large in some impact sectors although the avoided fraction appears a more robust metric. The AVOID2 programme began in 2014 and will provide results in the run up to the Paris CoP in 2015. This includes new post-IPCC 5th assessment evidence to inform the long-term climate goal, a more comprehensive assessment of the uncertainty ranges of feasible emission pathways compatible with the long-term goal and enhanced estimates of global impacts using the latest generation of impact models and scenarios.

Warm climates of the past—a lesson for the future?

PubMed Central

Lunt, D. J.; Elderfield, H.; Pancost, R.; Ridgwell, A.; Foster, G. L.; Haywood, A.; Kiehl, J.; Sagoo, N.; Shields, C.; Stone, E. J.; Valdes, P.

2013-01-01

This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10–11 October 2011. The Discussion Meeting, entitled ‘Warm climates of the past: a lesson for the future?’, brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change. PMID:24043873

Warm climates of the past--a lesson for the future?

PubMed

Lunt, D J; Elderfield, H; Pancost, R; Ridgwell, A; Foster, G L; Haywood, A; Kiehl, J; Sagoo, N; Shields, C; Stone, E J; Valdes, P

2013-10-28

This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10-11 October 2011. The Discussion Meeting, entitled 'Warm climates of the past: a lesson for the future?', brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change.

Modular modeling system for building distributed hydrologic models with a user-friendly software package

NASA Astrophysics Data System (ADS)

Wi, S.; Ray, P. A.; Brown, C.

2015-12-01

A software package developed to facilitate building distributed hydrologic models in a modular modeling system is presented. The software package provides a user-friendly graphical user interface that eases its practical use in water resources-related research and practice. The modular modeling system organizes the options available to users when assembling models according to the stages of hydrological cycle, such as potential evapotranspiration, soil moisture accounting, and snow/glacier melting processes. The software is intended to be a comprehensive tool that simplifies the task of developing, calibrating, validating, and using hydrologic models through the inclusion of intelligent automation to minimize user effort, and reduce opportunities for error. Processes so far automated include the definition of system boundaries (i.e., watershed delineation), climate and geographical input generation, and parameter calibration. Built-in post-processing toolkits greatly improve the functionality of the software as a decision support tool for water resources system management and planning. Example post-processing toolkits enable streamflow simulation at ungauged sites with predefined model parameters, and perform climate change risk assessment by means of the decision scaling approach. The software is validated through application to watersheds representing a variety of hydrologic regimes.

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

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

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

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

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

DOE PAGES

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

2016-07-14

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Integrating environmental and genetic effects to predict responses of tree populations to climate.

PubMed

Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

2010-01-01

Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

Considerations in Managing the Fill Rate of the Grand Ethiopian Renaissance Dam Reservoir Using a System Dynamics Approach.

NASA Technical Reports Server (NTRS)

Keith, Bruce; Ford, David N.; Horton, Radley M.

2016-01-01

The purpose of this study is to evaluate simulated fill rate scenarios for the Grand Ethiopian Renaissance Dam while taking into account plausible climate change outcomes for the Nile River Basin. The region lacks a comprehensive equitable water resource management strategy, which creates regional security concerns and future possible conflicts. We employ climate estimates from 33 general circulation models within a system dynamics model as a step in moving toward a feasible regional water resource management strategy. We find that annual reservoir fill rates of 8-15% are capable of building hydroelectric capacity in Ethiopia while concurrently ensuring a minimum level of stream flow disruption into Egypt before 2039. Insofar as climate change estimates suggest a modest average increase in stream flow into the Aswan, climate changes through 2039 are unlikely to affect the fill rate policies. However, larger fill rates will have a more detrimental effect on stream flow into the Aswan, particularly beyond a policy of 15%. While this study demonstrates that a technical solution for reservoir fill rates is feasible, the corresponding policy challenge is political. Implementation of water resource management strategies in the Nile River Basin specifically and Africa generally will necessitate a national and regional willingness to cooperate.

Impact of volcanic eruptions on the climate of the 1st millennium AD in a comprehensive climate simulation

NASA Astrophysics Data System (ADS)

Wagner, Sebastian; Zorita, Eduardo

2015-04-01

The climate of the 1st millennium AD shows some remarkable differences compared to the last millennium concerning variation in external forcings. Together with an orbitally induced increased solar insolation during the northern hemisphere summer season and a general lack of strong solar minima, the frequency and intensity of large tropical and extratropical eruptions is decreased. Here we present results of a new climate simulation carried out with the comprehensive Earth System Model MPI-ESM-P forced with variations in orbital, solar, volcanic and greenhouse gas variations and land use changes for the last 2,100 years. The atmospheric model has a horizontal resolution of T63 (approx. 125x125 km) and therefore also allows investigations of regional-to-continental scale climatic phenomena. The volcanic forcing was reconstructed based on a publication by Sigl et al. (2013) using the sulfate records of the NEEM and WAIS ice cores. To obtain information on the aerosol optical depth (AOD) these sulfate records were scaled to an established reconstruction from Crowley and Unterman (2010), which is also a standard forcing in the framework of CMIP5/PMIP3. A comparison between the newly created data set with the Crowley and Unterman dataset reveals that the new reconstruction shows in general weaker intensities, especially of the large tropical outbreaks and fewer northern hemispheric small-to-medium scale eruptions. However, the general pattern in the overlapping period is similar. A hypothesis that can be tested with the simulation is whether the reduced volcanic intensity of the 1st millennium AD contributed to the elevated temperature levels over Europe, evident within a new proxy-based reconstruction. On the other hand, the few but large volcanic eruptions, e.g. the 528 AD event, also induced negative decadal-scale temperature anomalies. Another interesting result of the simulation relates to the 79 AD eruption of the Vesuvius, which caused the collapse of the city of Pompeii and its surroundings. Despite its severe local effects the eruption does not show a clear-cut hemispheric or global cooling. Therefore the simulation allows investigations on the effect of individual and clustered eruptions on the climate in the 1st millennium AD and its potential influence to human induced migration periods and decay of cultures in different regions.

Multiple greenhouse-gas feedbacks from the land biosphere under future climate change scenarios

NASA Astrophysics Data System (ADS)

Stocker, Benjamin D.; Roth, Raphael; Joos, Fortunat; Spahni, Renato; Steinacher, Marco; Zaehle, Soenke; Bouwman, Lex; Xu-Ri; Prentice, Iain Colin

2013-07-01

Atmospheric concentrations of the three important greenhouse gases (GHGs) CO2, CH4 and N2O are mediated by processes in the terrestrial biosphere that are sensitive to climate and CO2. This leads to feedbacks between climate and land and has contributed to the sharp rise in atmospheric GHG concentrations since pre-industrial times. Here, we apply a process-based model to reproduce the historical atmospheric N2O and CH4 budgets within their uncertainties and apply future scenarios for climate, land-use change and reactive nitrogen (Nr) inputs to investigate future GHG emissions and their feedbacks with climate in a consistent and comprehensive framework. Results suggest that in a business-as-usual scenario, terrestrial N2O and CH4 emissions increase by 80 and 45%, respectively, and the land becomes a net source of C by AD 2100. N2O and CH4 feedbacks imply an additional warming of 0.4-0.5°C by AD 2300; on top of 0.8-1.0°C caused by terrestrial carbon cycle and Albedo feedbacks. The land biosphere represents an increasingly positive feedback to anthropogenic climate change and amplifies equilibrium climate sensitivity by 22-27%. Strong mitigation limits the increase of terrestrial GHG emissions and prevents the land biosphere from acting as an increasingly strong amplifier to anthropogenic climate change.

Chicago, IL Adapts to Improve Extreme Heat Preparedness

EPA Pesticide Factsheets

Recognizing that heat waves are expected to increase in Chicago due to climate change,–supported by the Chicago Climate Impacts Report, the city adopted a comprehensive set of actions to reduce deaths from extreme heat events.

Protecting health from climate change in the WHO European Region.

PubMed

Wolf, Tanja; Martinez, Gerardo Sanchez; Cheong, Hae-Kwan; Williams, Eloise; Menne, Bettina

2014-06-16

"How far are we in implementing climate change and health action in the WHO European Region?" This was the question addressed to representatives of WHO European Member States of the working group on health in climate change (HIC). Twenty-two Member States provided answers to a comprehensive questionnaire that focused around eight thematic areas (Governance; Vulnerability, impact and adaptation (health) assessments; Adaptation strategies and action plans; Climate change mitigation; Strengthening health systems; Raising awareness and building capacity; Greening health services; and Sharing best practices). Strong areas of development are climate change vulnerability and impact assessments, as well as strengthening health systems and awareness raising. Areas where implementation would benefit from further action are the development of National Health Adaptation Plans, greening health systems, sharing best practice and reducing greenhouse gas emissions in other sectors. At the Parma Conference in 2010, the European Ministerial Commitment to Act on climate change and health and the European Regional Framework for Action to protect health from climate change were endorsed by fifty three European Member States. The results of this questionnaire are the most comprehensive assessment so far of the progress made by WHO European Member States to protecting public health from climate change since the agreements in Parma and the World Health Assembly Resolution in 2008.

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.

Warming increases the risk of civil war in Africa.

PubMed

Burke, Marshall B; Miguel, Edward; Satyanath, Shanker; Dykema, John A; Lobell, David B

2009-12-08

Armed conflict within nations has had disastrous humanitarian consequences throughout much of the world. Here we undertake the first comprehensive examination of the potential impact of global climate change on armed conflict in sub-Saharan Africa. We find strong historical linkages between civil war and temperature in Africa, with warmer years leading to significant increases in the likelihood of war. When combined with climate model projections of future temperature trends, this historical response to temperature suggests a roughly 54% increase in armed conflict incidence by 2030, or an additional 393,000 battle deaths if future wars are as deadly as recent wars. Our results suggest an urgent need to reform African governments' and foreign aid donors' policies to deal with rising temperatures.

Hydroclimate variability in Scandinavia over the last millennium - insights from a climate model-proxy data comparison

NASA Astrophysics Data System (ADS)

Seftigen, Kristina; Goosse, Hugues; Klein, Francois; Chen, Deliang

2017-12-01

The integration of climate proxy information with general circulation model (GCM) results offers considerable potential for deriving greater understanding of the mechanisms underlying climate variability, as well as unique opportunities for out-of-sample evaluations of model performance. In this study, we combine insights from a new tree-ring hydroclimate reconstruction from Scandinavia with projections from a suite of forced transient simulations of the last millennium and historical intervals from the CMIP5 and PMIP3 archives. Model simulations and proxy reconstruction data are found to broadly agree on the modes of atmospheric variability that produce droughts-pluvials in the region. Despite these dynamical similarities, large differences between simulated and reconstructed hydroclimate time series remain. We find that the GCM-simulated multi-decadal and/or longer hydroclimate variability is systematically smaller than the proxy-based estimates, whereas the dominance of GCM-simulated high-frequency components of variability is not reflected in the proxy record. Furthermore, the paleoclimate evidence indicates in-phase coherencies between regional hydroclimate and temperature on decadal timescales, i.e., sustained wet periods have often been concurrent with warm periods and vice versa. The CMIP5-PMIP3 archive suggests, however, out-of-phase coherencies between the two variables in the last millennium. The lack of adequate understanding of mechanisms linking temperature and moisture supply on longer timescales has serious implications for attribution and prediction of regional hydroclimate changes. Our findings stress the need for further paleoclimate data-model intercomparison efforts to expand our understanding of the dynamics of hydroclimate variability and change, to enhance our ability to evaluate climate models, and to provide a more comprehensive view of future drought and pluvial risks.

Coupled ice sheet - climate simulations of the last glacial inception and last glacial maximum with a model of intermediate complexity that includes a dynamical downscaling of heat and moisture

NASA Astrophysics Data System (ADS)

Quiquet, Aurélien; Roche, Didier M.

2017-04-01

Comprehensive fully coupled ice sheet - climate models allowing for multi-millenia transient simulations are becoming available. They represent powerful tools to investigate ice sheet - climate interactions during the repeated retreats and advances of continental ice sheets of the Pleistocene. However, in such models, most of the time, the spatial resolution of the ice sheet model is one order of magnitude lower than the one of the atmospheric model. As such, orography-induced precipitation is only poorly represented. In this work, we briefly present the most recent improvements of the ice sheet - climate coupling within the model of intermediate complexity iLOVECLIM. On the one hand, from the native atmospheric resolution (T21), we have included a dynamical downscaling of heat and moisture at the ice sheet model resolution (40 km x 40 km). This downscaling accounts for feedbacks of sub-grid precipitation on large scale energy and water budgets. From the sub-grid atmospheric variables, we compute an ice sheet surface mass balance required by the ice sheet model. On the other hand, we also explicitly use oceanic temperatures to compute sub-shelf melting at a given depth. Based on palaeo evidences for rate of change of eustatic sea level, we discuss the capability of our new model to correctly simulate the last glacial inception ( 116 kaBP) and the ice volume of the last glacial maximum ( 21 kaBP). We show that the model performs well in certain areas (e.g. Canadian archipelago) but some model biases are consistent over time periods (e.g. Kara-Barents sector). We explore various model sensitivities (e.g. initial state, vegetation, albedo) and we discuss the importance of the downscaling of precipitation for ice nucleation over elevated area and for the surface mass balance of larger ice sheets.

Extreme Weather Events and Interconnected Infrastructures: Toward More Comprehensive Climate Change Planning [Meeting challenges in understanding impacts of extreme weather events on connected infrastructures

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

Wilbanks, Thomas J.; Fernandez, Steven J.; Allen, Melissa R.

The President s Climate Change Action Plan calls for the development of better science, data, and tools for climate preparedness. Many of the current questions about preparedness for extreme weather events in coming decades are, however, difficult to answer with assets that have been developed by climate science to answer longer-term questions about climate change. Capacities for projecting exposures to climate-related extreme events, along with their implications for interconnected infrastructures, are now emerging.

Extreme Weather Events and Interconnected Infrastructures: Toward More Comprehensive Climate Change Planning [Meeting challenges in understanding impacts of extreme weather events on connected infrastructures

DOE PAGES

Wilbanks, Thomas J.; Fernandez, Steven J.; Allen, Melissa R.

2015-06-23

The President s Climate Change Action Plan calls for the development of better science, data, and tools for climate preparedness. Many of the current questions about preparedness for extreme weather events in coming decades are, however, difficult to answer with assets that have been developed by climate science to answer longer-term questions about climate change. Capacities for projecting exposures to climate-related extreme events, along with their implications for interconnected infrastructures, are now emerging.

Tapping into the Power of School Climate to Prevent Bullying: One Application of Schoolwide Positive Behavior Interventions and Supports

ERIC Educational Resources Information Center

Bosworth, Kris; Judkins, Maryann

2014-01-01

Preventing bullying requires a comprehensive approach that includes a focus on school climate. We review the climate features shown to reduce bullying, then illustrate how School-wide Positive Behavioral Interventions and Supports (SWPBIS) applies these principles in practice. SWPBIS, grounded in multiple theories--behaviorism, social learning…

Evidence and implications of recent and projected climate change in Alaska's forest ecosystems

Treesearch

Jane M. Wolken; Teresa N. Hollingsworth; T. Scott Rupp; F. Stuart Chapin; Sarah F. Trainor; Tara M. Barrett; Patrick F. Sullivan; A. David McGuire; Eugenie S. Euskirchen; Paul E. Hennon; Erik A. Beever; Jeff S. Conn; Lisa K. Crone; David V. A' More; Nancy Fresco; Thomas A. Hanley; Knut Kielland; James J. Kruse; Trista Patterson; Edward A.G. Schuur; David L. Verbyla; John Yarie

2011-01-01

The structure and function of Alaska's forests have changed significantly in response to a changing climate, including alterations in species composition and climate feedbacks (e.g., carbon, radiation budgets) that have important regional societal consequences and human feedbacks to forest ecosystems. In this paper we present the first comprehensive synthesis of...

Relationships among Student, Staff, and Administrative Measures of School Climate and Student Health and Academic Outcomes

ERIC Educational Resources Information Center

Gase, Lauren N.; Gomez, Louis M.; Kuo, Tony; Glenn, Beth A.; Inkelas, Moira; Ponce, Ninez A.

2017-01-01

Background: School climate is an integral part of a comprehensive approach to improving the well-being of students; however, little is known about the relationships between its different domains and measures. We examined the relationships between student, staff, and administrative measures of school climate to understand the extent to which they…

Effect of initial conditions of a catchment on seasonal streamflow prediction using ensemble streamflow prediction (ESP) technique for the Rangitata and Waitaki River basins on the South Island of New Zealand

NASA Astrophysics Data System (ADS)

Singh, Shailesh Kumar; Zammit, Christian; Hreinsson, Einar; Woods, Ross; Clark, Martyn; Hamlet, Alan

2013-04-01

Increased access to water is a key pillar of the New Zealand government plan for economic growths. Variable climatic conditions coupled with market drivers and increased demand on water resource result in critical decision made by water managers based on climate and streamflow forecast. Because many of these decisions have serious economic implications, accurate forecast of climate and streamflow are of paramount importance (eg irrigated agriculture and electricity generation). New Zealand currently does not have a centralized, comprehensive, and state-of-the-art system in place for providing operational seasonal to interannual streamflow forecasts to guide water resources management decisions. As a pilot effort, we implement and evaluate an experimental ensemble streamflow forecasting system for the Waitaki and Rangitata River basins on New Zealand's South Island using a hydrologic simulation model (TopNet) and the familiar ensemble streamflow prediction (ESP) paradigm for estimating forecast uncertainty. To provide a comprehensive database for evaluation of the forecasting system, first a set of retrospective model states simulated by the hydrologic model on the first day of each month were archived from 1972-2009. Then, using the hydrologic simulation model, each of these historical model states was paired with the retrospective temperature and precipitation time series from each historical water year to create a database of retrospective hindcasts. Using the resulting database, the relative importance of initial state variables (such as soil moisture and snowpack) as fundamental drivers of uncertainties in forecasts were evaluated for different seasons and lead times. The analysis indicate that the sensitivity of flow forecast to initial condition uncertainty is depend on the hydrological regime and season of forecast. However initial conditions do not have a large impact on seasonal flow uncertainties for snow dominated catchments. Further analysis indicates that this result is valid when the hindcast database is conditioned by ENSO classification. As a result hydrological forecasts based on ESP technique, where present initial conditions with histological forcing data are used may be plausible for New Zealand catchments.

Multidirectional abundance shifts among North American birds and the relative influence of multifaceted climate factors.

PubMed

Huang, Qiongyu; Sauer, John R; Dubayah, Ralph O

2017-09-01

Shifts in species distributions are major fingerprint of climate change. Examining changes in species abundance structures at a continental scale enables robust evaluation of climate change influences, but few studies have conducted these evaluations due to limited data and methodological constraints. In this study, we estimate temporal changes in abundance from North American Breeding Bird Survey data at the scale of physiographic strata to examine the relative influence of different components of climatic factors and evaluate the hypothesis that shifting species distributions are multidirectional in resident bird species in North America. We quantify the direction and velocity of the abundance shifts of 57 permanent resident birds over 44 years using a centroid analysis. For species with significant abundance shifts in the centroid analysis, we conduct a more intensive correlative analysis to identify climate components most strongly associated with composite change of abundance within strata. Our analysis focus on two contrasts: the relative importance of climate extremes vs. averages, and of temperature vs. precipitation in strength of association with abundance change. Our study shows that 36 species had significant abundance shifts over the study period. The average velocity of the centroid is 5.89 km·yr -1 . The shifted distance on average covers 259 km, 9% of range extent. Our results strongly suggest that the climate change fingerprint in studied avian distributions is multidirectional. Among 6 directions with significant abundance shifts, the northwestward shift was observed in the largest number of species (n = 13). The temperature/average climate model consistently has greater predictive ability than the precipitation/extreme climate model in explaining strata-level abundance change. Our study shows heterogeneous avian responses to recent environmental changes. It highlights needs for more species-specific approaches to examine contributing factors to recent distributional changes and for comprehensive conservation planning for climate change adaptation. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Evaluating Carbon and Climate Sensitivities of the NOAA/GFDL Earth System Model ESM2Mb to Forcing Perturbations during the Paleocene-Eocene Thermal Maximum

NASA Astrophysics Data System (ADS)

Tandy, H.; Shevliakova, E.; Keller, G.

2017-12-01

The Paleocene-Eocene Thermal Maximum (PETM, 55.5 Myr) was a period of rapid warming resulting from major changes in the carbon cycle and has been cited as the closest historical analogue to anthropogenic carbon release. Up to now, modeling studies of the PETM used either a low-resolution coupled model of the ocean and atmosphere with prescribed CO2 or CH4, or coupled climate-carbon models of intermediate complexity (i.e. simplified ocean or atmosphere). In this study we carried a suit of numerical experiments with the NOAA/GFDL comprehensive atmosphere-ocean coupled model with integrated terrestrial and marine carbon cycle components, known as an Earth System Model (ESM2Mb). We analyzed the output from millennia-scale ESM2Mb simulations with different combinations of forcings from the pre-PETM and PETM, including greenhouse gas concentrations and solar intensity. In addition we explore sensitivities of climate and carbon cycling to changes in geology such as topography, continental positions, and the presence and absence of large land glaciers. Furthermore, we examine ESM2Mb climate and carbon sensitivities to PETM conditions with a focus on how alternate conditions and forcings relate to the uncertainty in the climate and carbon cycling estimates from paleo observations. We explore changes in atmosphere, land, and ocean temperatures and circulation patterns as well as vegetation distribution, permafrost, and carbon storage in terrestrial and marine ecosystems from pre-PETM to PETM conditions. We found that with the present day land/sea mask and land glaciers in ESM2Mb, changes in only greenhouse gas concentrations (CO2 and CH4) from pre-PETM to PETM conditions induce global warming of 3-5 °C, consistent with the lower range of estimates from paleo proxies. Changes in the carbon permafrost storage from warming cannot explain the rapid increase in the atmospheric CO2 concentration. Changes in the ocean circulation and carbon storage critically depend on geological conditions such as continental positions. The study illustrates how models designed for studying future climate change can capture past paleo events, such as the PETM, and how modern day geological conditions may affect climate and carbon cycle sensitivities.

Regional climate modeling of heat stress, frost, and water stress events in the agricultural region of Southwest Western Australia under the current climate and future climate scenarios.

NASA Astrophysics Data System (ADS)

Kala, Jatin; Lyons, Tom J.; Abbs, Deborah J.; Foster, Ian J.

2010-05-01

Heat stress, frost, and water stress events have significant impacts on grain quality and production within the agricultural region (wheat-belt) of Southwest Western Australia (SWWA) (Cramb, 2000) and understanding how the frequency and intensity of these events will change in the future is crucial for management purposes. Hence, the Regional Atmospheric Modeling System (Pielke et al, 1992) (RAMS Version 6.0) is used to simulate the past 10 years of the climate of SWWA at a 20 km grid resolution by down-scaling the 6-hourly 1.0 by 1.0 degree National Center for Environmental Prediction Final Analyses from December 1999 to Present. Daily minimum and maximum temperatures, as well as daily rainfall are validated against observations. Simulations of future climate are carried out by down-scaling the Commonwealth Scientific and Industrial Research Organization (CSIRO) Mark 3.5 General Circulation Model (Gordon et al, 2002) for 10 years (2046-2055) under the SRES A2 scenario using the Cubic Conformal Atmospheric Model (CCAM) (McGregor and Dix, 2008). The 6-hourly CCAM output is then downscaled to a 20 km resolution using RAMS. Changes in extreme events are discussed within the context of the continued viability of agriculture in SWWA. Cramb, J. (2000) Climate in relation to agriculture in south-western Australia. In: The Wheat Book (Eds W. K. Anderson and J. R. Garlinge). Bulletin 4443. Department of Agriculture, Western Australia. Gordon, H. B., Rotstayn, L. D., McGregor, J. L., Dix, M. R., Kowalczyk, E. A., O'Farrell, S. P., Waterman, L. J., Hirst, A. C., Wilson, S. G., Collier, M. A., Watterson, I. G., and Elliott, T. I. (2002). The CSIRO Mk3 Climate System Model [Electronic publication]. Aspendale: CSIRO Atmospheric Research. (CSIRO Atmospheric Research technical paper; no. 60). 130 p McGregor, J. L., and Dix, M. R., (2008) An updated description of the conformal-cubic atmospheric model. High Resolution Simulation of the Atmosphere and Ocean, Hamilton, K. and Ohfuchi, W., Eds., Springer, 51-76. Pielke, R. A., Cotton, W. R., Walko, R. L., Tremback, C. J., Lyons, W. A., Grasso, L. D., Nicholls, M. E., Moran, M. D., Wesley, D. A., Lee, T. J., Copeland, J. H., (1992) A comprehensive meteorological modeling system - RAMS. Meteorol. Atmos. Phys., 49, 69-91.

Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

NASA Astrophysics Data System (ADS)

Sun, Shanlei; Sun, Ge; Cohen, Erika; McNulty, Steven G.; Caldwell, Peter V.; Duan, Kai; Zhang, Yang

2016-03-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, and ecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled climate data of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12-digit Hydrologic Unit Code level) in the coterminous US (CONUS). Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8° C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 gC m-2 yr-1 (9 %) increase in GPP. We found a large spatial variability in response to climate change across the CONUS 12-digit HUC watersheds, but in general, the majority would see consistent increases all variables evaluated. Over half of the watersheds, mostly found in the northeast and the southern part of the southwest, would see an increase in annual Q (> 100 mm yr-1 or 20 %). In addition, we also evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or two-digit HUCs. The study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results may be useful for policy-makers and land managers to formulate appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

Emissions versus climate change

EPA Science Inventory

Climate change is likely to offset some of the improvements in air quality expected from reductions in pollutant emissions. A comprehensive analysis of future air quality over North America suggests that, on balance, the air will still be cleaner in coming decades.

Cholera in Cameroon, 2000-2012: Spatial and Temporal Analysis at the Operational (Health District) and Sub Climate Levels.

PubMed

Ngwa, Moise C; Liang, Song; Kracalik, Ian T; Morris, Lillian; Blackburn, Jason K; Mbam, Leonard M; Ba Pouth, Simon Franky Baonga; Teboh, Andrew; Yang, Yang; Arabi, Mouhaman; Sugimoto, Jonathan D; Morris, John Glenn

2016-11-01

Recurrent cholera outbreaks have been reported in Cameroon since 1971. However, case fatality ratios remain high, and we do not have an optimal understanding of the epidemiology of the disease, due in part to the diversity of Cameroon's climate subzones and a lack of comprehensive data at the health district level. A unique health district level dataset of reported cholera case numbers and related deaths from 2000-2012, obtained from the Ministry of Public Health of Cameroon and World Health Organization (WHO) country office, served as the basis for the analysis. During this time period, 43,474 cholera cases were reported: 1748 were fatal (mean annual case fatality ratio of 7.9%), with an attack rate of 17.9 reported cases per 100,000 inhabitants per year. Outbreaks occurred in three waves during the 13-year time period, with the highest case fatality ratios at the beginning of each wave. Seasonal patterns of illness differed strikingly between climate subzones (Sudano-Sahelian, Tropical Humid, Guinea Equatorial, and Equatorial Monsoon). In the northern Sudano-Sahelian subzone, highest number of cases tended to occur during the rainy season (July-September). The southern Equatorial Monsoon subzone reported cases year-round, with the lowest numbers during peak rainfall (July-September). A spatial clustering analysis identified multiple clusters of high incidence health districts during 2010 and 2011, which were the 2 years with the highest annual attack rates. A spatiotemporal autoregressive Poisson regression model fit to the 2010-2011 data identified significant associations between the risk of transmission and several factors, including the presence of major waterbody or highway, as well as the average daily maximum temperature and the precipitation levels over the preceding two weeks. The direction and/or magnitude of these associations differed between climate subzones, which, in turn, differed from national estimates that ignored subzones differences in climate variables. The epidemiology of cholera in Cameroon differs substantially between climate subzones. Development of an optimal comprehensive country-wide control strategy for cholera requires an understanding of the impact of the natural and built environment on transmission patterns at the local level, particularly in the setting of ongoing climate change.

A Climate Information Platform for Copernicus (CLIPC): managing the data flood

NASA Astrophysics Data System (ADS)

Juckes, Martin; Swart, Rob; Bärring, Lars; Groot, Annemarie; Thysse, Peter; Som de Cerff, Wim; Costa, Luis; Lückenkötter, Johannes; Callaghan, Sarah; Bennett, Victoria

2016-04-01

The FP7 project "Climate Information Platform for Copernicus" (CLIPC) is developing a demonstration portal for the Copernicus Climate Change Service (C3S). The project confronts many problems associated with the huge diversity of underlying data, complex multi-layered uncertainties and extremely complex and evolving user requirements. The infrastructure is founded on a comprehensive approach to managing data and documentation, using global domain independent standards where possible. An extensive thesaurus of terms provides both a robust and flexible foundation for data discovery services and accessible definitions to support users. It is, of course, essential to provide information to users through an interface which reflects their expectations rather than the intricacies of abstract data models. CLIPC has reviewed user engagement activities from other collaborative European projects, conducted user polls, interviews and meetings and is now entering an evaluation phase in which users discuss new features and options in the portal design. The CLIPC portal will provide access to raw climate science data and climate impact indicators derived from that data. The portal needs the flexibility to support access to extremely large datasets as well as providing means to manipulate data and explore complex products interactively.

Persistence and diversification of the Holarctic shrew, Sorex tundrensis (Family Soricidae), in response to climate change

USGS Publications Warehouse

Hope, Andrew G.; Waltari, Eric; Fedorov, Vadim B.; Goropashnaya, Anna V.; Talbot, Sandra; Cook, Joseph A.

2011-01-01

Environmental processes govern demography, species movements, community turnover and diversification and yet in many respects these dynamics are still poorly understood at high latitudes. We investigate the combined effects of climate change and geography through time for a widespread Holarctic shrew, Sorex tundrensis. We include a comprehensive suite of closely related outgroup taxa and three independent loci to explore phylogeographic structure and historical demography. We then explore the implications of these findings for other members of boreal communities. The tundra shrew and its sister species, the Tien Shan shrew (Sorex asper), exhibit strong geographic population structure across Siberia and into Beringia illustrating local centres of endemism that correspond to Late Pleistocene refugia. Ecological niche predictions for both current and historical distributions indicate a model of persistence through time despite dramatic climate change. Species tree estimation under a coalescent process suggests that isolation between populations has been maintained across timeframes deeper than the periodicity of Pleistocene glacial cycling. That some species such as the tundra shrew have a history of persistence largely independent of changing climate, whereas other boreal species shifted their ranges in response to climate change, highlights the dynamic processes of community assembly at high latitudes.

Persistence and diversification of the Holarctic shrew, Sorex tundrensis (Family Soricidae), in response to climate change

USGS Publications Warehouse

Hope, Andrew G.; Waltari, Eric; Fedorov, V.B.; Goropashnaya, A.V.; Talbot, Sandra; Cook, Joseph A.

2014-01-01

Environmental processes govern demography, species movements, community turnover and diversification and yet in many respects these dynamics are still poorly understood at high latitudes. We investigate the combined effects of climate change and geography through time for a widespread Holarctic shrew, Sorex tundrensis. We include a comprehensive suite of closely related outgroup taxa and three independent loci to explore phylogeographic structure and historical demography. We then explore the implications of these findings for other members of boreal communities. The tundra shrew and its sister species, the Tien Shan shrew (Sorex asper), exhibit strong geographic population structure across Siberia and into Beringia illustrating local centres of endemism that correspond to Late Pleistocene refugia. Ecological niche predictions for both current and historical distributions indicate a model of persistence through time despite dramatic climate change. Species tree estimation under a coalescent process suggests that isolation between populations has been maintained across timeframes deeper than the periodicity of Pleistocene glacial cycling. That some species such as the tundra shrew have a history of persistence largely independent of changing climate, whereas other boreal species shifted their ranges in response to climate change, highlights the dynamic processes of community assembly at high latitudes.

Preparing Middle School Teachers to Use Science Models Effectively when Teaching about Weather and Climate Topics

NASA Astrophysics Data System (ADS)

Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.

2012-12-01

According to the National Science Education Standards (NSES), teachers are encouraged to use science models in the classroom as a way to aid in the understanding of the nature of the scientific process. This is of particular importance to the atmospheric science community because climate and weather models are very important when it comes to understanding current and future behaviors of our atmosphere. Although familiar with weather forecasts on television and the Internet, most people do not understand the process of using computer models to generate weather and climate forecasts. As a result, the public often misunderstands claims scientists make about their daily weather as well as the state of climate change. Therefore, it makes sense that recent research in science education indicates that scientific models and modeling should be a topic covered in K-12 classrooms as part of a comprehensive science curriculum. The purpose of this research study is to describe how three middle school teachers use science models to teach about topics in climate and weather, as well as the challenges they face incorporating models effectively into the classroom. Participants in this study took part in a week long professional development designed to orient them towards appropriate use of science models for a unit on weather, climate, and energy concepts. The course design was based on empirically tested features of effective professional development for science teachers and was aimed at teaching content to the teachers while simultaneously orienting them towards effective use of science models in the classroom in a way that both aids in learning about the content knowledge as well as how models are used in scientific inquiry. Results indicate that teachers perceive models to be physical representations that can be used as evidence to convince students that the teacher's conception of the concept is correct. Additionally, teachers tended to use them as ways to explain an idea to their students; they rarely discussed the idea that models are a representation of reality (as opposed to a replication of reality) and never discussed the predictive power of models and how they are used to further scientific knowledge. The results indicate that these teachers do not have a complete understanding of science models and the role they play in the scientific process. Therefore, the teachers struggled to incorporate modeling into the classroom in a way that aligns with what the NSES suggests. They tended to lean on models as "proof" of a particular concept rather than a representation of a concept. In actuality, scientists do not just use models to explain a concept, they also use them to make projections and as a way to improve our understanding the atmosphere. A possible consequence of teachers using models as "proof" of a concept is that students expect climate and forecast models to be concrete and exact, rather than tentative and representative. Increasing student understanding of climate and weather models is important to meet the needs of future STEM professionals, decision-makers, and the general populace to support rational decision-making about weather and the future of climate by an educated society.

Driving terrestrial ecosystem models from space

NASA Technical Reports Server (NTRS)

Waring, R. H.

1993-01-01

Regional air pollution, land-use conversion, and projected climate change all affect ecosystem processes at large scales. Changes in vegetation cover and growth dynamics can impact the functioning of ecosystems, carbon fluxes, and climate. As a result, there is a need to assess and monitor vegetation structure and function comprehensively at regional to global scales. To provide a test of our present understanding of how ecosystems operate at large scales we can compare model predictions of CO2, O2, and methane exchange with the atmosphere against regional measurements of interannual variation in the atmospheric concentration of these gases. Recent advances in remote sensing of the Earth's surface are beginning to provide methods for estimating important ecosystem variables at large scales. Ecologists attempting to generalize across landscapes have made extensive use of models and remote sensing technology. The success of such ventures is dependent on merging insights and expertise from two distinct fields. Ecologists must provide the understanding of how well models emulate important biological variables and their interactions; experts in remote sensing must provide the biophysical interpretation of complex optical reflectance and radar backscatter data.

Inversion Estimate of California Methane Emissions Using a Bayesian Inverse Model with Multi-Tower Greenhouse Gas Monitoring Network and Aircraft Measurements

NASA Astrophysics Data System (ADS)

Cui, Y.; Falk, M.; Chen, Y.; Herner, J.; Croes, B. E.; Vijayan, A.

2017-12-01

Methane (CH4) is an important short-lived climate pollutant (SLCP), and the second most important greenhouse gas (GHG) in California which accounts for 9% of the statewide GHG emissions inventory. Over the years, California has enacted several ambitious climate change mitigation goals, including the California Global Warming Solutions Act of 2006 which requires ARB to reduce statewide GHG emissions to 1990 emission level by 2020, as well as Assembly Bill 1383 which requires implementation of a climate mitigation program to reduce statewide methane emissions by 40% below the 2013 levels. In order to meet these requirements, ARB has proposed a comprehensive SLCP Strategy with goals to reduce oil and gas related emissions and capture methane emissions from dairy operations and organic waste. Achieving these goals will require accurate understanding of the sources of CH4 emissions. Since direct monitoring of CH4 emission sources in large spatial and temporal scales is challenging and resource intensive, we developed a complex inverse technique combined with atmospheric three-dimensional (3D) transport model and atmospheric observations of CH4 concentrations from a regional tower network and aircraft measurements, to gain insights into emission sources in California. In this study, develop a comprehensive inversion estimate using available aircraft measurements from CalNex airborne campaigns (May-June 2010) and three years of hourly continuous measurements from the ARB Statewide GHG Monitoring Network (2014-2016). The inversion analysis is conducted using two independent 3D Lagrangian models (WRF-STILT and WRF-FLEXPART), with a variety of bottom-up prior inputs from national and regional inventories, as well as two different probability density functions (Gaussian and Lognormal). Altogether, our analysis provides a detailed picture of the spatially resolved CH4 emission sources and their temporal variation over a multi-year period.

Effects of Vegetarian Nutrition–A Nutrition Ecological Perspective

PubMed Central

Metz, Martina; Hoffmann, Ingrid

2010-01-01

Although vegetarian nutrition is a complex issue, the multidimensionality and interrelatedness of its effects are rarely explored. This article aims to demonstrate the complexity of vegetarian nutrition by means of the nutrition ecological modeling technique NutriMod. The integrative qualitative cause-effect model, which is based on scientific literature, provides a comprehensive picture of vegetarian nutrition. The nutrition ecological perspective offers a basis for the assessment of the effects of worldwide developments concerning shifts in diets and the effects of vegetarian nutrition on global problems like climate change. Furthermore, new research areas on the complexity of vegetarian nutrition can be identified. PMID:22254037

Modelling Groundwater Depletion at Regional and Global Scales: Present State and Future Prospects.

NASA Technical Reports Server (NTRS)

Wada, Yoshihide

2015-01-01

Except for frozen water in ice and glaciers, groundwater is the world's largest distributed store of freshwater and has strategic importance to global food and water security. In this paper, the most recent advances quantifying groundwater depletion (GWD) are comprehensively reviewed. This paper critically evaluates the recently advanced modeling approaches estimating GWD at regional and global scales, and the evidence of feedbacks to the Earth system including sea-level rise associated with GWD. Finally, critical challenges and opportunities in the use of groundwater are identified for the adaption to growing food demand and uncertain climate.

Modeling Groundwater Depletion at Regional and Global Scales: Present State and Future Prospects

NASA Astrophysics Data System (ADS)

Wada, Yoshihide

2016-03-01

Except for frozen water in ice and glaciers, groundwater is the world's largest distributed store of freshwater and has strategic importance to global food and water security. In this paper, the most recent advances quantifying groundwater depletion (GWD) are comprehensively reviewed. This paper critically evaluates the recently advanced modeling approaches estimating GWD at regional and global scales, and the evidence of feedbacks to the Earth system including sea-level rise associated with GWD. Finally, critical challenges and opportunities in the use of groundwater are identified for the adaption to growing food demand and uncertain climate.

Now what do people know about global climate change? Survey studies of educated laypeople.

PubMed

Reynolds, Travis William; Bostrom, Ann; Read, Daniel; Morgan, M Granger

2010-10-01

In 1992, a mental-models-based survey in Pittsburgh, Pennsylvania, revealed that educated laypeople often conflated global climate change and stratospheric ozone depletion, and appeared relatively unaware of the role of anthropogenic carbon dioxide emissions in global warming. This study compares those survey results with 2009 data from a sample of similarly well-educated laypeople responding to the same survey instrument. Not surprisingly, following a decade of explosive attention to climate change in politics and in the mainstream media, survey respondents in 2009 showed higher awareness and comprehension of some climate change causes. Most notably, unlike those in 1992, 2009 respondents rarely mentioned ozone depletion as a cause of global warming. They were also far more likely to correctly volunteer energy use as a major cause of climate change; many in 2009 also cited natural processes and historical climatic cycles as key causes. When asked how to address the problem of climate change, while respondents in 1992 were unable to differentiate between general "good environmental practices" and actions specific to addressing climate change, respondents in 2009 have begun to appreciate the differences. Despite this, many individuals in 2009 still had incorrect beliefs about climate change, and still did not appear to fully appreciate key facts such as that global warming is primarily due to increased concentrations of carbon dioxide in the atmosphere, and the single most important source of this carbon dioxide is the combustion of fossil fuels. © 2010 Society for Risk Analysis.

Science Writers' Guide to TERRA

NASA Technical Reports Server (NTRS)

2000-01-01

The launch of NASA's Terra spacecraft marks a new era of comprehensive monitoring of the Earth's atmosphere, oceans, and continents from a single space-based platform. Data from the five Terra instruments will create continuous, long-term records of the state of the land, oceans, and atmosphere. Together with data from other satellite systems launched by NASA and other countries, Terra will inaugurate a new self-consistent data record that will be gathered over the next 15 years. The science objectives of NASAs Earth Observing System (EOS) program are to provide global observations and scientific understanding of land cover change and global productivity, climate variability and change, natural hazards, and atmospheric ozone. Observations by the Terra instruments will: provide the first global and seasonal measurements of the Earth system, including such critical functions as biological productivity of the land and oceans, snow and ice, surface temperature, clouds, water vapor, and land cover; improve our ability to detect human impacts on the Earth system and climate, identify the "fingerprint" of human activity on climate, and predict climate change by using the new global observations in climate models; help develop technologies for disaster prediction, characterization, and risk reduction from wildfires, volcanoes, floods, and droughts, and start long-term monitoring of global climate change and environmental change.

Dew point temperature affects ascospore release of allergenic genus Leptosphaeria

NASA Astrophysics Data System (ADS)

Sadyś, Magdalena; Kaczmarek, Joanna; Grinn-Gofron, Agnieszka; Rodinkova, Victoria; Prikhodko, Alex; Bilous, Elena; Strzelczak, Agnieszka; Herbert, Robert J.; Jedryczka, Malgorzata

2018-06-01

The genus Leptosphaeria contains numerous fungi that cause the symptoms of asthma and also parasitize wild and crop plants. In search of a robust and universal forecast model, the ascospore concentration in air was measured and weather data recorded from 1 March to 31 October between 2006 and 2012. The experiment was conducted in three European countries of the temperate climate, i.e., Ukraine, Poland, and the UK. Out of over 150 forecast models produced using artificial neural networks (ANNs) and multivariate regression trees (MRTs), we selected the best model for each site, as well as for joint two-site combinations. The performance of all computed models was tested against records from 1 year which had not been used for model construction. The statistical analysis of the fungal spore data was supported by a comprehensive study of both climate and land cover within a 30-km radius from the air sampler location. High-performance forecasting models were obtained for individual sites, showing that the local micro-climate plays a decisive role in biology of the fungi. Based on the previous epidemiological studies, we hypothesized that dew point temperature (DPT) would be a critical factor in the models. The impact of DPT was confirmed only by one of the final best neural models, but the MRT analyses, similarly to the Spearman's rank test, indicated the importance of DPT in all but one of the studied cases and in half of them ranked it as a fundamental factor. This work applies artificial neural modeling to predict the Leptosphaeria airborne spore concentration in urban areas for the first time.

Dew point temperature affects ascospore release of allergenic genus Leptosphaeria

NASA Astrophysics Data System (ADS)

Sadyś, Magdalena; Kaczmarek, Joanna; Grinn-Gofron, Agnieszka; Rodinkova, Victoria; Prikhodko, Alex; Bilous, Elena; Strzelczak, Agnieszka; Herbert, Robert J.; Jedryczka, Malgorzata

2018-01-01

The genus Leptosphaeria contains numerous fungi that cause the symptoms of asthma and also parasitize wild and crop plants. In search of a robust and universal forecast model, the ascospore concentration in air was measured and weather data recorded from 1 March to 31 October between 2006 and 2012. The experiment was conducted in three European countries of the temperate climate, i.e., Ukraine, Poland, and the UK. Out of over 150 forecast models produced using artificial neural networks (ANNs) and multivariate regression trees (MRTs), we selected the best model for each site, as well as for joint two-site combinations. The performance of all computed models was tested against records from 1 year which had not been used for model construction. The statistical analysis of the fungal spore data was supported by a comprehensive study of both climate and land cover within a 30-km radius from the air sampler location. High-performance forecasting models were obtained for individual sites, showing that the local micro-climate plays a decisive role in biology of the fungi. Based on the previous epidemiological studies, we hypothesized that dew point temperature (DPT) would be a critical factor in the models. The impact of DPT was confirmed only by one of the final best neural models, but the MRT analyses, similarly to the Spearman's rank test, indicated the importance of DPT in all but one of the studied cases and in half of them ranked it as a fundamental factor. This work applies artificial neural modeling to predict the Leptosphaeria airborne spore concentration in urban areas for the first time.

Dew point temperature affects ascospore release of allergenic genus Leptosphaeria.

PubMed

Sadyś, Magdalena; Kaczmarek, Joanna; Grinn-Gofron, Agnieszka; Rodinkova, Victoria; Prikhodko, Alex; Bilous, Elena; Strzelczak, Agnieszka; Herbert, Robert J; Jedryczka, Malgorzata

2018-06-01

The genus Leptosphaeria contains numerous fungi that cause the symptoms of asthma and also parasitize wild and crop plants. In search of a robust and universal forecast model, the ascospore concentration in air was measured and weather data recorded from 1 March to 31 October between 2006 and 2012. The experiment was conducted in three European countries of the temperate climate, i.e., Ukraine, Poland, and the UK. Out of over 150 forecast models produced using artificial neural networks (ANNs) and multivariate regression trees (MRTs), we selected the best model for each site, as well as for joint two-site combinations. The performance of all computed models was tested against records from 1 year which had not been used for model construction. The statistical analysis of the fungal spore data was supported by a comprehensive study of both climate and land cover within a 30-km radius from the air sampler location. High-performance forecasting models were obtained for individual sites, showing that the local micro-climate plays a decisive role in biology of the fungi. Based on the previous epidemiological studies, we hypothesized that dew point temperature (DPT) would be a critical factor in the models. The impact of DPT was confirmed only by one of the final best neural models, but the MRT analyses, similarly to the Spearman's rank test, indicated the importance of DPT in all but one of the studied cases and in half of them ranked it as a fundamental factor. This work applies artificial neural modeling to predict the Leptosphaeria airborne spore concentration in urban areas for the first time.

Expanded oxygen minimum zones during the late Paleocene-early Eocene: Hints from multiproxy comparison and ocean modeling

NASA Astrophysics Data System (ADS)

Zhou, X.; Thomas, E.; Winguth, A. M. E.; Ridgwell, A.; Scher, H.; Hoogakker, B. A. A.; Rickaby, R. E. M.; Lu, Z.

2016-12-01

Anthropogenic warming could well drive depletion of oceanic oxygen in the future. Important insight into the relationship between deoxygenation and warming can be gleaned from the geological record, but evidence is limited because few ocean oxygenation records are available for past greenhouse climate conditions. We use I/Ca in benthic foraminifera to reconstruct late Paleocene through early Eocene bottom and pore water redox conditions in the South Atlantic and Southern Indian Oceans and compare our results with those derived from Mn speciation and the Ce anomaly in fish teeth. We conclude that waters with lower oxygen concentrations were widespread at intermediate depths (1.5-2 km), whereas bottom waters were more oxygenated at the deepest site, in the Southeast Atlantic Ocean (>3 km). Epifaunal benthic foraminiferal I/Ca values were higher in the late Paleocene, especially at low-oxygen sites, than at well-oxygenated modern sites, indicating higher seawater total iodine concentrations in the late Paleocene than today. The proxy-based bottom water oxygenation pattern agrees with the site-to-site O2 gradient as simulated in a comprehensive climate model (Community Climate System Model Version 3), but the simulated absolute dissolved O2 values are low (< 35 µmol/kg), while higher O2 values ( 60-100 µmol/kg) were obtained in an Earth system model (Grid ENabled Integrated Earth system model). Multiproxy data together with improvements in boundary conditions and model parameterization are necessary if the details of past oceanographic oxygenation are to be resolved.

Recent advances in understanding secondary organic aerosol: Implications for global climate forcing: Advances in Secondary Organic Aerosol

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

Shrivastava, Manish; Cappa, Christopher D.; Fan, Jiwen

Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate modelsmore » typically do not comprehensively include all important processes. Our review summarizes some of the important developments during the past decade in understanding SOA formation. We also highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid-catalyzed multiphase chemistry of isoprene epoxydiols, particle-phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process-related interactions, so that these processes can be accurately represented in atmospheric chemistry-climate models.« less

Abrupt glacial climate shifts controlled by ice sheet changes.

PubMed

Zhang, Xu; Lohmann, Gerrit; Knorr, Gregor; Purcell, Conor

2014-08-21

During glacial periods of the Late Pleistocene, an abundance of proxy data demonstrates the existence of large and repeated millennial-scale warming episodes, known as Dansgaard-Oeschger (DO) events. This ubiquitous feature of rapid glacial climate change can be extended back as far as 800,000 years before present (BP) in the ice core record, and has drawn broad attention within the science and policy-making communities alike. Many studies have been dedicated to investigating the underlying causes of these changes, but no coherent mechanism has yet been identified. Here we show, by using a comprehensive fully coupled model, that gradual changes in the height of the Northern Hemisphere ice sheets (NHISs) can alter the coupled atmosphere-ocean system and cause rapid glacial climate shifts closely resembling DO events. The simulated global climate responses--including abrupt warming in the North Atlantic, a northward shift of the tropical rainbelts, and Southern Hemisphere cooling related to the bipolar seesaw--are generally consistent with empirical evidence. As a result of the coexistence of two glacial ocean circulation states at intermediate heights of the ice sheets, minor changes in the height of the NHISs and the amount of atmospheric CO2 can trigger the rapid climate transitions via a local positive atmosphere-ocean-sea-ice feedback in the North Atlantic. Our results, although based on a single model, thus provide a coherent concept for understanding the recorded millennial-scale variability and abrupt climate changes in the coupled atmosphere-ocean system, as well as their linkages to the volume of the intermediate ice sheets during glacials.

Recent advances in understanding secondary organic aerosol: Implications for global climate forcing: Advances in Secondary Organic Aerosol

DOE PAGES

Shrivastava, Manish; Cappa, Christopher D.; Fan, Jiwen; ...

2017-06-15

Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate modelsmore » typically do not comprehensively include all important processes. Our review summarizes some of the important developments during the past decade in understanding SOA formation. We also highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid-catalyzed multiphase chemistry of isoprene epoxydiols, particle-phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process-related interactions, so that these processes can be accurately represented in atmospheric chemistry-climate models.« less

The Upstream and Downstream impact of Milankovitch cycles in continental nonmarine sedimentary records

NASA Astrophysics Data System (ADS)

Valero, Luis; Garcés, Miguel; Huerta, Pedro; Cabrera, Lluís

2016-04-01

Discerning the effects of climate in the stratigraphic record is crucial for the comprehension of past climate changes. The signature of climate in sedimentary sequences is often assessed by the identification of Milankovitch cycles, as they can be recognized due to their (quasi) periodic behaviour. The integration of diverse stratigraphic disciplines is required in order to understand the different processes involved in the expression of the orbital cycles in the sedimentary records. New advances in Stratigraphy disclose the different variables that affect the sedimentation along the sediment routing systems. These variables can be summarized as the relationship between accommodation and sediment supply (AS/SS), because they account for the shifts of the total mass balance of a basin. Based in these indicators we propose a synthetic model for the understanding of the expression of climate in continental basins. Sedimentation in internally drained lake basins is particularly sensitive to net precipitation/evaporation variations. Rapid base level oscillations modify the AS/SS ratio sufficiently as to mask possible sediment flux variations associated to the changing discharge. On the other hand, basins lacking a central lacustrine system do not experience climatically-driven accommodation changes, and thus are more sensitive to archive sediment pulses. Small basins lacking carbonate facies are the ideal candidates to archive the impact of orbital forcing in the landscapes, as their small-scale sediment transfer systems are unable to buffer the upstream signal. Sedimentation models that include the relationship between accommodation and sediment supply, the effects of density and type of vegetation, and its coupled response with climate are needed to enhance their reliability.

Hydrodynamic evaluation of long term impacts of climate change and coastal effluents in the Arabian Gulf.

PubMed

Elhakeem, Abubaker; Elshorbagy, Walid

2015-12-30

A comprehensive basin wide hydrodynamic evaluation has been carried out to assess the long term impacts of climate change and coastal effluents on the salinity and seawater temperature of the Arabian Gulf (AG) using Delft3D-Flow model. The long term impacts of climate change scenarios A2 and B1 of the IPCC-AR4 on the AG hydrodynamics were evaluated. Using the current capacity and production rates of coastal desalination, power, and refinery plants, two projection scenarios until the year 2080 with 30 year intervals were developed namely the realistic and the optimistic discharge scenarios. Simulations of the individual climate change scenarios ascertained overall increase of the AG salinity and temperature and decrease of precipitation. The changes varied spatially with different scenarios as per the depth, proximity to exchange with ocean water, flushing, vertical mixing, and flow restriction. The individual tested scenarios of coastal projected discharges showed significant effects but within 10-20 km from the outfalls. Copyright © 2015 Elsevier Ltd. All rights reserved.

Past, Present and Future Distributions of an Iberian Endemic, Lepus granatensis: Ecological and Evolutionary Clues from Species Distribution Models

PubMed Central

Acevedo, Pelayo; Melo-Ferreira, José; Real, Raimundo; Alves, Paulo Célio

2012-01-01

The application of species distribution models (SDMs) in ecology and conservation biology is increasing and assuming an important role, mainly because they can be used to hindcast past and predict current and future species distributions. However, the accuracy of SDMs depends on the quality of the data and on appropriate theoretical frameworks. In this study, comprehensive data on the current distribution of the Iberian hare (Lepus granatensis) were used to i) determine the species’ ecogeographical constraints, ii) hindcast a climatic model for the last glacial maximum (LGM), relating it to inferences derived from molecular studies, and iii) calibrate a model to assess the species future distribution trends (up to 2080). Our results showed that the climatic factor (in its pure effect and when it is combined with the land-cover factor) is the most important descriptor of the current distribution of the Iberian hare. In addition, the model’s output was a reliable index of the local probability of species occurrence, which is a valuable tool to guide species management decisions and conservation planning. Climatic potential obtained for the LGM was combined with molecular data and the results suggest that several glacial refugia may have existed for the species within the major Iberian refugium. Finally, a high probability of occurrence of the Iberian hare in the current species range and a northward expansion were predicted for future. Given its current environmental envelope and evolutionary history, we discuss the macroecology of the Iberian hare and its sensitivity to climate change. PMID:23272115

Present and future connection of Asian-Pacific Oscillation to large-scale atmospheric circulations and East Asian rainfall: results of CMIP5

NASA Astrophysics Data System (ADS)

Zhou, Botao; Xu, Ying; Shi, Ying

2018-01-01

The summer Asian-Pacific oscillation (APO), one of the major modes of climate variability over the Asian-Pacific sector, has a pronounced effect on variations of large-scale atmospheric circulations and climate. This study evaluated the capability of 30 state-of-the-art climate models among the Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating its association with the atmospheric circulations over the Asian-Pacific region and the precipitation over East Asia. Furthermore, their future connections under the RCP8.5 scenario were examined. The evaluation results show that 5 out of 30 climate models can well capture the observed APO-related features in a comprehensive way, including the strengthened South Asian high (SAH), deepened North Pacific trough (NPT) and northward East Asian jet (EAJ) in the upper troposphere; an intensification of the Asian low and the North Pacific subtropical high (NPSH) as well as a northward shift of the western Pacific subtropical high (WPSH) in the lower troposphere; and a decrease in East Asian summer rainfall (EASR) under the positive APO phase. Based on the five CMIP5 models' simulations, the dynamic linkages of the APO to the SAH, NPT, AL, and NPSH are projected to maintain during the second half of the twenty-first century. However, its connection with the EASR tends to reduce significantly. Such a reduction might result from the weakening of the linkage of the APO to the meridional displacement of the EAJ and WPSH as a response to the warming scenario.

Climate Information and Misinformation: Getting the Message Out

NASA Astrophysics Data System (ADS)

Carr, M.; Rubenstein, M.; Brash, K.; Hernandez, T. E.; Anderson, R. F.; Fulton, M.; Kahn, B.

2010-12-01

While it is commonly accepted that improved science comprehension is a key element to informed decisions on the many societal issues that interface with science and technology, it is not always clear what that understanding should entail. Is it knowledge of a set of facts and their context, the ability to read scientific papers, familiarity with data sets and their strengths and limitations, the development of original research? Physical scientists continue to operate assuming the deficit model: that lack of societal engagement results from ignorance or lack of information. Yet, in the case of climate, an active community of citizen scientists is engaged in a parallel research activity that aims to audit the basic tenets of the field, thus illustrating that greater literacy does not necessarily lead to consensus. Communication experts have long noted the inadequacy of the deficit model, highlighting the importance of prior knowledge, interests, and values. Science communicators recommend direct public engagement using non-traditional tools and fora. Here we explore three modes of engaging the public on the theme of climate change skepticism: a report published by a major financial institution (following a deficit model, but targeting a highly educated non-science community), blogging (using the broad potential reach and ongoing engagement of the internet), and student discussion groups (taking a participatory 'community outreach' approach).

Simulation of the Indian Summer Monsoon Using Comprehensive Atmosphere-land Interactions, in the Absence of Two-way Air-sea Interactions

NASA Technical Reports Server (NTRS)

Lim, Young-Kwon; Shin, D. W.; Cocke, Steven; Kang, Sung-Dae; Kim, Hae-Dong

2011-01-01

Community Land Model version 2 (CLM2) as a comprehensive land surface model and a simple land surface model (SLM) were coupled to an atmospheric climate model to investigate the role of land surface processes in the development and the persistence of the South Asian summer monsoon. Two-way air-sea interactions were not considered in order to identify the reproducibility of the monsoon evolution by the comprehensive land model, which includes more realistic vertical soil moisture structures, vegetation and 2-way atmosphere-land interactions at hourly intervals. In the monsoon development phase (May and June). comprehensive land-surface treatment improves the representation of atmospheric circulations and the resulting convergence/divergence through the improvements in differential heating patterns and surface energy fluxes. Coupling with CLM2 also improves the timing and spatial distribution of rainfall maxima, reducing the seasonal rainfall overestimation by approx.60 % (1.8 mm/d for SLM, 0.7 mm/dI for CLM2). As for the interannual variation of the simulated rainfall, correlation coefficients of the Indian seasonal rainfall with observation increased from 0.21 (SLM) to 0.45 (CLM2). However, in the mature monsoon phase (July to September), coupling with the CLM2 does not exhibit a clear improvement. In contrast to the development phase, latent heat flux is underestimated and sensible heat flux and surface temperature over India are markedly overestimated. In addition, the moisture fluxes do not correlate well with lower-level atmospheric convergence, yielding correlation coefficients and root mean square errors worse than those produced by coupling with the SLM. A more realistic representation of the surface temperature and energy fluxes is needed to achieve an improved simulation for the mature monsoon period.

Simulating the Past, Present and Future of the Upper Troposphere and Lower Stratosphere

NASA Astrophysics Data System (ADS)

Gettelman, Andrew; Hegglin, Michaela

2010-05-01

A comprehensive assessment of coupled chemistry climate model (CCM) performance in the upper troposphere and lower stratosphere has been conducted with 18 models. Both qualitative and quantitative comparisons of model representation of UTLS dynamical, radiative and chemical structure have been conducted, using a collection of quantitative grading techniques. The models are able to reproduce the observed climatology of dynamical, radiative and chemical structure in the tropical and extratropical UTLS, despite relatively coarse vertical and horizontal resolution. Diagnostics of the Tropical Tropopause Layer (TTL), Tropopause Inversion Layer (TIL) and Extra-tropical Transition Layer (ExTL) are analyzed. The results provide new insight into the key processes that govern the dynamics and transport in the tropics and extra-tropicsa. The presentation will explain how models are able to reproduce key features of the UTLS, what features they do not reproduce, and why. Model trends over the historical period are also assessed and interannual variability is included in the metrics. Finally, key trends in the UTLS for the future with a given halogen and greenhouse gas scenario are presented, indicating significant changes in tropopause height and temperature, as well as UTLS ozone concentrations in the 21st century due to climate change and ozone recovery.

A Comprehensive Guide to Readers Theatre: Enhancing Fluency and Comprehension in Middle School and Beyond

ERIC Educational Resources Information Center

Black, Alison; Stave, Anna M.

2007-01-01

With the current education climate so focused on accountability, teachers need to ensure that their teaching practices are supported by today's content-specific standards. To meet this need, "A Comprehensive Guide to Readers Theatre" shows not only how to implement Readers Theatre in the classroom but also how to use it to meet current literacy…

The geographic distribution and economic value of climate change-related ozone health impacts in the United States in 2030.

PubMed

Fann, Neal; Nolte, Christopher G; Dolwick, Patrick; Spero, Tanya L; Brown, Amanda Curry; Phillips, Sharon; Anenberg, Susan

2015-05-01

In this United States-focused analysis we use outputs from two general circulation models (GCMs) driven by different greenhouse gas forcing scenarios as inputs to regional climate and chemical transport models to investigate potential changes in near-term U.S. air quality due to climate change. We conduct multiyear simulations to account for interannual variability and characterize the near-term influence of a changing climate on tropospheric ozone-related health impacts near the year 2030, which is a policy-relevant time frame that is subject to fewer uncertainties than other approaches employed in the literature. We adopt a 2030 emissions inventory that accounts for fully implementing anthropogenic emissions controls required by federal, state, and/or local policies, which is projected to strongly influence future ozone levels. We quantify a comprehensive suite of ozone-related mortality and morbidity impacts including emergency department visits, hospital admissions, acute respiratory symptoms, and lost school days, and estimate the economic value of these impacts. Both GCMs project average daily maximum temperature to increase by 1-4°C and 1-5 ppb increases in daily 8-hr maximum ozone at 2030, though each climate scenario produces ozone levels that vary greatly over space and time. We estimate tens to thousands of additional ozone-related premature deaths and illnesses per year for these two scenarios and calculate an economic burden of these health outcomes of hundreds of millions to tens of billions of U.S. dollars (2010$). Near-term changes to the climate have the potential to greatly affect ground-level ozone. Using a 2030 emission inventory with regional climate fields downscaled from two general circulation models, we project mean temperature increases of 1 to 4°C and climate-driven mean daily 8-hr maximum ozone increases of 1-5 ppb, though each climate scenario produces ozone levels that vary significantly over space and time. These increased ozone levels are estimated to result in tens to thousands of ozone-related premature deaths and illnesses per year and an economic burden of hundreds of millions to tens of billions of U.S. dollars (2010$).

Relationships among Safety Climate, Safety Behavior, and Safety Outcomes for Ethnic Minority Construction Workers.

PubMed

Lyu, Sainan; Hon, Carol K H; Chan, Albert P C; Wong, Francis K W; Javed, Arshad Ali

2018-03-09

In many countries, it is common practice to attract and employ ethnic minority (EM) or migrant workers in the construction industry. This primarily occurs in order to alleviate the labor shortage caused by an aging workforce with a lack of new entrants. Statistics show that EM construction workers are more likely to have occupational fatal and nonfatal injuries than their local counterparts; however, the mechanism underlying accidents and injuries in this vulnerable population has been rarely examined. This study aims to investigate relationships among safety climate, safety behavior, and safety outcomes for EM construction workers. To this end, a theoretical research model was developed based on a comprehensive review of the current literature. In total, 289 valid questionnaires were collected face-to-face from 223 Nepalese construction workers and 56 Pakistani construction workers working on 15 construction sites in Hong Kong. Structural equation modelling was employed to validate the constructs and test the hypothesized model. Results show that there were significant positive relationships between safety climate and safety behaviors, and significant negative relationships between safety behaviors and safety outcomes for EM construction workers. This research contributes to the literature regarding EM workers by providing empirical evidence of the mechanisms by which safety climate affects safety behaviors and outcomes. It also provides insights in order to help the key stakeholders formulate safety strategies for EM workers in many areas where numerous EM workers are employed, such as in the U.S., the UK, Australia, Singapore, Malaysia, and the Middle East.

Stratospheric Aerosol--Observations, Processes, and Impact on Climate

NASA Technical Reports Server (NTRS)

Kresmer, Stefanie; Thomason, Larry W.; von Hobe, Marc; Hermann, Markus; Deshler, Terry; Timmreck, Claudia; Toohey, Matthew; Stenke, Andrea; Schwarz, Joshua P.; Weigel, Ralf;

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

Li, Zhanqing; Lau, W. K. -M.; Ramanathan, V.

Asian monsoons and aerosols have been studied extensively which are intertwined in influencing the climate of Asia. This paper provides a comprehensive review of ample studies on Asian aerosol, monsoon and their interactions. The region is the primary source of aerosol emissions of varies species, influenced by distinct weather and climatic regimes. On continental scale, aerosols reduce surface insolation and weaken the land-ocean thermal contrast, thus inhibiting the development of monsoons. Locally, aerosol radiative effects alter the thermodynamic stability and convective potential of the lower atmosphere leading to reduced temperatures, increased atmospheric stability, and weakened wind and atmospheric circulation. Themore » atmospheric thermodynamic state may also be altered by the aerosol serving as cloud condensation nuclei or ice nuclei. Many mechanisms have been put forth regarding how aerosols modulate the amplitude, frequency, intensity, and phase of numerous monsoon climate variables. A wide range of theoretical, observational, and modeling findings on the Asian monsoon, aerosols, and their interactions are synthesized. A new paradigm is proposed on investigating aerosol-monsoon interactions, in which natural aerosols such as desert dust, black carbon from biomass burning, and biogenic aerosols from vegetation are considered integral components of an intrinsic aerosol-monsoon climate system, subject to external forcings of global warming, anthropogenic aerosols, and land use and change. Future research on aerosol-monsoon interactions calls for an integrated approach and international collaborations based on long-term sustained observations, process measurements, and improved models, as well as using observations to constrain model simulations and projections.« less

Pacific Islands Regional Climate Assessment: Building a Framework to Track Physical and Social Indicators of Climate Change Across Pacific Islands

NASA Astrophysics Data System (ADS)

Grecni, Z. N.; Keener, V. W.

2016-12-01

Assessments inform regional and local climate change governance and provide the critical scientific basis for U.S. climate policy. Despite the centrality of scientific information to public discourse and decision making, comprehensive assessments of climate change drivers, impacts, and the vulnerability of human and ecological systems at regional or local scales are often conducted on an ad hoc basis. Methods for sustained assessment and communication of scientific information are diverse and nascent. The Pacific Islands Regional Climate Assessment (PIRCA) is a collaborative effort to assess climate change indicators, impacts, and adaptive capacity of the Hawaiian archipelago and the US-Affiliated Pacific Islands (USAPI). In 2012, PIRCA released the first comprehensive report summarizing the state of scientific knowledge about climate change in the region as a technical input to the U.S. National Climate Assessment. A multi-method evaluation of PIRCA outputs and delivery revealed that the vast majority of key stakeholders view the report as extremely credible and use it as a resource. The current study will present PIRCA's approach to establishing physical and social indicators to track on an ongoing basis, starting with the Republic of the Marshall Islands as an initial location of focus for providing a cross-sectoral indicators framework. Identifying and tracking useful indicators is aimed at sustaining the process of knowledge coproduction with decision makers who seek to better understand the climate variability and change and its impacts on Pacific Island communities.

Large-scale, high-performance and cloud-enabled multi-model analytics experiments in the context of the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Fiore, S.; Płóciennik, M.; Doutriaux, C.; Blanquer, I.; Barbera, R.; Williams, D. N.; Anantharaj, V. G.; Evans, B. J. K.; Salomoni, D.; Aloisio, G.

2017-12-01

The increased models resolution in the development of comprehensive Earth System Models is rapidly leading to very large climate simulations output that pose significant scientific data management challenges in terms of data sharing, processing, analysis, visualization, preservation, curation, and archiving.Large scale global experiments for Climate Model Intercomparison Projects (CMIP) have led to the development of the Earth System Grid Federation (ESGF), a federated data infrastructure which has been serving the CMIP5 experiment, providing access to 2PB of data for the IPCC Assessment Reports. In such a context, running a multi-model data analysis experiment is very challenging, as it requires the availability of a large amount of data related to multiple climate models simulations and scientific data management tools for large-scale data analytics. To address these challenges, a case study on climate models intercomparison data analysis has been defined and implemented in the context of the EU H2020 INDIGO-DataCloud project. The case study has been tested and validated on CMIP5 datasets, in the context of a large scale, international testbed involving several ESGF sites (LLNL, ORNL and CMCC), one orchestrator site (PSNC) and one more hosting INDIGO PaaS services (UPV). Additional ESGF sites, such as NCI (Australia) and a couple more in Europe, are also joining the testbed. The added value of the proposed solution is summarized in the following: it implements a server-side paradigm which limits data movement; it relies on a High-Performance Data Analytics (HPDA) stack to address performance; it exploits the INDIGO PaaS layer to support flexible, dynamic and automated deployment of software components; it provides user-friendly web access based on the INDIGO Future Gateway; and finally it integrates, complements and extends the support currently available through ESGF. Overall it provides a new "tool" for climate scientists to run multi-model experiments. At the time this contribution is being written, the proposed testbed represents the first implementation of a distributed large-scale, multi-model experiment in the ESGF/CMIP context, joining together server-side approaches for scientific data analysis, HPDA frameworks, end-to-end workflow management, and cloud computing.

A satellite simulator for TRMM PR applied to climate model simulations

NASA Astrophysics Data System (ADS)

Spangehl, T.; Schroeder, M.; Bodas-Salcedo, A.; Hollmann, R.; Riley Dellaripa, E. M.; Schumacher, C.

2017-12-01

Climate model simulations have to be compared against observation based datasets in order to assess their skill in representing precipitation characteristics. Here we use a satellite simulator for TRMM PR in order to evaluate simulations performed with MPI-ESM (Earth system model of the Max Planck Institute for Meteorology in Hamburg, Germany) performed within the MiKlip project (https://www.fona-miklip.de/, funded by Federal Ministry of Education and Research in Germany). While classical evaluation methods focus on geophysical parameters such as precipitation amounts, the application of the satellite simulator enables an evaluation in the instrument's parameter space thereby reducing uncertainties on the reference side. The CFMIP Observation Simulator Package (COSP) provides a framework for the application of satellite simulators to climate model simulations. The approach requires the introduction of sub-grid cloud and precipitation variability. Radar reflectivities are obtained by applying Mie theory, with the microphysical assumptions being chosen to match the atmosphere component of MPI-ESM (ECHAM6). The results are found to be sensitive to the methods used to distribute the convective precipitation over the sub-grid boxes. Simple parameterization methods are used to introduce sub-grid variability of convective clouds and precipitation. In order to constrain uncertainties a comprehensive comparison with sub-grid scale convective precipitation variability which is deduced from TRMM PR observations is carried out.

Applying a Systems Approach to Monitoring and Assessing Climate Change Mitigation Potential in Mexico's Forest Sector

NASA Astrophysics Data System (ADS)

Olguin-Alvarez, M. I.; Wayson, C.; Fellows, M.; Birdsey, R.; Smyth, C.; Magnan, M.; Dugan, A.; Mascorro, V.; Alanís, A.; Serrano, E.; Kurz, W. A.

2017-12-01

Since 2012, the Mexican government through its National Forestry Commission, with support from the Commission for Environmental Cooperation, the Forest Services of Canada and USA, the SilvaCarbon Program and research institutes in Mexico, has made important progress towards the use of carbon dynamics models ("gain-loss" approach) for greenhouse gas (GHG) emissions monitoring and projections into the future. Here we assess the biophysical mitigation potential of policy alternatives identified by the Mexican Government (e.g. net zero deforestation rate, sustainable forest management) based on a systems approach that models carbon dynamics in forest ecosystems, harvested wood products and substitution benefits in two contrasting states of Mexico. We provide key messages and results derived from the use of the Carbon Budget Model of the Canadian Forest Sector and a harvested wood products model, parameterized with input data from Mexicós National Forest Monitoring System (e.g. forest inventories, remote sensing, disturbance data). The ultimate goal of this tri-national effort is to develop data and tools for carbon assessment in strategic landscapes in North America, emphasizing the need to include multiple sectors and types of collaborators (scientific and policy-maker communities) to design more comprehensive portfolios for climate change mitigation in accordance with the Paris Agreement of the United Nation Framework Convention on Climate Change (e.g. Mid-Century Strategy, NDC goals).

Role of the U.S. Forest Service: Helping forests, grasslands, and wildlife adapt to shifts in climate

Treesearch

Monica S. Tomosy; Frank R. Thompson; Douglas Boyce

2011-01-01

This fall, the U.S. Forest Service (USFS) will release a comprehensive new guidebook designed to help managers develop climate adaptation options for National Forests (Peterson et al. 2011, in press). The adaptation process is based on partnerships between local resource managers and scientists working collaboratively to understand potential climate change effects,...

Educator Effectiveness Series: Assessing School Climate. Q&A with Jonathan Cohen, Ph.D. REL Mid-Atlantic Webinar

ERIC Educational Resources Information Center

Cohen, Jonathan

2015-01-01

The REL Mid-Atlantic Webinar discussed the elements in a positive school climate and shared different methods for assessing school data, including the Comprehensive School Climate Inventory. The Q&A presented in this document address the questions participants had for Dr. Cohen following the webinar. The webinar recording and PowerPoint…

The Coupled Mars Dust and Water Cycles: Understanding How Clouds Affect the Vertical Distribution and Meridional Transport of Dust and Water.

NASA Technical Reports Server (NTRS)

Kahre, M. A.

2015-01-01

The dust and water cycles are crucial to the current Martian climate, and they are coupled through cloud formation. Dust strongly impacts the thermal structure of the atmosphere and thus greatly affects atmospheric circulation, while clouds provide radiative forcing and control the hemispheric exchange of water through the modification of the vertical distributions of water and dust. Recent improvements in the quality and sophistication of both observations and climate models allow for a more comprehensive understanding of how the interaction between the dust and water cycles (through cloud formation) affects the dust and water cycles individually. We focus here on the effects of clouds on the vertical distribution of dust and water, and how those vertical distributions control the net meridional transport of water. For this study, we utilize observations of temperature, dust and water ice from the Mars Climate Sounder (MCS) on the Mars Reconnaissance Orbiter (MRO) combined with the NASA ARC Mars Global Climate Model (MGCM). We demonstrate that the magnitude and nature of the net meridional transport of water between the northern and southern hemispheres during NH summer is sensitive to the vertical structure of the simulated aphelion cloud belt. We further examine how clouds influence the atmospheric thermal structure and thus the vertical structure of the cloud belt. Our goal is to identify and understand the importance of radiative/dynamic feedbacks due to the physical processes involved with cloud formation and evolution on the current climate of Mars.

Climate change impact on the discharge in meso-scale catchments and consequences for the hydropower-production in Switzerland

NASA Astrophysics Data System (ADS)

Rössler, Ole; Hänggi, Pascal; Köplin, Nina; Meyer, Rapahel; Schädler, Bruno; Weingartner, Rolf

2013-04-01

The potential effect of climate change on hydrology is the acceleration of the hydrological cycle that in turn will likely cause changes in the discharge regime. As a result, socio-economic systems (e.g., tourism, hydropower industry) may be drastically affected. In this study, we comprehensively analyzed the effect of climate change on different hydrological components like mean and low-flow levels, and drought stress in mesoscale catchments of Switzerland. In terms of mean flows approx. 200 catchments in Switzerland were simulated for the reference period 1984-2005 using the hydrological model PREVAH and projection for near (2025-2046) and far future (2074-2095) are based on delta-change values of 10 ENSEMBLES regional climate models assuming A1B emission scenario (CH2011 climate scenario data sets). We found seven distinct response types of catchments, each exhibiting a characteristic annual cycle of hydrologic change. A general pattern observed for all catchments, is the clearly decreasing summer runoff. Hence, within a second analysis of future discharge a special focus was set on summer low flow in a selection of 29 catchments in the Swiss Midlands. Low flows are critical as they have great implications on water usage and biodiversity. We re-calibrated the hydrological model PREVAH with a focus on base-flow and gauged discharge and used the aforementioned climate data sets and simulation time periods. We found low flow situations to be very likely to increase in both, magnitude and duration, especially in central and western Switzerland plateau. At third, the drought stress potential was analyzed by simulating the soil moisture level under climate change conditions in a high mountain catchment. We used the distributed hydrological model WaSiM-ETH for this aspect as soil characteristics are much better represented in this model. Soil moisture in forests below 2000 m a.s.l. were found to be affected at most, which might have implication to their function as avalanche protection forests. However, we found high uncertainties related to the downscaling method applied. Finally, we analyzed the effect of changed discharge characteristics on the hydropower production by coupling the hydrological model BERNHYDRO with a hydropower management model. For the near future (until 2050), the results indicate that losses in the hydropower production during the summer can be compensated by benefit during winter. These different aspects of climate change impacts on the hydrosphere reveal a differentiated picture involving potentially threatened and widely unaffected catchments, hydrologic parameters and hydrologic constraints to the society.

SAO and Kelvin Waves in the EuroGRIPS GCMS and the UK Meteorological Offices Analyses

NASA Technical Reports Server (NTRS)

Amodei, M.; Pawson, S.; Scaife, A. A.; Lahoz, W.; Langematz, U.; Li, Ding Min; Simon, P.

2000-01-01

This work is an intercomparison of four tropospheric-stratospheric climate models, the Unified Model (UM) of the U.K. Meteorological Office (UKMO), the model of the Free University in Berlin (FUB). the ARPEGE-climat model of the National Center for Meteorological Research (CNRM), and the Extended UGAMP GCM (EUGCM) of the Center for Global Atmospheric Modelling (CGAM), against the UKMO analyses. This comparison has been made in the framework of the "GSM-Reality Intercomparison Project for SPARC" (GRIPS). SPARC (Stratospheric Processes and their Role in Climate) aims are to investigate the effects of the middle atmosphere on climate and the GRIPS purpose is to organized a comprehensive assessment of current Middle Atmosphere-Climate Models (MACMs). The models integrations were made without identical contraints e.g. boundary conditions, incoming solar radiation). All models are able to represent the dominant features of the extratropical circulation. In this paper, the structure of the tropical winds and the strengths of the Kelvin waves are examined. Explanations for the differences exhibited. between the models. as well as between models and analyses, are also proposed. In the analyses a rich spectrum of waves (eastward and westward) is present and contributes to drive the SAO (SemiAnnual Oscillation) and the QBO (Quasi-Biennal Oscillation). The amplitude of the Kelvin waves is close to the one observed in UARS (Upper Atmosphere Research Satellite) data. In agreement with observations, the Kelvin waves generated in the models propagate into the middle atmosphere as wave packets which underlines convective forcing origin. In most models, slow Kelvin waves propagate too high and are hence overestimated in the upper stratosphere and in the mesosphere, except for the UM which is more diffusive. These waves are not sufficient to force realistic westerlies of the QBO or SAO westerly phases. If the SAO is represented by all models only two of them are able to generate westerlies between 10 hPa and 50 hPa. The importance of the role played by subgrided gravity waves is more and more recognized. Actually, the EUGCM which includes a parametrization of gravity waves with a non-zero phase speed is able to simulate. with however some unrealistic features, clear easterly to westerly transitions as well as westerlies downward propagations. Thermal damping is also important in the westerlies forcing in the stratosphere. The model ARPEGE-climat shows more westerlies in the stratosphere than tile other three models probably due to the use of a simplified scheme to predict the ozone distribution in the middle atmosphere.

The evaluation of basin water resources utilization efficiency based on Chaos projection mode

NASA Astrophysics Data System (ADS)

Guan, X.; Liang, S.; Meng, Y.; Wang, H.

2017-12-01

To promote the coordinated development of a healthy economy, society, and environment, and the sustainable development of water resources comprehensive utilization efficiency (WRCUE), this study investigated appropriate indicators using the trapezoidal fuzzy number method, and constructed an evaluation index system for WRCUE. A WRCUE evaluation model is applied to the areas in the Yellow River Basin in China using a genetic projection pursuit method. The comprehensive evaluation index system of water use efficiency includes 6 indicators: Water consumption per unit industrial value added, water consumption per unit GDP, eliminate the climate effect on agricultural water use efficiency, irrigation water consumption per unit area, domestic water use per capita and industrial water ratio. Then, multiple indexes in the index system are transformed to a comprehensive index by the combined model, which is used to represent the total water resources utilization efficiency. Results show that the WRCUE in Yellow River basin and the provinces have a great distance. WRCUE is well developed in Shanxi, Shandong, and Henan provinces, moderately developed in Shaanxi, Inner Mongolia, and Sichuan provinces, and poorly developed in the Ningxia Autonomous Region, Gansu Province, and Qinghai Province. According to the capacities of provinces, related measures are proposed.

Predictability of the summer East Asian upper-tropospheric westerly jet in ENSEMBLES multi-model forecasts

NASA Astrophysics Data System (ADS)

Li, Chaofan; Lin, Zhongda

2015-12-01

The interannual variation of the East Asian upper-tropospheric westerly jet (EAJ) significantly affects East Asian climate in summer. Identifying its performance in model prediction may provide us another viewpoint, from the perspective of upper-tropospheric circulation, to understand the predictability of summer climate anomalies in East Asia. This study presents a comprehensive assessment of year-to-year variability of the EAJ based on retrospective seasonal forecasts, initiated from 1 May, in the five state-of-the-art coupled models from ENSEMBLES during 1960-2005. It is found that the coupled models show certain capability in describing the interannual meridional displacement of the EAJ, which reflects the models' performance in the first leading empirical orthogonal function (EOF) mode. This capability is mainly shown over the region south of the EAJ axis. Additionally, the models generally capture well the main features of atmospheric circulation and SST anomalies related to the interannual meridional displacement of the EAJ. Further analysis suggests that the predicted warm SST anomalies in the concurrent summer over the tropical eastern Pacific and northern Indian Ocean are the two main sources of the potential prediction skill of the southward shift of the EAJ. In contrast, the models are powerless in describing the variation over the region north of the EAJ axis, associated with the meridional displacement, and interannual intensity change of the EAJ, the second leading EOF mode, meaning it still remains a challenge to better predict the EAJ and, subsequently, summer climate in East Asia, using current coupled models.

North American extreme temperature events and related large scale meteorological patterns: A review of statistical methods, dynamics, modeling, and trends

DOE PAGES

Grotjahn, Richard; Black, Robert; Leung, Ruby; ...

2015-05-22

This paper reviews research approaches and open questions regarding data, statistical analyses, dynamics, modeling efforts, and trends in relation to temperature extremes. Our specific focus is upon extreme events of short duration (roughly less than 5 days) that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). Methods used to define extreme events statistics and to identify and connect LSMPs to extreme temperatures are presented. Recent advances in statistical techniques can connect LSMPs to extreme temperatures through appropriately defined covariates that supplements more straightforward analyses. A wide array of LSMPs, ranging from synoptic tomore » planetary scale phenomena, have been implicated as contributors to extreme temperature events. Current knowledge about the physical nature of these contributions and the dynamical mechanisms leading to the implicated LSMPs is incomplete. There is a pressing need for (a) systematic study of the physics of LSMPs life cycles and (b) comprehensive model assessment of LSMP-extreme temperature event linkages and LSMP behavior. Generally, climate models capture the observed heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreaks frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Climate models have been used to investigate past changes and project future trends in extreme temperatures. Overall, modeling studies have identified important mechanisms such as the effects of large-scale circulation anomalies and land-atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs more specifically to understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated so more research is needed to understand the limitations of climate models and improve model skill in simulating extreme temperatures and their associated LSMPs. Furthermore, the paper concludes with unresolved issues and research questions.« less

The DACCIWA model evaluation project: representation of the meteorology of southern West Africa in state-of-the-art weather, seasonal and climate prediction models

NASA Astrophysics Data System (ADS)

Kniffka, Anke; Benedetti, Angela; Knippertz, Peter; Stanelle, Tanja; Brooks, Malcolm; Deetz, Konrad; Maranan, Marlon; Rosenberg, Philip; Pante, Gregor; Allan, Richard; Hill, Peter; Adler, Bianca; Fink, Andreas; Kalthoff, Norbert; Chiu, Christine; Vogel, Bernhard; Field, Paul; Marsham, John

2017-04-01

DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) is an EU-funded project that aims to determine the influence of anthropogenic and natural emissions on the atmospheric composition, air quality, weather and climate over southern West Africa. DACCIWA organised a major international field campaign in June-July 2016 and involves a wide range of modelling activities. Here we report about the coordinated model evaluation performed in the framework of DACCIWA focusing on meteorological fields. This activity consists of two elements: (a) the quality of numerical weather prediction during the field campaign, (b) the ability of seasonal and climate models to represent the mean state and its variability. For the first element, the extensive observations from the main field campaign in West Africa in June-July 2016 (ground supersites, radiosondes, aircraft measurements) will be combined with conventional data (synoptic stations, satellites data from various sensors) to evaluate models against. The forecasts include operational products from centres such as the ECMWF, UK MetOffice and the German Weather Service and runs specifically conducted for the planning and the post-analysis of the field campaign using higher resolutions (e.g., WRF, COSMO). The forecast and the observations are analysed in a concerted way to assess the ability of the models to represent the southern West African weather systems and secondly to provide a comprehensive synoptic overview of the state of the atmosphere. In a second step the process will be extended to long-term modelling periods. This includes both seasonal and climate models, respectively. In this case, the observational dataset contains long-term satellite observations and station data, some of which were digitised from written records in the framework of DACCIWA. Parameter choice and spatial averaging will build directly on the weather forecasting evaluation to allow an assessment of the impact of short-term errors on long-term simulations.

Temperature and Humidity Profiles in the TqJoint Data Group of AIRS Version 6 Product for the Climate Model Evaluation

NASA Technical Reports Server (NTRS)

Ding, Feng; Fang, Fan; Hearty, Thomas J.; Theobald, Michael; Vollmer, Bruce; Lynnes, Christopher

2014-01-01

The Atmospheric Infrared Sounder (AIRS) mission is entering its 13th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing long-wave radiation, cloud properties, and trace gases. Thus AIRS data have been widely used, among other things, for short-term climate research and observational component for model evaluation. One instance is the fifth phase of the Coupled Model Intercomparison Project (CMIP5) which uses AIRS version 5 data in the climate model evaluation. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for data from the AIRS mission. The GES DISC, in collaboration with the AIRS Project, released data from the version 6 algorithm in early 2013. The new algorithm represents a significant improvement over previous versions in terms of greater stability, yield, and quality of products. The ongoing Earth System Grid for next generation climate model research project, a collaborative effort of GES DISC and NASA JPL, will bring temperature and humidity profiles from AIRS version 6. The AIRS version 6 product adds a new "TqJoint" data group, which contains data for a common set of observations across water vapor and temperature at all atmospheric levels and is suitable for climate process studies. How different may the monthly temperature and humidity profiles in "TqJoint" group be from the "Standard" group where temperature and water vapor are not always valid at the same time? This study aims to answer the question by comprehensively comparing the temperature and humidity profiles from the "TqJoint" group and the "Standard" group. The comparison includes mean differences at different levels globally and over land and ocean. We are also working on examining the sampling differences between the "TqJoint" and "Standard" group using MERRA data.

European climate reconstructed for the past 500 years based on documentary and instrumental evidence

NASA Astrophysics Data System (ADS)

Wheeler, Dennis; Brazdil, Rudolf; Pfister, Christian

2010-05-01

European climate reconstructed for the past 500 years based on documentary and instrumental evidence Dennis Wheeler, Rudolf Brázdil, Christian Pfister and the Millennium project SG1 team The paper summarises the results of historical-climatological research conducted as part of the EU-funded 6th FP project MILLENNIUM the principal focus of which was the investigation of European climate during the past one thousand years (http://www.millenniumproject.net/). This project represents a major advance in bringing together, for the first time on such a scale, historical climatologists with other palaeoclimatological communities and climate modellers from many European countries. As part of MILLENNIUM, a sub-group (SG1) of historical climatologists from ten countries had the responsibility of collating and comprehensively analysing evidence from instrumental and documentary archives. This paper presents the main results of this undertaking but confines its attention to the study of the climate of the past 500 years and represents a summary of 10 themed papers submitted for a special issue of Climatic Change. They range across a variety of topics including newly-studied documentary data sources (e.g. early instrumental records, opening of the Stockholm harbour, ship log book data), temperature reconstructions for Central Europe, the Stockholm area and Mediterranean based on different types of documentary evidence, the application of standard paleoclimatological approaches to reconstructions based on index series derived from the documentary data, the influence of circulation dynamics on January-April climate , a comparison of reconstructions based on documentary data with the model runs (ECHO-G), a study of the quality of instrumental data in climate reconstructions, a 500-year flood chronology in Europe, and selected disastrous European windstorms and their reflection in documentary evidence and human memory. Finally, perspectives of historical-climatological research and future challenges and directions in this rapidly-developing and important field are presented together with an overview of the potential of documentary sources for climatic reconstructions.

Single-Column Modeling, GCM Parameterizations and Atmospheric Radiation Measurement Data

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

Somerville, R.C.J.; Iacobellis, S.F.

2005-03-18

Our overall goal is identical to that of the Atmospheric Radiation Measurement (ARM) Program: the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data at all three ARM sites, and the implementation and testing of these parameterizations in global and regional models. To test recently developed prognostic parameterizations based on detailed cloud microphysics, we have first compared single-column model (SCM) output with ARM observations at the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Topical Western Pacific (TWP) sites. We focus on the predicted cloud amounts and on a suite of radiativemore » quantities strongly dependent on clouds, such as downwelling surface shortwave radiation. Our results demonstrate the superiority of parameterizations based on comprehensive treatments of cloud microphysics and cloud-radiative interactions. At the SGP and NSA sites, the SCM results simulate the ARM measurements well and are demonstrably more realistic than typical parameterizations found in conventional operational forecasting models. At the TWP site, the model performance depends strongly on details of the scheme, and the results of our diagnostic tests suggest ways to develop improved parameterizations better suited to simulating cloud-radiation interactions in the tropics generally. These advances have made it possible to take the next step and build on this progress, by incorporating our parameterization schemes in state-of-the-art 3D atmospheric models, and diagnosing and evaluating the results using independent data. Because the improved cloud-radiation results have been obtained largely via implementing detailed and physically comprehensive cloud microphysics, we anticipate that improved predictions of hydrologic cycle components, and hence of precipitation, may also be achievable. We are currently testing the performance of our ARM-based parameterizations in state-of-the--art global and regional models. One fruitful strategy for evaluating advances in parameterizations has turned out to be using short-range numerical weather prediction as a test-bed within which to implement and improve parameterizations for modeling and predicting climate variability. The global models we have used to date are the CAM atmospheric component of the National Center for Atmospheric Research (NCAR) CCSM climate model as well as the National Centers for Environmental Prediction (NCEP) numerical weather prediction model, thus allowing testing in both climate simulation and numerical weather prediction modes. We present detailed results of these tests, demonstrating the sensitivity of model performance to changes in parameterizations.« less

Capturing interactions between nitrogen and hydrological cycles under historical climate and land use: Susquehanna watershed analysis with the GFDL land model LM3-TAN

USGS Publications Warehouse

Lee, M.; Malyshev, S.; Shevliakova, E.; Milly, Paul C. D.; Jaffé, P. R.

2014-01-01

We developed a process model LM3-TAN to assess the combined effects of direct human influences and climate change on terrestrial and aquatic nitrogen (TAN) cycling. The model was developed by expanding NOAA's Geophysical Fluid Dynamics Laboratory land model LM3V-N of coupled terrestrial carbon and nitrogen (C-N) cycling and including new N cycling processes and inputs such as a soil denitrification, point N sources to streams (i.e., sewage), and stream transport and microbial processes. Because the model integrates ecological, hydrological, and biogeochemical processes, it captures key controls of the transport and fate of N in the vegetation–soil–river system in a comprehensive and consistent framework which is responsive to climatic variations and land-use changes. We applied the model at 1/8° resolution for a study of the Susquehanna River Basin. We simulated with LM3-TAN stream dissolved organic-N, ammonium-N, and nitrate-N loads throughout the river network, and we evaluated the modeled loads for 1986–2005 using data from 16 monitoring stations as well as a reported budget for the entire basin. By accounting for interannual hydrologic variability, the model was able to capture interannual variations of stream N loadings. While the model was calibrated with the stream N loads only at the last downstream Susquehanna River Basin Commission station Marietta (40°02' N, 76°32' W), it captured the N loads well at multiple locations within the basin with different climate regimes, land-use types, and associated N sources and transformations in the sub-basins. Furthermore, the calculated and previously reported N budgets agreed well at the level of the whole Susquehanna watershed. Here we illustrate how point and non-point N sources contributing to the various ecosystems are stored, lost, and exported via the river. Local analysis of six sub-basins showed combined effects of land use and climate on soil denitrification rates, with the highest rates in the Lower Susquehanna Sub-Basin (extensive agriculture; Atlantic coastal climate) and the lowest rates in the West Branch Susquehanna Sub-Basin (mostly forest; Great Lakes and Midwest climate). In the re-growing secondary forests, most of the N from non-point sources was stored in the vegetation and soil, but in the agricultural lands most N inputs were removed by soil denitrification, indicating that anthropogenic N applications could drive substantial increase of N2O emission, an intermediate of the denitrification process.

Hydrological Modelling the Middle Magdalena Valley (Colombia)

NASA Astrophysics Data System (ADS)

Arenas, M. C.; Duque, N.; Arboleda, P.; Guadagnini, A.; Riva, M.; Donado-Garzon, L. D.

2017-12-01

Hydrological distributed modeling is key point for a comprehensive assessment of the feedback between the dynamics of the hydrological cycle, climate conditions and land use. Such modeling results are markedly relevant in the fields of water resources management, natural hazards and oil and gas industry. Here, we employ TopModel (TOPography based hydrological MODEL) for the hydrological modeling of an area in the Middle Magdalena Valley (MMV), a tropical basin located in Colombia. This study is located over the intertropical convergence zone and is characterized by special meteorological conditions, with fast water fluxes over the year. It has been subject to significant land use changes, as a result of intense economical activities, i.e., and agriculture, energy and oil & gas production. The model employees a record of 12 years of daily precipitation and evapotranspiration data as inputs. Streamflow data monitored across the same time frame are used for model calibration. The latter is performed by considering data from 2000 to 2008. Model validation then relies on observations from 2009 to 2012. The robustness of our analyses is based on the Nash-Sutcliffe coefficient (values of this metric being 0.62 and 0.53, respectively for model calibration and validation). Our results reveal high water storage capacity in the soil, and a marked subsurface runoff, consistent with the characteristics of the soil types in the regions. A significant influence on runoff response of the basin to topographical factors represented in the model is evidenced. Our calibrated model provides relevant indications about recharge in the region, which is important to quantify the interaction between surface water and groundwater, specially during the dry season, which is more relevant in climate-change and climate-variability scenarios.

Projecting the potential evapotranspiration by coupling different formulations and input data reliabilities: The possible uncertainty source for climate change impacts on hydrological regime

NASA Astrophysics Data System (ADS)

Wang, Weiguang; Li, Changni; Xing, Wanqiu; Fu, Jianyu

2017-12-01

Representing atmospheric evaporating capability for a hypothetical reference surface, potential evapotranspiration (PET) determines the upper limit of actual evapotranspiration and is an important input to hydrological models. Due that present climate models do not give direct estimates of PET when simulating the hydrological response to future climate change, the PET must be estimated first and is subject to the uncertainty on account of many existing formulae and different input data reliabilities. Using four different PET estimation approaches, i.e., the more physically Penman (PN) equation with less reliable input variables, more empirical radiation-based Priestley-Taylor (PT) equation with relatively dependable downscaled data, the most simply temperature-based Hamon (HM) equation with the most reliable downscaled variable, and downscaling PET directly by the statistical downscaling model, this paper investigated the differences of runoff projection caused by the alternative PET methods by a well calibrated abcd monthly hydrological model. Three catchments, i.e., the Luanhe River Basin, the Source Region of the Yellow River and the Ganjiang River Basin, representing a large climatic diversity were chosen as examples to illustrate this issue. The results indicated that although similar monthly patterns of PET over the period 2021-2050 for each catchment were provided by the four methods, the magnitudes of PET were still slightly different, especially for spring and summer months in the Luanhe River Basin and the Source Region of the Yellow River with relatively dry climate feature. The apparent discrepancy in magnitude of change in future runoff and even the diverse change direction for summer months in the Luanhe River Basin and spring months in the Source Region of the Yellow River indicated that the PET method related uncertainty occurred, especially in the Luanhe River Basin and the Source Region of the Yellow River with smaller aridity index. Moreover, the possible reason of discrepancies in uncertainty between three catchments was quantitatively discussed by the contribution analysis based on climatic elasticity method. This study can provide beneficial reference to comprehensively understand the impacts of climate change on hydrological regime and thus improve the regional strategy for future water resource management.

C-band radar observes water level change in swamp forests

USGS Publications Warehouse

Lu, Zhong; Crane, Mike; Kwoun, Oh-Ig; Wells, Christopher J.; Rykhus, Russ

2005-01-01

Wetlands cover more than 4% of the Earth's land surface and interact with hydrologic, biogeochemical, and sediment transport processes that are fundamental in understanding ecological and climatic changes [Alsdorf et al, 2003; Prigent et al., 2001 ; Melack and Forsberg, 2000;Dunne et al., 1998]. Measurement of water level changes in wetlands, and consequently of changes in water storage capacity, provides a required input for hydrologic models, and is required to comprehensively assess flood hazards [e.g., Coe, 1998].

Implications of Climate Mitigation for Future Agricultural Production

NASA Technical Reports Server (NTRS)

Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Deryng, Delphine; Folberth, Christian; Pugh, Thomas A. M.; Schmid, Erwin

2015-01-01

Climate change is projected to negatively impact biophysical agricultural productivity in much of the world. Actions taken to reduce greenhouse gas emissions and mitigate future climate changes, are thus of central importance for agricultural production. Climate impacts are, however, not unidirectional; some crops in some regions (primarily higher latitudes) are projected to benefit, particularly if increased atmospheric carbon dioxide is assumed to strongly increase crop productivity at large spatial and temporal scales. Climate mitigation measures that are implemented by reducing atmospheric carbon dioxide concentrations lead to reductions both in the strength of climate change and in the benefits of carbon dioxide fertilization. Consequently, analysis of the effects of climate mitigation on agricultural productivity must address not only regions for which mitigation is likely to reduce or even reverse climate damages. There are also regions that are likely to see increased crop yields due to climate change, which may lose these added potentials under mitigation action. Comparing data from the most comprehensive archive of crop yield projections publicly available, we find that climate mitigation leads to overall benefits from avoided damages at the global scale and especially in many regions that are already at risk of food insecurity today. Ignoring controversial carbon dioxide fertilization effects on crop productivity, we find that for the median projection aggressive mitigation could eliminate approximately 81% of the negative impacts of climate change on biophysical agricultural productivity globally by the end of the century. In this case, the benefits of mitigation typically extend well into temperate regions, but vary by crop and underlying climate model projections. Should large benefits to crop yields from carbon dioxide fertilization be realized, the effects of mitigation become much more mixed, though still positive globally and beneficial in many food insecure countries.

Decadal application of WRF/chem for regional air quality and climate modeling over the U.S. under the representative concentration pathways scenarios. Part 2: Current vs. future simulations

NASA Astrophysics Data System (ADS)

Yahya, Khairunnisa; Campbell, Patrick; Zhang, Yang

2017-03-01

Following a comprehensive model evaluation, this Part II paper presents projected changes in future (2046-2055) climate, air quality, and their interactions under the RCP4.5 and RCP8.5 scenarios using the Weather, Research and Forecasting model with Chemistry (WRF/Chem). In general, both WRF/Chem RCP4.5 and RCP8.5 simulations predict similar increases on average (∼2 °C) for 2-m temperature (T2) but different spatial distributions of the projected changes in T2, 2-m relative humidity, 10-m wind speed, precipitation, and planetary boundary layer height, due to differences in the spatial distributions of projected emissions, and their feedbacks into climate. Future O3 mixing ratios will decrease for most parts of the U.S. under the RCP4.5 scenario but increase for all areas under the RCP8.5 scenario due to higher projected temperature, greenhouse gas concentrations and biogenic volatile organic compounds (VOC) emissions, higher O3 values for boundary conditions, and disbenefit of NOx reduction and decreased NO titration over VOC-limited O3 chemistry regions. Future PM2.5 concentrations will decrease for both RCP4.5 and RCP8.5 scenarios with different trends in projected concentrations of individual PM species. Total cloud amounts decrease under both scenarios in the future due to decreases in PM and cloud droplet number concentration thus increased radiation. Those results illustrate the impacts of carbon policies with different degrees of emission reductions on future climate and air quality. The WRF/Chem and WRF simulations show different spatial patterns for projected changes in T2 for future decade, indicating different impacts of prognostic and prescribed gas/aerosol concentrations, respectively, on climate change.

Impacts of Climate Change on the Global Invasion Potential of the African Clawed Frog Xenopus laevis

PubMed Central

Ihlow, Flora; Courant, Julien; Secondi, Jean; Herrel, Anthony; Rebelo, Rui; Measey, G. John; Lillo, Francesco; De Villiers, F. André; Vogt, Solveig; De Busschere, Charlotte; Backeljau, Thierry; Rödder, Dennis

2016-01-01

By altering or eliminating delicate ecological relationships, non-indigenous species are considered a major threat to biodiversity, as well as a driver of environmental change. Global climate change affects ecosystems and ecological communities, leading to changes in the phenology, geographic ranges, or population abundance of several species. Thus, predicting the impacts of global climate change on the current and future distribution of invasive species is an important subject in macroecological studies. The African clawed frog (Xenopus laevis), native to South Africa, possesses a strong invasion potential and populations have become established in numerous countries across four continents. The global invasion potential of X. laevis was assessed using correlative species distribution models (SDMs). SDMs were computed based on a comprehensive set of occurrence records covering South Africa, North America, South America and Europe and a set of nine environmental predictors. Models were built using both a maximum entropy model and an ensemble approach integrating eight algorithms. The future occurrence probabilities for X. laevis were subsequently computed using bioclimatic variables for 2070 following four different IPCC scenarios. Despite minor differences between the statistical approaches, both SDMs predict the future potential distribution of X. laevis, on a global scale, to decrease across all climate change scenarios. On a continental scale, both SDMs predict decreasing potential distributions in the species’ native range in South Africa, as well as in the invaded areas in North and South America, and in Australia where the species has not been introduced. In contrast, both SDMs predict the potential range size to expand in Europe. Our results suggest that all probability classes will be equally affected by climate change. New regional conditions may promote new invasions or the spread of established invasive populations, especially in France and Great Britain. PMID:27248830

Impacts of Climate Change on the Global Invasion Potential of the African Clawed Frog Xenopus laevis.

PubMed

Ihlow, Flora; Courant, Julien; Secondi, Jean; Herrel, Anthony; Rebelo, Rui; Measey, G John; Lillo, Francesco; De Villiers, F André; Vogt, Solveig; De Busschere, Charlotte; Backeljau, Thierry; Rödder, Dennis

2016-01-01

By altering or eliminating delicate ecological relationships, non-indigenous species are considered a major threat to biodiversity, as well as a driver of environmental change. Global climate change affects ecosystems and ecological communities, leading to changes in the phenology, geographic ranges, or population abundance of several species. Thus, predicting the impacts of global climate change on the current and future distribution of invasive species is an important subject in macroecological studies. The African clawed frog (Xenopus laevis), native to South Africa, possesses a strong invasion potential and populations have become established in numerous countries across four continents. The global invasion potential of X. laevis was assessed using correlative species distribution models (SDMs). SDMs were computed based on a comprehensive set of occurrence records covering South Africa, North America, South America and Europe and a set of nine environmental predictors. Models were built using both a maximum entropy model and an ensemble approach integrating eight algorithms. The future occurrence probabilities for X. laevis were subsequently computed using bioclimatic variables for 2070 following four different IPCC scenarios. Despite minor differences between the statistical approaches, both SDMs predict the future potential distribution of X. laevis, on a global scale, to decrease across all climate change scenarios. On a continental scale, both SDMs predict decreasing potential distributions in the species' native range in South Africa, as well as in the invaded areas in North and South America, and in Australia where the species has not been introduced. In contrast, both SDMs predict the potential range size to expand in Europe. Our results suggest that all probability classes will be equally affected by climate change. New regional conditions may promote new invasions or the spread of established invasive populations, especially in France and Great Britain.

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

NASA Technical Reports Server (NTRS)

Wang, Weile; Nemani, Ramakrishna R.; Michaelis, Andrew; Hashimoto, Hirofumi; Dungan, Jennifer L.; Thrasher, Bridget L.; Dixon, Keith W.

2016-01-01

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km x 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

Model of urban water management towards water sensitive city: a literature review

NASA Astrophysics Data System (ADS)

Maftuhah, D. I.; Anityasari, M.; Sholihah, M.

2018-04-01

Nowadays, many cities are facing with complex issues such as climate change, social, economic, culture, and environmental problems, especially urban water. In other words, the city has to struggle with the challenge to make sure its sustainability in all aspects. This research focuses on how to ensure the city sustainability and resilience on urban water management. Many research were not only conducted in urban water management, but also in sustainability itself. Moreover, water sustainability shifts from urban water management into water sensitive city. This transition needs comprehensive aspects such as social, institutional dynamics, technical innovation, and local contents. Some literatures about model of urban water management and the transition towards water sensitivity had been reviewed in this study. This study proposed discussion about model of urban water management and the transition towards water sensitive city. Research findings suggest that there are many different models developed in urban water management, but they are not comprehensive yet and only few studies discuss about the transition towards water sensitive and resilience city. The drawbacks of previous research can identify and fulfill the gap of this study. Therefore, the paper contributes a general framework for the urban water management modelling studies.

On the use of through-fall exclusion experiments to filter model hypotheses.

NASA Astrophysics Data System (ADS)

Fisher, R.

2015-12-01

One key threat to the continued existence of large tropical forest carbon reservoirs is the increasing severity of drought across Amazonian forests, observed both in climate model predictions, in recent extreme drought events and in the more chronic lengthening of the dry season of South Eastern Amazonia. Model comprehension of these systems is in it's infancy, particularly with regard to the sensitivities of model output to the representation of hydraulic strategies in tropical forest systems. Here we use data from the ongoing 14 year old Caxiuana through-fall exclusion experiment, in Eastern Brazil, to filter a set of representations of the costs and benefits of alternative hydraulic strategies. In representations where there is a high resource cost to hydraulic resilience, the trait filtering CLM4.5(ED) model selects vegetation types that are sensitive to drought. Conversely, where drought tolerance is inexpensive, a more robust ecosystem emerges from the vegetation dynamic prediction. Thus, there is an impact of trait trade-off relationships on rainforest drought tolerance. It is possible to constrain the more realistic scenarios using outputs from the drought experiments. Better prediction would likely result from a more comprehensive understanding of the costs and benefits of alternative plant strategies.

Convening Young Leaders for Climate Resilience in New York State

NASA Astrophysics Data System (ADS)

Kretser, J.

2017-12-01

This project, led by The Wild Center, will partner with Cornell Cooperative Extension of Delaware County, the Kurt Hahn Expeditionary Learning School in Brooklyn, and the Alliance for Climate Education to do the following over three years: 1) increase climate literacy and preparedness planning in high school students through place-based Youth Climate Summits in the Adirondacks, Catskills, and New York City; 2) enhance young people's capacity to lead on climate issues through a Youth Climate Leadership Practicum 3) increase teacher comprehension and understanding of climate change through a Teacher Climate Institute and 4) communicate climate change impacts and resilience through student-driven Community Climate Outreach activities. The project will align with New York State's climate resiliency planning by collaborating with the NYS Department of Environmental Conservation Office of Climate (OCC), NYS Energy Research Development Authority (NYSERDA), and NOAA's Climate Program Office to provide accurate scientific information, resources, and tools. This collaboration will result in an increase in understanding of the impacts of climate change in rural (Adirondacks, Catskills) and urban (New York City) regions of New York State; a wider awareness of the threats and vulnerabilities that are associated with a community's location; and a stronger connection between current community resilience initiatives, educators, and youth. All three of the project sites are critically underserved in both climate literacy and action, making addressing the need of these sites to be resilient and proactive in the face of climate change critical. Our model will provide pilot lessons for how youth in both rural and urban areas can draw on local assets to address resiliency in ways appropriate for their own areas, and these lessons may be able to be applied across the United States.The proposed project is informed by best practices and specifically strengthens and replicates The Wild Center's past success with the Adirondack Youth Climate Summit, student leadership, and student-led community outreach for climate awareness - all work that has been tested or piloted over the last seven years.

Performance metrics and variance partitioning reveal sources of uncertainty in species distribution models

USGS Publications Warehouse

Watling, James I.; Brandt, Laura A.; Bucklin, David N.; Fujisaki, Ikuko; Mazzotti, Frank J.; Romañach, Stephanie; Speroterra, Carolina

2015-01-01

Species distribution models (SDMs) are widely used in basic and applied ecology, making it important to understand sources and magnitudes of uncertainty in SDM performance and predictions. We analyzed SDM performance and partitioned variance among prediction maps for 15 rare vertebrate species in the southeastern USA using all possible combinations of seven potential sources of uncertainty in SDMs: algorithms, climate datasets, model domain, species presences, variable collinearity, CO2 emissions scenarios, and general circulation models. The choice of modeling algorithm was the greatest source of uncertainty in SDM performance and prediction maps, with some additional variation in performance associated with the comprehensiveness of the species presences used for modeling. Other sources of uncertainty that have received attention in the SDM literature such as variable collinearity and model domain contributed little to differences in SDM performance or predictions in this study. Predictions from different algorithms tended to be more variable at northern range margins for species with more northern distributions, which may complicate conservation planning at the leading edge of species' geographic ranges. The clear message emerging from this work is that researchers should use multiple algorithms for modeling rather than relying on predictions from a single algorithm, invest resources in compiling a comprehensive set of species presences, and explicitly evaluate uncertainty in SDM predictions at leading range margins.

Major modes of short-term climate variability in the newly developed NUIST Earth System Model (NESM)

NASA Astrophysics Data System (ADS)

Cao, Jian; Wang, Bin; Xiang, Baoqiang; Li, Juan; Wu, Tianjie; Fu, Xiouhua; Wu, Liguang; Min, Jinzhong

2015-05-01

A coupled earth system model (ESM) has been developed at the Nanjing University of Information Science and Technology (NUIST) by using version 5.3 of the European Centre Hamburg Model (ECHAM), version 3.4 of the Nucleus for European Modelling of the Ocean (NEMO), and version 4.1 of the Los Alamos sea ice model (CICE). The model is referred to as NUIST ESM1 (NESM1). Comprehensive and quantitative metrics are used to assess the model's major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model's assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring-fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific (CP)-ENSO and eastern Pacific (EP)-ENSO; however, the equatorial SST variability, biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden-Julian Oscillation (MJO), and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version (T159) demonstrates improved simulation with respect to the climatology, interannual variance, monsoon-ENSO lead-lag correlation, spatial structures of the leading mode of the Asian-Australian monsoon rainfall variability, and the eastward propagation of the MJO.

Models meet data: Challenges and opportunities in implementing land management in Earth system models.

PubMed

Pongratz, Julia; Dolman, Han; Don, Axel; Erb, Karl-Heinz; Fuchs, Richard; Herold, Martin; Jones, Chris; Kuemmerle, Tobias; Luyssaert, Sebastiaan; Meyfroidt, Patrick; Naudts, Kim

2018-04-01

As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land-cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices-forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire-for (1) their importance on the Earth system, (2) the possibility of implementing them in state-of-the-art ESMs, and (3) availability of required input data. Matching these criteria, we identify "low-hanging fruits" for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs. © 2017 John Wiley & Sons Ltd.

Effects of climatic variability and change on forest ecosystems: a comprehensive science synthesis for the U.S

Treesearch

James M. Vose; David L. Peterson; Toral Patel-Weynand

2012-01-01

This report is a scientific assessment of the current condition and likely future condition of forest resources in the United States relative to climatic variability and change. It serves as the U.S. Forest Service forest sector technical report for the National Climate Assessment and includes descriptions of key regional issues and examples of a risk-based framework...

Tectonics of the central Andes

NASA Technical Reports Server (NTRS)

Bloom, Arthur L.; Isacks, Bryan L.; Fielding, Eric J.; Fox, Andrew N.; Gubbels, Timothy L.

1989-01-01

Acquisition of nearly complete coverage of Thematic Mapper data for the central Andes between about 15 to 34 degrees S has stimulated a comprehensive and unprecedented study of the interaction of tectonics and climate in a young and actively developing major continental mountain belt. The current state of the synoptic mapping of key physiographic, tectonic, and climatic indicators of the dynamics of the mountain/climate system are briefly reviewed.

Commentaries on the National School Climate Standards. Benchmarks to Promote Effective Teaching, Learning and Comprehensive School Improvement. School Climate Brief, Number 2

ERIC Educational Resources Information Center

National School Climate Center, 2010

2010-01-01

The majority of Americans have a shared vision that K-12 education needs to support children's ability to love, work and participate effectively in a democratic society. The National School Climate Center, a growing number of State Departments of Education and recently, the United States Department of Education believe that when school communities…

Evaluating the effects of ideology on public understanding of climate change science: how to improve communication across ideological divides?

PubMed

Zia, Asim; Todd, Anne Marie

2010-11-01

While ideology can have a strong effect on citizen understanding of science, it is unclear how ideology interacts with other complicating factors, such as college education, which influence citizens' comprehension of information. We focus on public understanding of climate change science and test the hypotheses: [H1] as citizens' ideology shifts from liberal to conservative, concern for global warming decreases; [H2] citizens with college education and higher general science literacy tend to have higher concern for global warming; and [H3] college education does not increase global warming concern for conservative ideologues. We implemented a survey instrument in California's San Francisco Bay Area, and employed regression models to test the effects of ideology and other socio-demographic variables on citizen concern about global warming, terrorism, the economy, health care and poverty. We are able to confirm H1 and H3, but reject H2. Various strategies are discussed to improve the communication of climate change science across ideological divides.

Merging climate and multi-sensor time-series data in real-time drought monitoring across the U.S.A.

USGS Publications Warehouse

Brown, Jesslyn F.; Miura, T.; Wardlow, B.; Gu, Yingxin

2011-01-01

Droughts occur repeatedly in the United States resulting in billions of dollars of damage. Monitoring and reporting on drought conditions is a necessary function of government agencies at multiple levels. A team of Federal and university partners developed a drought decision- support tool with higher spatial resolution relative to traditional climate-based drought maps. The Vegetation Drought Response Index (VegDRI) indicates general canopy vegetation condition assimilation of climate, satellite, and biophysical data via geospatial modeling. In VegDRI, complementary drought-related data are merged to provide a comprehensive, detailed representation of drought stress on vegetation. Time-series data from daily polar-orbiting earth observing systems [Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS)] providing global measurements of land surface conditions are ingested into VegDRI. Inter-sensor compatibility is required to extend multi-sensor data records; thus, translations were developed using overlapping observations to create consistent, long-term data time series. 

77 FR 70805 - Presquile National Wildlife Refuge, Chesterfield County, VA; Final Comprehensive Conservation...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-27

... opportunities, including environmental education programs for approximately 120 school-aged students each year... species, protect cultural resources, monitor for climate change impacts, distribute refuge revenue sharing..., and a more aggressive response to habitat changes associated with invasive species, global climate...

Creating a global sub-daily precipitation dataset

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Blenkinsop, Stephen; Fowler, Hayley

2017-04-01

Extremes of precipitation can cause flooding and droughts which can lead to substantial damages to infrastructure and ecosystems and can result in loss of life. It is still uncertain how hydrological extremes will change with global warming as we do not fully understand the processes that cause extreme precipitation under current climate variability. The INTENSE project is using a novel and fully-integrated data-modelling approach to provide a step-change in our understanding of the nature and drivers of global precipitation extremes and change on societally relevant timescales, leading to improved high-resolution climate model representation of extreme rainfall processes. The INTENSE project is in conjunction with the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges Project (GEWEX) Science questions. The first step towards achieving this is to construct a new global sub-daily precipitation dataset. Data collection is ongoing and already covers North America, Europe, Asia and Australasia. Comprehensive, open source quality control software is being developed to set a new standard for verifying sub-daily precipitation data and a set of global hydroclimatic indices will be produced based upon stakeholder recommendations. This will provide a unique global data resource on sub-daily precipitation whose derived indices, e.g. monthly/annual maxima, will be freely available to the wider scientific community.

Linkages between ocean circulation, heat uptake and transient warming: a sensitivity study

NASA Astrophysics Data System (ADS)

Pfister, Patrik; Stocker, Thomas

2016-04-01

Transient global warming due to greenhouse gas radiative forcing is substantially reduced by ocean heat uptake (OHU). However, the fraction of equilibrium warming that is realized in transient climate model simulations differs strongly between models (Frölicher and Paynter 2015). It has been shown that this difference is not only related to the magnitude of OHU, but also to the radiative response the OHU causes, measured by the OHU efficacy (Winton et al., 2010). This efficacy is strongly influenced by the spatial pattern of the OHU and its changes (Rose et al. 2014, Winton et al. 2013), predominantly caused by changes in the Atlantic meridional overturning circulation (AMOC). Even in absence of external greenhouse gas forcing, an AMOC weakening causes a radiative imbalance at the top of the atmosphere (Peltier and Vettoretti, 2014), inducing in a net warming of the Earth System. We investigate linkages between those findings by performing both freshwater and greenhouse gas experiments in an Earth System Model of Intermediate Complexity. To assess the sensitivity of the results to ocean and atmospheric transport as well as climate sensitivity, we use an ensemble of model versions, systematically varying key parameters. We analyze circulation changes and radiative adjustments in conjunction with traditional warming metrics such as the transient climate response and the equilibrium climate sensitivity. This aims to improve the understanding of the influence of ocean circulation and OHU on transient climate change, and of the relevance of different metrics for describing this influence. References: Frölicher, T. L. and D.J. Paynter (2015), Extending the relationship between global warming and cumulative carbon emissions to multi-millennial timescales, Environ. Res. Lett., 10, 075022 Peltier, W. R., and G. Vettoretti (2014), Dansgaard-Oeschger oscillations predicted in a comprehensive model of glacial climate: A "kicked" salt oscillator in the Atlantic, Geophys. Res. Lett., 41, 7306-7313 Rose, B. E. J., K. C. Armour, D. S. Battisti, N. Feldl, and D. D. B. Koll (2014), The dependence of transient climate sensitivity and radiative feedbacks on the spatial pattern of ocean heat uptake, Geophys. Res. Lett., 41, 1071-1078 Winton M., K. Takahashi and I. M. Held (2010), Importance of ocean heat uptake efficacy to transient climate change, J. Clim., 23, 2333-44 Winton, M., S. M. Griffies, B. Samuels, J. L. Sarmiento and T. L. Frölicher (2013) Connecting changing ocean circulation with changing climate, J. Clim., 26, 2268-78

A bottom-up, vulnerability-based framework for identifying the adaptive capacity of water resources systems in a changing climate

NASA Astrophysics Data System (ADS)

Culley, Sam; Noble, Stephanie; Timbs, Michael; Yates, Adam; Giuliani, Matteo; Castelletti, Andrea; Maier, Holger; Westra, Seth

2015-04-01

Water resource system infrastructure and operating policies are commonly designed on the assumption that the statistics of future rainfall, temperature and other hydrometeorological variables are equal to those of the historical record. There is now substantial evidence demonstrating that this assumption is no longer valid, and that climate change will significantly impact water resources systems worldwide. Under different climatic inputs, the performance of these systems may degrade to a point where they become unable to meet the primary objectives for which they were built. In such a changing context, using existing infrastructure more efficiently - rather than planning additional infrastructure - becomes key to restore the system's performance at acceptable levels and minimize financial investments and associated risk. The traditional top-down approach for assessing climate change impacts relies on the use of a cascade of models from the global to the local scale. However, it is often difficult to utilize this top-down approach in a decision-making procedure, as there is disparity amongst various climate projections, arising from incomplete scientific understanding of the complicated processes and feedbacks within the climate system, and model limitations in reproducing those relationships. In contrast with this top-down approach, this study contributes a framework to identify the adaptive capacity of water resource systems under changing climatic conditions adopting a bottom-up, vulnerability-based approach. The performance of the current system management is first assessed for a comprehensive range of climatic conditions, which are independent of climate model forecasts. The adaptive capacity of the system is then estimated by re-evaluating the performance of a set of adaptive operating policies, which are optimized for each climatic condition under which the system is simulated. The proposed framework reverses the perspective by identifying water system vulnerability drivers and by enhancing the adaptive capacity of the system to respond to unforeseen events, in order to design robust and resilient adaptation measures. The approach is demonstrated on the multipurpose operation of the Lake Como system, located in Northern Italy, accounting for flood protection and irrigation supply. Numerical results show that our framework successfully identified the failure boundary based on current system management policies, which is demonstrated as being particularly sensitive to decreases in both precipitation and temperature. To estimate the likelihood of the climate being in states causing system failures and to provide a time frame for reaching such states, we consider 22 climate model projections; these projections suggest that the current management policies will lead to a high chance of failure over the next 40 years. The adaptive capacity of the re-optimized operating policies exhibits the potential for partially mitigating adverse climate change impacts and for extending the life of the system.

Exploring the response of net primary productivity variations to urban expansion and climate change: a scenario analysis for Guangdong Province in China.

PubMed

Pei, Fengsong; Li, Xia; Liu, Xiaoping; Lao, Chunhua; Xia, Gengrui

2015-03-01

Urban land development alters landscapes and carbon cycle, especially net primary productivity (NPP). Despite projections that NPP is often reduced by urbanization, little is known about NPP changes under future urban expansion and climate change conditions. In this paper, terrestrial NPP was calculated by using Biome-BGC model. However, this model does not explicitly address urban lands. Hence, we proposed a method of NPP-fraction to detect future urban NPP, assuming that the ratio of real NPP to potential NPP for urban cells remains constant for decades. Furthermore, NPP dynamics were explored by integrating the Biome-BGC and the cellular automata (CA), a widely used method for modeling urban growth. Consequently, urban expansion, climate change and their associated effects on the NPP were analyzed for the period of 2010-2039 using Guangdong Province in China as a case study. In addition, four scenarios were designed to reflect future conditions, namely baseline, climate change, urban expansion and comprehensive scenarios. Our analyses indicate that vegetation NPP in urban cells may increase (17.63 gC m(-2) year(-1)-23.35 gC m(-2) year(-1)) in the climate change scenario. However, future urban expansion may cause some NPP losses of 241.61 gC m(-2) year(-1), decupling the NPP increase of the climate change factor. Taking into account both climate change and urban expansion, vegetation NPP in urban area may decrease, minimally at a rate of 228.54 gC m(-2) year(-1) to 231.74 gC m(-2) year(-1). Nevertheless, they may account for an overall NPP increase of 0.78 TgC year(-1) to 1.28 TgC year(-1) in the whole province. All these show that the provincial NPP increase from climate change may offset the NPP decrease from urban expansion. Despite these results, it is of great significance to regulate reasonable expansion of urban lands to maintain carbon balance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Conservation Status of North American Birds in the Face of Future Climate Change.

PubMed

Langham, Gary M; Schuetz, Justin G; Distler, Trisha; Soykan, Candan U; Wilsey, Chad

2015-01-01

Human-induced climate change is increasingly recognized as a fundamental driver of biological processes and patterns. Historic climate change is known to have caused shifts in the geographic ranges of many taxa and future climate change is expected to result in even greater redistributions of species. As a result, predicting the impact of climate change on future patterns of biodiversity will greatly aid conservation planning. Using the North American Breeding Bird Survey and Audubon Christmas Bird Count, two of the most comprehensive continental datasets of vertebrates in the world, and correlative distribution modeling, we assessed geographic range shifts for 588 North American bird species during both the breeding and non-breeding seasons under a range of future emission scenarios (SRES A2, A1B, B2) through the end of the century. Here we show that 314 species (53%) are projected to lose more than half of their current geographic range across three scenarios of climate change through the end of the century. For 126 species, loss occurs without concomitant range expansion; whereas for 188 species, loss is coupled with potential to colonize new replacement range. We found no strong associations between projected climate sensitivities and existing conservation prioritizations. Moreover, species responses were not clearly associated with habitat affinities, migration strategies, or climate change scenarios. Our results demonstrate the need to include climate sensitivity into current conservation planning and to develop adaptive management strategies that accommodate shrinking and shifting geographic ranges. The persistence of many North American birds will depend on their ability to colonize climatically suitable areas outside of current ranges and management actions that target climate adaptation.

Conservation Status of North American Birds in the Face of Future Climate Change

PubMed Central

Langham, Gary M.; Schuetz, Justin G.; Distler, Trisha; Soykan, Candan U.; Wilsey, Chad

2015-01-01

Human-induced climate change is increasingly recognized as a fundamental driver of biological processes and patterns. Historic climate change is known to have caused shifts in the geographic ranges of many taxa and future climate change is expected to result in even greater redistributions of species. As a result, predicting the impact of climate change on future patterns of biodiversity will greatly aid conservation planning. Using the North American Breeding Bird Survey and Audubon Christmas Bird Count, two of the most comprehensive continental datasets of vertebrates in the world, and correlative distribution modeling, we assessed geographic range shifts for 588 North American bird species during both the breeding and non-breeding seasons under a range of future emission scenarios (SRES A2, A1B, B2) through the end of the century. Here we show that 314 species (53%) are projected to lose more than half of their current geographic range across three scenarios of climate change through the end of the century. For 126 species, loss occurs without concomitant range expansion; whereas for 188 species, loss is coupled with potential to colonize new replacement range. We found no strong associations between projected climate sensitivities and existing conservation prioritizations. Moreover, species responses were not clearly associated with habitat affinities, migration strategies, or climate change scenarios. Our results demonstrate the need to include climate sensitivity into current conservation planning and to develop adaptive management strategies that accommodate shrinking and shifting geographic ranges. The persistence of many North American birds will depend on their ability to colonize climatically suitable areas outside of current ranges and management actions that target climate adaptation. PMID:26333202

The Influence of Roof Material on Diurnal Urban Canyon Breathing

NASA Astrophysics Data System (ADS)

Abuhegazy, Mohamed; Yaghoobian, Neda

2017-11-01

Improvements in building energy use, air quality in urban canyons and in general urban microclimates require understanding the complex interaction between urban morphology, materials, climate, and inflow conditions. Review of the literature indicates that despite a long history of valuable urban microclimate studies, more comprehensive approaches are needed to address energy, and heat and flow transport in urban areas. In this study, a more comprehensive simulation of the diurnally varying street canyon flow and associated heat transport is numerically investigated, using Large-eddy Simulation (LES). We use computational modeling to examine the impact of diurnal variation of the heat fluxes from urban surfaces on the air flow and temperature distribution in street canyons with a focus on the role of roof materials and their temperature footprints. A detailed building energy model with a three-dimensional raster-type geometry provides urban surface heat fluxes as thermal boundary conditions for the LES to determine the key aero-thermodynamic factors that affect urban street ventilation.

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.

The NorWeST Stream Temperature Database, Model, and Climate Scenarios for the Northwest U.S. (Invited)

NASA Astrophysics Data System (ADS)

Isaak, D.; Wenger, S.; Peterson, E.; Ver Hoef, J.; Luce, C.; Hostetler, S. W.; Kershner, J.; Dunham, J.; Nagel, D.; Roper, B.

2013-12-01

Anthropogenic climate change is warming the Earth's rivers and streams and threatens significant changes to aquatic biodiversity. Effective threat response will require prioritization of limited conservation resources and coordinated interagency efforts guided by accurate information about climate, and climate change, at scales relevant to the distributions of species across landscapes. Here, we describe the NorWeST (i.e., NorthWest Stream Temperature) project to develop a comprehensive interagency stream temperature database and high-resolution climate scenarios across Washington, Oregon, Idaho, Montana, and Wyoming (~400,000 stream kilometers). The NorWeST database consists of stream temperature data contributed by >60 state, federal, tribal, and private resource agencies and may be the largest of its kind in the world (>45,000,000 hourly temperature recordings at >15,000 unique monitoring sites). These data are being used with spatial statistical network models to accurately downscale (R2 = 90%; RMSE < 1 C) global climate patterns to all perennially flowing reaches within river networks at 1-kilometer resolution. Historic stream temperature scenarios are developed using air temperature data from RegCM3 runs for the NCEP historical reanalysis and future scenarios (2040s and 2080s) are developed by applying bias corrected air temperature and discharge anomalies from ensemble climate and hydrology model runs for A1B and A2 warming trajectories. At present, stream temperature climate scenarios have been developed for 230,000 stream kilometers across Idaho and western Montana using data from more than 7,000 monitoring sites. The raw temperature data and stream climate scenarios are made available as ArcGIS geospatial products for download through the NorWeST website as individual river basins are completed (http://www.fs.fed.us/rm/boise/AWAE/projects/NorWeST.shtml). By providing open access to temperature data and scenarios, the project is fostering new research on stream temperatures and better collaborative management of aquatic resources through improved: 1) climate vulnerability assessments for sensitive species, 2) decision support tools that use regionally consistent scenarios, 3) water quality assessments, and 4) temperature and biological monitoring programs. Additional project details are contained in this Great Northern Landscape Conservation Cooperative newsletter (http://greatnorthernlcc.org/features/streamtemp-database).

From Global to Local

ERIC Educational Resources Information Center

Kinslow, Andrew; Sadler, Troy; Friedrichsen, Patricia; Zangori, Laura; Peel, Amanda; Graham, Kerri

2017-01-01

The global scale of climate change may seem beyond many high school students' comprehension. To complicate matters, climate change has emerged as a political issue that pits candidates, neighbors, and sometimes teachers and students against each other (Kahan 2015). The "Next Generation Science Standards" (NGSS Lead States 2013) call on…

Understanding the glacial methane cycle

NASA Astrophysics Data System (ADS)

Hopcroft, Peter O.; Valdes, Paul J.; O'Connor, Fiona M.; Kaplan, Jed O.; Beerling, David J.

2017-02-01

Atmospheric methane (CH4) varied with climate during the Quaternary, rising from a concentration of 375 p.p.b.v. during the last glacial maximum (LGM) 21,000 years ago, to 680 p.p.b.v. at the beginning of the industrial revolution. However, the causes of this increase remain unclear; proposed hypotheses rely on fluctuations in either the magnitude of CH4 sources or CH4 atmospheric lifetime, or both. Here we use an Earth System model to provide a comprehensive assessment of these competing hypotheses, including estimates of uncertainty. We show that in this model, the global LGM CH4 source was reduced by 28-46%, and the lifetime increased by 2-8%, with a best-estimate LGM CH4 concentration of 463-480 p.p.b.v. Simulating the observed LGM concentration requires a 46-49% reduction in sources, indicating that we cannot reconcile the observed amplitude. This highlights the need for better understanding of the effects of low CO2 and cooler climate on wetlands and other natural CH4 sources.

A comprehensive catalogue and classification of human thermal climate indices

NASA Astrophysics Data System (ADS)

de Freitas, C. R.; Grigorieva, E. A.

2015-01-01

The very large number of human thermal climate indices that have been proposed over the past 100 years or so is a manifestation of the perceived importance within the scientific community of the thermal environment and the desire to quantify it. Schemes used differ in approach according to the number of variables taken into account, the rationale employed, the relative sophistication of the underlying body-atmosphere heat exchange theory and the particular design for application. They also vary considerably in type and quality, as well as in several other aspects. Reviews appear in the literature, but they cover a limited number of indices. A project that produces a comprehensive documentation, classification and overall evaluation of the full range of existing human thermal climate indices has never been attempted. This paper deals with documentation and classification. A subsequent report will focus on evaluation. Here a comprehensive register of 162 thermal indices is assembled and a sorting scheme devised that groups them according to eight primary classification classes. It is the first stage in a project to organise and evaluate the full range of all human thermal climate indices. The work, when completed, will make it easier for users to reflect on the merits of all available thermal indices. It will be simpler to locate and compare indices and decide which is most appropriate for a particular application or investigation.

A comprehensive catalogue and classification of human thermal climate indices.

PubMed

de Freitas, C R; Grigorieva, E A

2015-01-01

The very large number of human thermal climate indices that have been proposed over the past 100 years or so is a manifestation of the perceived importance within the scientific community of the thermal environment and the desire to quantify it. Schemes used differ in approach according to the number of variables taken into account, the rationale employed, the relative sophistication of the underlying body-atmosphere heat exchange theory and the particular design for application. They also vary considerably in type and quality, as well as in several other aspects. Reviews appear in the literature, but they cover a limited number of indices. A project that produces a comprehensive documentation, classification and overall evaluation of the full range of existing human thermal climate indices has never been attempted. This paper deals with documentation and classification. A subsequent report will focus on evaluation. Here a comprehensive register of 162 thermal indices is assembled and a sorting scheme devised that groups them according to eight primary classification classes. It is the first stage in a project to organise and evaluate the full range of all human thermal climate indices. The work, when completed, will make it easier for users to reflect on the merits of all available thermal indices. It will be simpler to locate and compare indices and decide which is most appropriate for a particular application or investigation.

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.

Methodology for the assessment of the impacts of climate change on land degradation at multiple scales: Use of high resolution satellite imagery, modelling, and ground measurements for the assessment in Ethiopia

NASA Astrophysics Data System (ADS)

Ahmed, Oumer

In this study, a new multi-scalar methodology for assessing land degradation response to climate change is presented by analyzing 22 years of both climatic data and satellite observations, together with future projections from modelling, for Ethiopia. A comprehensive analysis of the impacts of climate change on land degradation was performed as evidenced from the integration of a host of land degradation indicators, namely: normalized difference vegetation Index (NDVI), net primary productivity (NPP), crop yield, biomass, length of growing period (LGP), rainfall use efficiency (RUE), energy use efficiency (EUE) and aridity index (AI). The results from the national level assessment indicate that over the period of 1984-2006, NPP decreased overall. Degrading areas occupy 30% of the country and suffer an average loss of NPP 10.3 kg C ha-1 y-1. The crop yield prediction results indicate a wide range of outcomes is to be expected for the country, due to the heterogeneity of the agro-climatic resources as well as of projected climate change. The results of the sub-national level assessment show that about 29% of the Awash watershed is degrading, and these degrading areas experience an average loss of NPP 4.6 kg C ha-1 y-1. Further, about 33.8% of the degrading area in the watershed is associated with bare land and 25% with agricultural land. Finally, since remotely sensed estimates are frequently used to assess land degradation at multiple scales, scale transfer methods are evaluated in this study to provide a tool to rank both upscaling and downscaling procedures.

Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

USGS Publications Warehouse

Alvarez, Otto; Guo, Qinghua; Klinger, Robert C.; Li, Wenkai; Doherty, Paul

2013-01-01

Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.

Uncertainty and extreme events in future climate and hydrologic projections for the Pacific Northwest: providing a basis for vulnerability and core/corridor assessments

USGS Publications Warehouse

Littell, Jeremy S.; Mauger, Guillaume S.; Salathe, Eric P.; Hamlet, Alan F.; Lee, Se-Yeun; Stumbaugh, Matt R.; Elsner, Marketa; Norheim, Robert; Lutz, Eric R.; Mantua, Nathan J.

2014-01-01

The purpose of this project was to (1) provide an internally-consistent set of downscaled projections across the Western U.S., (2) include information about projection uncertainty, and (3) assess projected changes of hydrologic extremes. These objectives were designed to address decision support needs for climate adaptation and resource management actions. Specifically, understanding of uncertainty in climate projections – in particular for extreme events – is currently a key scientific and management barrier to adaptation planning and vulnerability assessment. The new dataset fills in the Northwest domain to cover a key gap in the previous dataset, adds additional projections (both from other global climate models and a comparison with dynamical downscaling) and includes an assessment of changes to flow and soil moisture extremes. This new information can be used to assess variations in impacts across the landscape, uncertainty in projections, and how these differ as a function of region, variable, and time period. In this project, existing University of Washington Climate Impacts Group (UW CIG) products were extended to develop a comprehensive data archive that accounts (in a reigorous and physically based way) for climate model uncertainty in future climate and hydrologic scenarios. These products can be used to determine likely impacts on vegetation and aquatic habitat in the Pacific Northwest (PNW) region, including WA, OR, ID, northwest MT to the continental divide, northern CA, NV, UT, and the Columbia Basin portion of western WY New data series and summaries produced for this project include: 1) extreme statistics for surface hydrology (e.g. frequency of soil moisture and summer water deficit) and streamflow (e.g. the 100-year flood, extreme 7-day low flows with a 10-year recurrence interval); 2) snowpack vulnerability as indicated by the ratio of April 1 snow water to cool-season precipitation; and, 3) uncertainty analyses for multiple climate scenarios.

Increase in flood risk resulting from climate change in a developed urban watershed - the role of storm temporal patterns

NASA Astrophysics Data System (ADS)

Hettiarachchi, Suresh; Wasko, Conrad; Sharma, Ashish

2018-03-01

The effects of climate change are causing more frequent extreme rainfall events and an increased risk of flooding in developed areas. Quantifying this increased risk is of critical importance for the protection of life and property as well as for infrastructure planning and design. The updated National Oceanic and Atmospheric Administration (NOAA) Atlas 14 intensity-duration-frequency (IDF) relationships and temporal patterns are widely used in hydrologic and hydraulic modeling for design and planning in the United States. Current literature shows that rising temperatures as a result of climate change will result in an intensification of rainfall. These impacts are not explicitly included in the NOAA temporal patterns, which can have consequences on the design and planning of adaptation and flood mitigation measures. In addition there is a lack of detailed hydraulic modeling when assessing climate change impacts on flooding. The study presented in this paper uses a comprehensive hydrologic and hydraulic model of a fully developed urban/suburban catchment to explore two primary questions related to climate change impacts on flood risk. (1) How do climate change effects on storm temporal patterns and rainfall volumes impact flooding in a developed complex watershed? (2) Is the storm temporal pattern as critical as the total volume of rainfall when evaluating urban flood risk? We use the NOAA Atlas 14 temporal patterns, along with the expected increase in temperature for the RCP8.5 scenario for 2081-2100, to project temporal patterns and rainfall volumes to reflect future climatic change. The model results show that different rainfall patterns cause variability in flood depths during a storm event. The changes in the projected temporal patterns alone increase the risk of flood magnitude up to 35 %, with the cumulative impacts of temperature rise on temporal patterns and the storm volume increasing flood risk from 10 to 170 %. The results also show that regional storage facilities are sensitive to rainfall patterns that are loaded in the latter part of the storm duration, while extremely intense short-duration storms will cause flooding at all locations. This study shows that changes in temporal patterns will have a significant impact on urban/suburban flooding and need to be carefully considered and adjusted to account for climate change when used for the design and planning of future storm water systems.

Modeling and mapping the current and future distribution of Pseudomonas syringae pv. actinidiae under climate change in China.

PubMed

Wang, Rulin; Li, Qing; He, Shisong; Liu, Yuan; Wang, Mingtian; Jiang, Gan

2018-01-01

Bacterial canker of kiwifruit caused by Pseudomonas syringae pv. actinidiae (Psa) is a major threat to the kiwifruit industry throughout the world and accounts for substantial economic losses in China. The aim of the present study was to test and explore the possibility of using MaxEnt (maximum entropy models) to predict and analyze the future large-scale distribution of Psa in China. Based on the current environmental factors, three future climate scenarios, which were suggested by the fifth IPCC report, and the current distribution sites of Psa, MaxEnt combined with ArcGIS was applied to predict the potential suitable areas and the changing trend of Psa in China. The jackknife test and correlation analysis were used to choose dominant climatic factors. The receiver operating characteristic curve (ROC) drawn by MaxEnt was used to evaluate the accuracy of the simulation. The results showed that under current climatic conditions, the area from latitude 25° to 36°N and from longitude 101° to 122°E is the primary potential suitable area of Psa in China. The highly suitable area (with suitability between 66 and 100) was mainly concentrated in Northeast Sichuan, South Shaanxi, most of Chongqing, West Hubei and Southwest Gansu and occupied 4.94% of land in China. Under different future emission scenarios, both the areas and the centers of the suitable areas all showed differences compared with the current situation. Four climatic variables, i.e., maximum April temperature (19%), mean temperature of the coldest quarter (14%), precipitation in May (11.5%) and minimum temperature in October (10.8%), had the largest impact on the distribution of Psa. The MaxEnt model is potentially useful for forecasting the future adaptive distribution of Psa under climate change, and it provides important guidance for comprehensive management.

Consequences of Changes in Vegetation and Snow Cover for Climate Feedbacks in Alaska and Northwest Canada

NASA Astrophysics Data System (ADS)

Euskirchen, E. S.; Breen, A. L.; Bennett, A.; Genet, H.; Lindgren, M.; Kurkowski, T. A.; McGuire, A. D.; Rupp, S. T.

2016-12-01

A continuing challenge in global change studies is to determine how land surface changes may impact atmospheric heating. Changes in vegetation and snow cover may lead to feedbacks to climate through changes in surface albedo and energy fluxes between the land and atmosphere. In addition to these biogeophysical feedbacks, biogeochemical feedbacks associated with changes in carbon (C) storage in the vegetation and soils may also influence climate. Here, using a transient biogeographic model (ALFRESCO) and an ecosystem model (DOS-TEM), we quantified the biogeophysical feedbacks due to changes in vegetation and snow cover across continuous permafrost to non-permafrost ecosystems in Alaska and northwest Canada. We also computed the changes in carbon storage in this region to provide a general assessment of the direction of the biogeochemical feedback. We considered four ecoregions, or Landscape Conservations Cooperatives (LCCs; including the Arctic, North Pacific, Western Alaska, and Northwest Boreal). We examined the 90-year period from 2010- 2099 using one future emission scenario (A1B), under outputs from two general circulation models (MPI-ECHAM5 and CCCMA-CGCM3.1). We consider a more comprehensive suite of possible feedbacks to climate due to shifts in vegetation than previous studies, including both boreal and tundra fire, an advance of treeline, reduction in forest cover due to drought, and increases in the distribution of shrub tundra. However, changes in snow cover still provided the dominant positive land surface feedback to atmospheric heating. This positive feedback was partially moderated by an increase in area burned in spruce forests and shrub tundra. Overall, increases in C storage in the vegetation and soils across the study region would act as a negative feedback to climate. By exploring these feedbacks, we can reach a more integrated understanding of the vulnerability of this region to changes in climate.

A user-targeted synthesis of the VALUE perfect predictor experiment

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Climate variability in China during the last millennium based on reconstructions and simulations

NASA Astrophysics Data System (ADS)

García-Bustamante, E.; Luterbacher, J.; Xoplaki, E.; Werner, J. P.; Jungclaus, J.; Zorita, E.; González-Rouco, J. F.; Fernández-Donado, L.; Hegerl, G.; Ge, Q.; Hao, Z.; Wagner, S.

2012-04-01

Multi-decadal to centennial climate variability in China during the last millennium is analysed. We compare the low frequency temperature and precipitation variations from proxy-based reconstructions and palaeo-simulations from climate models. Focusing on the regional responses to the global climate evolution is of high relevance due to the complexity of the interactions between physical mechanisms at different spatio-temporal scales and the potential severity of the derived multiple socio-economic impacts. China stands out as a particularly interesting region, not only due to its complex climatic features, ranging from the semiarid northwestern Tibetan Plateau to the tropical monsoon southeastern climates, but also because of its wealth of proxy data. However, comprehensive assessments of proxy- and model-based information about palaeo-climatic variations in China are, to our knowledge, still lacking. In addition, existing studies depict a general lack of agreement between reconstructions and model simulations with respect to the amplitude and/or occurrence of warmer/colder and wetter/drier periods during the last millennium and the magnitude of the 20th century warming trend. Furthermore, these works are mainly focused on eastern China regions that show a denser proxy data coverage. We investigate how last millennium palaeo-runs compare to independent evidences from an unusual large number of proxy reconstructions over the study area by employing state-of-the-art palaeo-simulations with multi-member ensembles from the CMIP5/PMIP3 project. This shapes an ideal frame for the evaluation of the uncertainties associated to internal and intermodel model variability. Preliminary results indicate that despite the strong regional and seasonal dependencies, temperature reconstructions in China evidence coherent variations among all regions at centennial scale, especially during the last 500 years. The spatial consistency of low frequency temperature changes is an interesting aspect and of relevance for the assessment of forced climatic responses in China. The comparison between reconstructions and simulations from climate models show that, apart from the 20th century warming trend, the variance of the reconstructed mean China temperature lies in the envelope (uncertainty range) spanned by the temperature simulations. The uncertainty arises from the internal (multi-member ensembles) and the inter-model variability. Centennial variations tend to be broadly synchronous in the reconstructions and the simulations. However, the simulations show a delay of the warm period 1000-1300 AD. This warm medieval period both in the simulations and the reconstructions is followed by cooling till 1800 AD. Based on the simulations, the recent warming is not unprecedented and is comparable to the medieval warming. Further steps of this study will address the individual contribution of anthropogenic and natural forcings on climate variability and change during the last millennium in China. We will make use of of models that provide runs including single forcings (fingerprints) for the attribution of climate variations from decadal to multi-centennial time scales. With this aim, we will implement statistical techniques for the detection of optimal signal-to-noise-ratio between external forcings and internal variability of reconstructed temperatures and precipitation. To apply these approaches the uncertainties associated with both reconstructions and simulations will be estimated. The latter will shed some light into the mechanisms behind current climate evolution and will help to constrain uncertainties in the sensitivity of model simulations to increasing CO2 scenarios of future climate change. This work will also contribute to the overall aims of the PAGES 2k initiative in Asia (http://www.pages.unibe.ch/workinggroups/2k-network)

Towards More Comprehensive Projections of Urban Heat-Related Mortality: Estimates for New York City under Multiple Population, Adaptation, and Climate Scenarios

PubMed Central

Petkova, Elisaveta P.; Vink, Jan K.; Horton, Radley M.; Gasparrini, Antonio; Bader, Daniel A.; Francis, Joe D.; Kinney, Patrick L.

2016-01-01

Background: High temperatures have substantial impacts on mortality and, with growing concerns about climate change, numerous studies have developed projections of future heat-related deaths around the world. Projections of temperature-related mortality are often limited by insufficient information to formulate hypotheses about population sensitivity to high temperatures and future demographics. Objectives: The present study derived projections of temperature-related mortality in New York City by taking into account future patterns of adaptation or demographic change, both of which can have profound influences on future health burdens. Methods: We adopted a novel approach to modeling heat adaptation by incorporating an analysis of the observed population response to heat in New York City over the course of eight decades. This approach projected heat-related mortality until the end of the 21st century based on observed trends in adaptation over a substantial portion of the 20th century. In addition, we incorporated a range of new scenarios for population change until the end of the 21st century. We then estimated future heat-related deaths in New York City by combining the changing temperature–mortality relationship and population scenarios with downscaled temperature projections from the 33 global climate models (GCMs) and two Representative Concentration Pathways (RCPs). Results: The median number of projected annual heat-related deaths across the 33 GCMs varied greatly by RCP and adaptation and population change scenario, ranging from 167 to 3,331 in the 2080s compared with 638 heat-related deaths annually between 2000 and 2006. Conclusions: These findings provide a more complete picture of the range of potential future heat-related mortality risks across the 21st century in New York City, and they highlight the importance of both demographic change and adaptation responses in modifying future risks. Citation: Petkova EP, Vink JK, Horton RM, Gasparrini A, Bader DA, Francis JD, Kinney PL. 2017. Towards more comprehensive projections of urban heat-related mortality: estimates for New York City under multiple population, adaptation, and climate scenarios. Environ Health Perspect 125:47–55; http://dx.doi.org/10.1289/EHP166 PMID:27337737

Towards More Comprehensive Projections of Urban Heat-Related Mortality: Estimates for New York City under Multiple Population, Adaptation, and Climate Scenarios.

PubMed

Petkova, Elisaveta P; Vink, Jan K; Horton, Radley M; Gasparrini, Antonio; Bader, Daniel A; Francis, Joe D; Kinney, Patrick L

2017-01-01

High temperatures have substantial impacts on mortality and, with growing concerns about climate change, numerous studies have developed projections of future heat-related deaths around the world. Projections of temperature-related mortality are often limited by insufficient information to formulate hypotheses about population sensitivity to high temperatures and future demographics. The present study derived projections of temperature-related mortality in New York City by taking into account future patterns of adaptation or demographic change, both of which can have profound influences on future health burdens. We adopted a novel approach to modeling heat adaptation by incorporating an analysis of the observed population response to heat in New York City over the course of eight decades. This approach projected heat-related mortality until the end of the 21st century based on observed trends in adaptation over a substantial portion of the 20th century. In addition, we incorporated a range of new scenarios for population change until the end of the 21st century. We then estimated future heat-related deaths in New York City by combining the changing temperature-mortality relationship and population scenarios with downscaled temperature projections from the 33 global climate models (GCMs) and two Representative Concentration Pathways (RCPs). The median number of projected annual heat-related deaths across the 33 GCMs varied greatly by RCP and adaptation and population change scenario, ranging from 167 to 3,331 in the 2080s compared with 638 heat-related deaths annually between 2000 and 2006. These findings provide a more complete picture of the range of potential future heat-related mortality risks across the 21st century in New York City, and they highlight the importance of both demographic change and adaptation responses in modifying future risks. Citation: Petkova EP, Vink JK, Horton RM, Gasparrini A, Bader DA, Francis JD, Kinney PL. 2017. Towards more comprehensive projections of urban heat-related mortality: estimates for New York City under multiple population, adaptation, and climate scenarios. Environ Health Perspect 125:47-55; http://dx.doi.org/10.1289/EHP166.

An assessment of anthropogenic and climatic stressors on estuaries using a spatio-temporal GIS-modelling approach for sustainability: Towamba estuary, southeastern Australia.

PubMed

Al-Nasrawi, Ali K M; Hamylton, Sarah M; Jones, Brian G

2018-06-03

Monitoring estuarine ecological-geomorphological dynamics has become a crucial aspect of studying the impacts of climate change and worldwide infrastructure development in coastal zones. Together, these factors have changed the natural eco-geomorphic processes that affect estuarine regimes and comprehensive modelling of coastal resources can assist managers to make appropriate decisions about their sustainable use. This study has utilised Towamba estuary (southeastern NSW, Australia), to demonstrate the value and priority of modelling estuarine dynamism as a measure of the rates and consequences of eco-geomorphic changes. This research employs several geoinformatic modelling approaches over time to investigate and assess how climate change and human activities have altered this estuarine eco-geomorphic setting. Multitemporal trend/change analysis of sediment delivery, shoreline positions and land cover, determined from fieldwork and GIS analysis of remote sensing datasets, shows significant spatio-temporal changes to the elevation and areal extent of sedimentary facies in the Towamba estuary over the past 65 years. Geomorphic growth (~ 2600 m 2 annually) has stabilised the estuarine habitats, particularly within native vegetation, salt marsh and mangrove areas. Geomorphic changes have occurred because of a combination of sediment runoff from the mostly unmodified terrestrial catchment, nearshore processes (ocean dynamics) and human activities. The construction of GIS models, verified with water and sediment samples, can characterise physical processes and quantify changes within the estuarine ecosystem. Such robust models will allow resource managers to evaluate the potential effects of changes to the current coastal ecosystems.

Corporate funding and ideological polarization about climate change

PubMed Central

Farrell, Justin

2016-01-01

Drawing on large-scale computational data and methods, this research demonstrates how polarization efforts are influenced by a patterned network of political and financial actors. These dynamics, which have been notoriously difficult to quantify, are illustrated here with a computational analysis of climate change politics in the United States. The comprehensive data include all individual and organizational actors in the climate change countermovement (164 organizations), as well as all written and verbal texts produced by this network between 1993–2013 (40,785 texts, more than 39 million words). Two main findings emerge. First, that organizations with corporate funding were more likely to have written and disseminated texts meant to polarize the climate change issue. Second, and more importantly, that corporate funding influences the actual thematic content of these polarization efforts, and the discursive prevalence of that thematic content over time. These findings provide new, and comprehensive, confirmation of dynamics long thought to be at the root of climate change politics and discourse. Beyond the specifics of climate change, this paper has important implications for understanding ideological polarization more generally, and the increasing role of private funding in determining why certain polarizing themes are created and amplified. Lastly, the paper suggests that future studies build on the novel approach taken here that integrates large-scale textual analysis with social networks. PMID:26598653

Corporate funding and ideological polarization about climate change.

PubMed

Farrell, Justin

2016-01-05

Drawing on large-scale computational data and methods, this research demonstrates how polarization efforts are influenced by a patterned network of political and financial actors. These dynamics, which have been notoriously difficult to quantify, are illustrated here with a computational analysis of climate change politics in the United States. The comprehensive data include all individual and organizational actors in the climate change countermovement (164 organizations), as well as all written and verbal texts produced by this network between 1993-2013 (40,785 texts, more than 39 million words). Two main findings emerge. First, that organizations with corporate funding were more likely to have written and disseminated texts meant to polarize the climate change issue. Second, and more importantly, that corporate funding influences the actual thematic content of these polarization efforts, and the discursive prevalence of that thematic content over time. These findings provide new, and comprehensive, confirmation of dynamics long thought to be at the root of climate change politics and discourse. Beyond the specifics of climate change, this paper has important implications for understanding ideological polarization more generally, and the increasing role of private funding in determining why certain polarizing themes are created and amplified. Lastly, the paper suggests that future studies build on the novel approach taken here that integrates large-scale textual analysis with social networks.

Chapter 11: City-Wide Collaborations for Urban Climate Education

NASA Technical Reports Server (NTRS)

Snyder, Steven; Hoffstadt, Rita Mukherjee; Allen, Lauren B.; Crowley, Kevin; Bader, Daniel A.; Horton, Radley M.

2014-01-01

Although cities cover only 2 percent of the Earth's surface, more than 50 percent of the world's people live in urban environments, collectively consuming 75 percent of the Earth's resources. Because of their population densities, reliance on infrastructure, and role as centers of industry, cities will be greatly impacted by, and will play a large role in, the reduction or exacerbation of climate change. However, although urban dwellers are becoming more aware of the need to reduce their carbon usage and to implement adaptation strategies, education efforts on these strategies have not been comprehensive. To meet the needs of an informed and engaged urban population, a more systemic, multiplatform and coordinated approach is necessary. The Climate and Urban Systems Partnership (CUSP) is designed to explore and address this challenge. Spanning four cities-Philadelphia, New York, Pittsburgh, and Washington, DC-the project is a partnership between the Franklin Institute, the Columbia University Center for Climate Systems Research, the University of Pittsburgh Learning Research and Development Center, Carnegie Museum of Natural History, New York Hall of Science, and the Marian Koshland Science Museum of the National Academy of Sciences. The partnership is developing a comprehensive, interdisciplinary network to educate urban residents about climate science and the urban impacts of climate change.

Persistence and diversification of the Holarctic shrew, Sorex tundrensis (Family Soricidae), in response to climate change

USGS Publications Warehouse

Hope, A.G.; Waltari, Eric; Fedorov, V.B.; Goropashnaya, A.V.; Talbot, S.L.; Cook, J.A.

2011-01-01

Environmental processes govern demography, species movements, community turnover and diversification and yet in many respects these dynamics are still poorly understood at high latitudes. We investigate the combined effects of climate change and geography through time for a widespread Holarctic shrew, Sorex tundrensis. We include a comprehensive suite of closely related outgroup taxa and three independent loci to explore phylogeographic structure and historical demography. We then explore the implications of these findings for other members of boreal communities. The tundra shrew and its sister species, the Tien Shan shrew (Sorex asper), exhibit strong geographic population structure across Siberia and into Beringia illustrating local centres of endemism that correspond to Late Pleistocene refugia. Ecological niche predictions for both current and historical distributions indicate a model of persistence through time despite dramatic climate change. Species tree estimation under a coalescent process suggests that isolation between populations has been maintained across timeframes deeper than the periodicity of Pleistocene glacial cycling. That some species such as the tundra shrew have a history of persistence largely independent of changing climate, whereas other boreal species shifted their ranges in response to climate change, highlights the dynamic processes of community assembly at high latitudes. ?? 2011 Blackwell Publishing Ltd.

Triassic–Jurassic climate in continental high-latitude Asia was dominated by obliquity-paced variations (Junggar Basin, Ürümqi, China)

PubMed Central

Sha, Jingeng; Olsen, Paul E.; Pan, Yanhong; Xu, Daoyi; Wang, Yaqiang; Zhang, Xiaolin; Yao, Xiaogang; Vajda, Vivi

2015-01-01

Empirical constraints on orbital gravitational solutions for the Solar System can be derived from the Earth’s geological record of past climates. Lithologically based paleoclimate data from the thick, coal-bearing, fluvial-lacustrine sequences of the Junggar Basin of Northwestern China (paleolatitude ∼60°) show that climate variability of the warm and glacier-free high latitudes of the latest Triassic–Early Jurassic (∼198–202 Ma) Pangea was strongly paced by obliquity-dominated (∼40 ky) orbital cyclicity, based on an age model using the 405-ky cycle of eccentricity. In contrast, coeval low-latitude continental climate was much more strongly paced by climatic precession, with virtually no hint of obliquity. Although this previously unknown obliquity dominance at high latitude is not necessarily unexpected in a high CO2 world, these data deviate substantially from published orbital solutions in period and amplitude for eccentricity cycles greater than 405 ky, consistent with chaotic diffusion of the Solar System. In contrast, there are indications that the Earth–Mars orbital resonance was in today’s 2-to-1 ratio of eccentricity to inclination. These empirical data underscore the need for temporally comprehensive, highly reliable data, as well as new gravitational solutions fitting those data. PMID:25759439

Triassic-Jurassic climate in continental high-latitude Asia was dominated by obliquity-paced variations (Junggar Basin, Ürümqi, China).

PubMed

Sha, Jingeng; Olsen, Paul E; Pan, Yanhong; Xu, Daoyi; Wang, Yaqiang; Zhang, Xiaolin; Yao, Xiaogang; Vajda, Vivi

2015-03-24

Empirical constraints on orbital gravitational solutions for the Solar System can be derived from the Earth's geological record of past climates. Lithologically based paleoclimate data from the thick, coal-bearing, fluvial-lacustrine sequences of the Junggar Basin of Northwestern China (paleolatitude ∼60°) show that climate variability of the warm and glacier-free high latitudes of the latest Triassic-Early Jurassic (∼198-202 Ma) Pangea was strongly paced by obliquity-dominated (∼40 ky) orbital cyclicity, based on an age model using the 405-ky cycle of eccentricity. In contrast, coeval low-latitude continental climate was much more strongly paced by climatic precession, with virtually no hint of obliquity. Although this previously unknown obliquity dominance at high latitude is not necessarily unexpected in a high CO2 world, these data deviate substantially from published orbital solutions in period and amplitude for eccentricity cycles greater than 405 ky, consistent with chaotic diffusion of the Solar System. In contrast, there are indications that the Earth-Mars orbital resonance was in today's 2-to-1 ratio of eccentricity to inclination. These empirical data underscore the need for temporally comprehensive, highly reliable data, as well as new gravitational solutions fitting those data.

Evaluation of the National Solar Radiation Database (NSRDB) Using Ground-Based Measurements

NASA Astrophysics Data System (ADS)

Xie, Y.; Sengupta, M.; Habte, A.; Lopez, A.

2017-12-01

Solar resource is essential for a wide spectrum of applications including renewable energy, climate studies, and solar forecasting. Solar resource information can be obtained from ground-based measurement stations and/or from modeled data sets. While measurements provide data for the development and validation of solar resource models and other applications modeled data expands the ability to address the needs for increased accuracy and spatial and temporal resolution. The National Renewable Energy Laboratory (NREL) has developed and regular updates modeled solar resource through the National Solar Radiation Database (NSRDB). The recent NSRDB dataset was developed using the physics-based Physical Solar Model (PSM) and provides gridded solar irradiance (global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance) at a 4-km by 4-km spatial and half-hourly temporal resolution covering 18 years from 1998-2015. A comprehensive validation of the performance of the NSRDB (1998-2015) was conducted to quantify the accuracy of the spatial and temporal variability of the solar radiation data. Further, the study assessed the ability of NSRDB (1998-2015) to accurately capture inter-annual variability, which is essential information for solar energy conversion projects and grid integration studies. Comparisons of the NSRDB (1998-2015) with nine selected ground-measured data were conducted under both clear- and cloudy-sky conditions. These locations provide a high quality data covering a variety of geographical locations and climates. The comparison of the NSRDB to the ground-based data demonstrated that biases were within +/- 5% for GHI and +/-10% for DNI. A comprehensive uncertainty estimation methodology was established to analyze the performance of the gridded NSRDB and includes all sources of uncertainty at various time-averaged periods, a method that is not often used in model evaluation. Further, the study analyzed the inter-annual and mean-anomaly of the 18 years of solar radiation data. This presentation will outline the validation methodology and provide detailed results of the comparison.

Understanding Emissions in East Asia - The KORUS 2015 Emissions Inventory

NASA Astrophysics Data System (ADS)

Woo, J. H.; Kim, Y.; Park, R.; Choi, Y.; Simpson, I. J.; Emmons, L. K.; Streets, D. G.

2017-12-01

The air quality over Northeast Asia have been deteriorated for decades due to high population and energy use in the region. Despite of more stringent air pollution control policies by the governments, air quality over the region seems not been improved as much - even worse sometimes. The needs of more scientific understanding of inter-relationship among emissions, transport, chemistry over the region are much higher to effectively protect public health and ecosystems. Two aircraft filed campaigns targeting year 2016, MAPS-Seoul and KORUS-AQ, have been organized to study the air quality of over Korea and East Asia relating to chemical evolution, emission inventories, trans-boundary contribution, and satellite application. We developed a new East-Asia emissions inventory, named KORUS2015, based on NIER/KU-CREATE (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment), in support of the filed campaigns. For anthropogenic emissions, it has 54 fuel classes, 201 sub-sectors and 13 pollutants, including CO2, SO2, NOx, CO, NMVOC, NH3, PM10, and PM2.5. Since the KORUS2015 emissions framework was developed using the integrated climate and air quality assessment modeling framework (i.e. GAINS) and is fully connected with the comprehensive emission processing/modeling systems (i.e. SMOKE, KU-EPS, and MEGAN), it can be effectively used to support atmospheric field campaigns for science and policy. During the field campaigns, we are providing modeling emissions inventory to participating air quality models, such as CMAQ, WRF-Chem, CAMx, GEOS-Chem, MOZART, for forecasting and post-analysis modes. Based on initial assessment of those results, we are improving our emissions, such as VOC speciation, biogenic VOCs modeling. From the 2nditeration between emissions and modeling/measurement, further analysis results will be presented at the conference. Acknowledgements : This subject is supported by Korea Ministry of Environment as "Climate Change Correspondence Program." This work was supported under the framework of national strategy project on fine particulate matters by Ministry of Science, ICT and Future Planning.

Foundations and Comprehensive Community Initiatives: The Challenges of Partnership. Discussion Paper.

ERIC Educational Resources Information Center

Brown, Prudence; Garg, Sunil

Against a backdrop of increasing localization of responsibilities for human services and community development, and in a climate of diminished resources for these activities, foundations have explored the comprehensive community initiative (CCI) as a strategy to direct support toward improved well-being for children and families. This discussion…

Relationships among Safety Climate, Safety Behavior, and Safety Outcomes for Ethnic Minority Construction Workers

PubMed Central

Lyu, Sainan; Chan, Albert P. C.; Wong, Francis K. W.

2018-01-01

In many countries, it is common practice to attract and employ ethnic minority (EM) or migrant workers in the construction industry. This primarily occurs in order to alleviate the labor shortage caused by an aging workforce with a lack of new entrants. Statistics show that EM construction workers are more likely to have occupational fatal and nonfatal injuries than their local counterparts; however, the mechanism underlying accidents and injuries in this vulnerable population has been rarely examined. This study aims to investigate relationships among safety climate, safety behavior, and safety outcomes for EM construction workers. To this end, a theoretical research model was developed based on a comprehensive review of the current literature. In total, 289 valid questionnaires were collected face-to-face from 223 Nepalese construction workers and 56 Pakistani construction workers working on 15 construction sites in Hong Kong. Structural equation modelling was employed to validate the constructs and test the hypothesized model. Results show that there were significant positive relationships between safety climate and safety behaviors, and significant negative relationships between safety behaviors and safety outcomes for EM construction workers. This research contributes to the literature regarding EM workers by providing empirical evidence of the mechanisms by which safety climate affects safety behaviors and outcomes. It also provides insights in order to help the key stakeholders formulate safety strategies for EM workers in many areas where numerous EM workers are employed, such as in the U.S., the UK, Australia, Singapore, Malaysia, and the Middle East. PMID:29522503

Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

NASA Astrophysics Data System (ADS)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

Applying a systems approach to assess carbon emission reductions from climate change mitigation in Mexico’s forest sector

NASA Astrophysics Data System (ADS)

Olguin, Marcela; Wayson, Craig; Fellows, Max; Birdsey, Richard; Smyth, Carolyn E.; Magnan, Michael; Dugan, Alexa J.; Mascorro, Vanessa S.; Alanís, Armando; Serrano, Enrique; Kurz, Werner A.

2018-03-01

The Paris Agreement of the United Nation Framework Convention on Climate Change calls for a balance of anthropogenic greenhouse emissions and removals in the latter part of this century. Mexico indicated in its Intended Nationally Determined Contribution and its Climate Change Mid-Century Strategy that the land sector will contribute to meeting GHG emission reduction goals. Since 2012, the Mexican government through its National Forestry Commission, with international financial and technical support, has been developing carbon dynamics models to explore climate change mitigation options in the forest sector. Following a systems approach, here we assess the biophysical mitigation potential of forest ecosystems, harvested wood products and their substitution benefits (i.e. the change in emissions resulting from substitution of wood for more emissions-intensive products and fossil fuels), for policy alternatives considered by the Mexican government, such as a net zero deforestation rate and sustainable forest management. We used available analytical frameworks (Carbon Budget Model of the Canadian Forest Sector and a harvested wood products model), parameterized with local input data in two contrasting Mexican states. Using information from the National Forest Monitoring System (e.g. forest inventories, remote sensing, disturbance data), we demonstrate that activities aimed at reaching a net-zero deforestation rate can yield significant CO2e mitigation benefits by 2030 and 2050 relative to a baseline scenario (‘business as usual’), but if combined with increasing forest harvest to produce long-lived products and substitute more energy-intensive materials, emissions reductions could also provide other co-benefits (e.g. jobs, illegal logging reduction). We concluded that the relative impact of mitigation activities is locally dependent, suggesting that mitigation strategies should be designed and implemented at sub-national scales. We were also encouraged about the ability of the modeling framework to effectively use Mexico’s data, and showed the need to include multiple sectors and types of collaborators (scientific and policy-maker communities) to design more comprehensive portfolios for climate change mitigation.

Gimme shelter--the relative sensitivity of parasitic nematodes with direct and indirect life cycles to climate change.

PubMed

Molnár, Péter K; Dobson, Andrew P; Kutz, Susan J

2013-11-01

Climate change is expected to alter the dynamics of host-parasite systems globally. One key element in developing predictive models for these impacts is the life cycle of the parasite. It is, for example, commonly assumed that parasites with an indirect life cycle would be more sensitive to changing environmental conditions than parasites with a direct life cycle due to the greater chance that at least one of their obligate host species will go extinct. Here, we challenge this notion by contrasting parasitic nematodes with a direct life cycle against those with an indirect life cycle. Specifically, we suggest that behavioral thermoregulation by the intermediate host may buffer the larvae of indirectly transmitted parasites against temperature extremes, and hence climate warming. We term this the 'shelter effect'. Formalizing each life cycle in a comprehensive model reveals a fitness advantage for the direct life cycle over the indirect life cycle at low temperatures, but the shelter effect reverses this advantage at high temperatures. When examined for seasonal environments, the models suggest that climate warming may in some regions create a temporal niche in mid-summer that excludes parasites with a direct life cycle, but allows parasites with an indirect life cycle to persist. These patterns are amplified if parasite larvae are able to manipulate their intermediate host to increase ingestion probability by definite hosts. Furthermore, our results suggest that exploiting the benefits of host sheltering may have aided the evolution of indirect life cycles. Our modeling framework utilizes the Metabolic Theory of Ecology to synthesize the complexities of host behavioral thermoregulation and its impacts on various temperature-dependent parasite life history components in a single measure of fitness, R0 . It allows quantitative predictions of climate change impacts, and is easily generalized to many host-parasite systems. © 2013 John Wiley & Sons Ltd.

The impact of SciDAC on US climate change research and the IPCCAR4

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

Wehner, Michael

2005-07-08

SciDAC has invested heavily in climate change research. We offer a candid opinion as to the impact of the DOE laboratories' SciDAC projects on the upcoming Fourth Assessment Report of the Intergovernmental Panel on Climate Change. As a result of the direct importance of climate change to society, climate change research is highly coordinated at the international level. The Intergovernmental Panel on Climate Change (IPCC) is charged with providing regular reports on the state of climate change research to government policymakers. These reports are the product of thousands of scientists efforts. A series of reviews involving both scientists and policymakersmore » make them among the most reviewed documents produced in any scientific field. The high profile of these reports acts a driver to many researchers in the climate sciences. The Fourth Assessment Report (AR4) is scheduled to be released in 2007. SciDAC sponsored research has enabled the United States climate modeling community to make significant contributions to this report. Two large multi-Laboratory SciDAC projects are directly relevant to the activities of the IPCC. The first, entitled ''Collaborative Design and Development of the Community Climate System Model for Terascale Computers'', has made important software contributions to the recently released third version of the Community Climate System Model (CCSM3.0) developed at the National Center for Atmospheric Research. This is a multi-institutional project involving Los Alamos National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory, Argonne National Laboratory, Lawrence Livermore National Laboratory and the National Center for Atmospheric Research. The original principal investigators were Robert Malone and John B. Drake. The current principal investigators are Phil Jones and John B. Drake. The second project, entitled ''Earth System Grid II: Turning Climate Datasets into Community Resources'' aims to facilitate the distribution of the copious amounts of data produced by coupled climate model integrations to the general scientific community. This is also a multi-institutional project involving Argonne National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory and the National Center for Atmospheric Research. The principal investigators are Ian Foster, Don Middleton and Dean Williams. Perhaps most significant among the activities of the ''Collaborative Design'', project was the development of an efficient multi-processor coupling package. CCSM3.0 is an extraordinarily complicated physics code. The fully coupled model consists of separate submodels of the atmosphere, ocean, sea ice and land. In addition, comprehensive biogeochemistry and atmospheric chemistry submodels are under intensive current development. Each of these submodels is a large and sophisticated program in its own right. Furthermore, in the coupled model, each of the submodels, including the coupler, is a separate multiprocessor executable program. The coupler package must efficiently coordinate the communication as well as interpolate or aggregate information between these programs. This regridding function is necessary because each major subsystem (air, water or surface) is allowed to have its own independent grid.« less

Case Studies of Water Utility Climate Change Vulnerability Assessment [External Review Draft Report

EPA Science Inventory

This report presents a series of case studies describing the approaches taken by four water utilities in the United States to assess their vulnerability to climate change. The report is not intended to be a comprehensive listing of assessment approaches or utilities conducting v...

A Comprehensive Needs Assessment To Facilitate Prevention of School Drop Out and Violence.

ERIC Educational Resources Information Center

Hunt, Mary Ellen; Meyers, Joel; Davies, Gwen; Meyers, Barbara; Grogg, Kathryn Rogers; Neel, John

2002-01-01

Study addresses school violence and dropout and proposes that the underlying factor of school connectedness/school climate should guide preventive and intervention efforts. Principal components analysis revealed five distinct factors: school connectedness/positive school climate, causes of violence, causes of school dropout, interventions for drop…

Asset Management and Sustainability at the University of Richmond

ERIC Educational Resources Information Center

Burchard, Wendy

2009-01-01

In January 2008, Ed Ayers, president of the University of Richmond, signed the American College and University Presidents' Climate Commitment. This commits the university to creating a comprehensive action plan to move toward climate neutrality. Even before "sustainability" became one of the university's overall goals, Information Services (IS)…

Using an autologistic regression model to identify spatial risk factors and spatial risk patterns of hand, foot and mouth disease (HFMD) in Mainland China

PubMed Central

2014-01-01

Background There have been large-scale outbreaks of hand, foot and mouth disease (HFMD) in Mainland China over the last decade. These events varied greatly across the country. It is necessary to identify the spatial risk factors and spatial distribution patterns of HFMD for public health control and prevention. Climate risk factors associated with HFMD occurrence have been recognized. However, few studies discussed the socio-economic determinants of HFMD risk at a space scale. Methods HFMD records in Mainland China in May 2008 were collected. Both climate and socio-economic factors were selected as potential risk exposures of HFMD. Odds ratio (OR) was used to identify the spatial risk factors. A spatial autologistic regression model was employed to get OR values of each exposures and model the spatial distribution patterns of HFMD risk. Results Results showed that both climate and socio-economic variables were spatial risk factors for HFMD transmission in Mainland China. The statistically significant risk factors are monthly average precipitation (OR = 1.4354), monthly average temperature (OR = 1.379), monthly average wind speed (OR = 1.186), the number of industrial enterprises above designated size (OR = 17.699), the population density (OR = 1.953), and the proportion of student population (OR = 1.286). The spatial autologistic regression model has a good goodness of fit (ROC = 0.817) and prediction accuracy (Correct ratio = 78.45%) of HFMD occurrence. The autologistic regression model also reduces the contribution of the residual term in the ordinary logistic regression model significantly, from 17.25 to 1.25 for the odds ratio. Based on the prediction results of the spatial model, we obtained a map of the probability of HFMD occurrence that shows the spatial distribution pattern and local epidemic risk over Mainland China. Conclusions The autologistic regression model was used to identify spatial risk factors and model spatial risk patterns of HFMD. HFMD occurrences were found to be spatially heterogeneous over the Mainland China, which is related to both the climate and socio-economic variables. The combination of socio-economic and climate exposures can explain the HFMD occurrences more comprehensively and objectively than those with only climate exposures. The modeled probability of HFMD occurrence at the county level reveals not only the spatial trends, but also the local details of epidemic risk, even in the regions where there were no HFMD case records. PMID:24731248

ENSO activity during the last climate cycle using IFA

NASA Astrophysics Data System (ADS)

Leduc, Guillaume; Vidal, Laurence; Thirumalai, Kaustubh

2017-04-01

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

A first approach to calculate BIOCLIM variables and climate zones for Antarctica

NASA Astrophysics Data System (ADS)

Wagner, Monika; Trutschnig, Wolfgang; Bathke, Arne C.; Ruprecht, Ulrike

2018-02-01

For testing the hypothesis that macroclimatological factors determine the occurrence, biodiversity, and species specificity of both symbiotic partners of Antarctic lecideoid lichens, we present a first approach for the computation of the full set of 19 BIOCLIM variables, as available at http://www.worldclim.org/ for all regions of the world with exception of Antarctica. Annual mean temperature (Bio 1) and annual precipitation (Bio 12) were chosen to define climate zones of the Antarctic continent and adjacent islands as required for ecological niche modeling (ENM). The zones are based on data for the years 2009-2015 which was obtained from the Antarctic Mesoscale Prediction System (AMPS) database of the Ohio State University. For both temperature and precipitation, two separate zonings were specified; temperature values were divided into 12 zones (named 1 to 12) and precipitation values into five (named A to E). By combining these two partitions, we defined climate zonings where each geographical point can be uniquely assigned to exactly one zone, which allows an immediate explicit interpretation. The soundness of the newly calculated climate zones was tested by comparison with already published data, which used only three zones defined on climate information from the literature. The newly defined climate zones result in a more precise assignment of species distribution to the single habitats. This study provides the basis for a more detailed continental-wide ENM using a comprehensive dataset of lichen specimens which are located within 21 different climate regions.

Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States.

PubMed

Auffhammer, Maximilian; Baylis, Patrick; Hausman, Catherine H

2017-02-21

It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond [Rose S, et al. (2014) Understanding the Social Cost of Carbon: A Technical Assessment ]. The empirical literature has shown significant increases in climate-driven impacts on overall consumption, yet has not focused on the cost implications of the increased intensity and frequency of extreme events driving peak demand, which is the highest load observed in a period. We use comprehensive, high-frequency data at the level of load balancing authorities to parameterize the relationship between average or peak electricity demand and temperature for a major economy. Using statistical models, we analyze multiyear data from 166 load balancing authorities in the United States. We couple the estimated temperature response functions for total daily consumption and daily peak load with 18 downscaled global climate models (GCMs) to simulate climate change-driven impacts on both outcomes. We show moderate and heterogeneous changes in consumption, with an average increase of 2.8% by end of century. The results of our peak load simulations, however, suggest significant increases in the intensity and frequency of peak events throughout the United States, assuming today's technology and electricity market fundamentals. As the electricity grid is built to endure maximum load, our findings have significant implications for the construction of costly peak generating capacity, suggesting additional peak capacity costs of up to 180 billion dollars by the end of the century under business-as-usual.

One multi-media environmental system with linkage between meteorology/ hydrology/ air quality models and water quality model

NASA Astrophysics Data System (ADS)

Tang, C.; Lynch, J. A.; Dennis, R. L.

2016-12-01

The biogeochemical processing of nitrogen and associated pollutants is driven by meteorological and hydrological processes in conjunction with pollutant loading. There are feedbacks between meteorology and hydrology that will be affected by land-use change and climate change. Changes in meteorology will affect pollutant deposition. It is important to account for those feedbacks and produce internally consistent simulations of meteorology, hydrology, and pollutant loading to drive the (watershed/water quality) biogeochemical models. In this study, the ecological response to emission reductions in streams in the Potomac watershed was evaluated. Firstly, we simulated the deposition by using the fully coupled Weather Research & Forecasting (WRF) model and the Community Multiscale Air Quality (CAMQ) model; secondly, we created the hydrological data by the offline linked Variable Infiltration Capacity (VIC) model and the WRF model. Lastly, we investigated the water quality by one comprehensive/environment model, namely the linkage of CMAQ, WRF, VIC and the Model of Acidification of Groundwater In Catchment (MAGIC) model from 2002 to 2010.The simulated results (such as NO3, SO4, and SBC) fit well to the observed values. The linkage provides a generally accurate, well-tested tool for evaluating sensitivities to varying meteorology and environmental changes on acidification and other biogeochemical processes, with capability to comprehensively explore strategic policy and management design.

The Atmospheric Boundary Layer

NASA Astrophysics Data System (ADS)

Garratt, J. R.

1994-05-01

A comprehensive and lucid account of the physics and dynamics of the lowest one to two kilometers of the Earth's atmosphere in direct contact with the Earth's surface, known as the atmospheric boundary layer (ABL). Dr. Garratt emphasizes the application of the ABL problems to numerical modeling of the climate, which makes this book unique among recent texts on the subject. He begins with a brief introduction to the ABL before leading to the development of mean and turbulence equations and the many scaling laws and theories that are the cornerstone of any serious ABL treatment. Modeling of the ABL is crucially dependent for its realism on the surface boundary conditions, so chapters four and five deal with aerodynamic and energy considerations, with attention given to both dry and wet land surfaces and the sea. The author next treats the structure of the clear-sky, thermally stratified ABL, including the convective and stable cases over homogeneous land, the marine ABL, and the internal boundary layer at the coastline. Chapter seven then extends this discussion to the cloudy ABL. This is particularly relevant to current research because the extensive stratocumulus regions over the subtropical oceans and stratus regions over the Arctic have been identified as key players in the climate system. In the final chapters, Dr. Garratt summarizes the book's material by discussing appropriate ABL and surface parameterization schemes in general circulation models of the atmosphere that are being used for climate stimulation.

The Response of Tropospheric Ozone to ENSO in Observations and a Chemistry-Climate Simulation

NASA Technical Reports Server (NTRS)

Oman, L. D.; Douglass, A. R.; Ziemke, J. R.; Waugh, D. W.; Rodriguez, J. M.; Nielsen, J. E.

2012-01-01

The El Nino-Southern Oscillation (ENSO) is the dominant mode of tropical variability on interannual time scales. ENSO appears to extend its influence into the chemical composition of the tropical troposphere. Recent results have revealed an ENSO induced wave-l anomaly in observed tropical tropospheric column ozone. This results in a dipole over the western and eastern tropical Pacific, whereby differencing the two regions produces an ozone anomaly with an extremely high correlation to the Nino 3.4 Index. We have successfully reproduced this result using the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 25 years. An examination of the modeled ozone field reveals the vertical contributions of tropospheric ozone to the column over the western and eastern Pacific region. We will show targeted comparisons with observations from NASA's Aura satellite Microwave Limb Sounder (MLS), and the Tropospheric Emissions Spectrometer (TES) to provide insight into the vertical structure of ozone changes. The tropospheric ozone response to ENSO could be a useful chemistry-climate model evaluation tool and should be considered in future modeling assessments.

Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States Climate Dynamics

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

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.

This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 x 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmentalmore » Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation’s performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.« less

Modelling land use change in the Ganga basin

NASA Astrophysics Data System (ADS)

Moulds, Simon; Mijic, Ana; Buytaert, Wouter

2014-05-01

Over recent decades the green revolution in India has driven substantial environmental change. Modelling experiments have identified northern India as a "hot spot" of land-atmosphere coupling strength during the boreal summer. However, there is a wide range of sensitivity of atmospheric variables to soil moisture between individual climate models. The lack of a comprehensive land use change dataset to force climate models has been identified as a major contributor to model uncertainty. This work aims to construct a monthly time series dataset of land use change for the period 1966 to 2007 for northern India to improve the quantification of regional hydrometeorological feedbacks. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the Aqua and Terra satellites provides near-continuous remotely sensed datasets from 2000 to the present day. However, the quality and availability of satellite products before 2000 is poor. To complete the dataset MODIS images are extrapolated back in time using the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) modelling framework, recoded in the R programming language to overcome limitations of the original interface. Non-spatial estimates of land use area published by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) for the study period, available on an annual, district-wise basis, are used as a direct model input. Land use change is allocated spatially as a function of biophysical and socioeconomic drivers identified using logistic regression. The dataset will provide an essential input to a high-resolution, physically-based land-surface model to generate the lower boundary condition to assess the impact of land use change on regional climate.

Essays on agricultural adaptation to climate change and ethanol market integration in the U.S

NASA Astrophysics Data System (ADS)

Aisabokhae, Ruth Ada

Climate factors like precipitation and temperature, being closely intertwined with agriculture, make a changing climate a big concern for the entire human race and its basic survival. Adaptation to climate is a long-running characteristic of agriculture evidenced by the varying types and forms of agricultural enterprises associated with differing climatic conditions. Nevertheless climate change poses a substantial, additional adaptation challenge for agriculture. Mitigation encompasses efforts to reduce the current and future extent of climate change. Biofuels production, for instance, expands agriculture's role in climate change mitigation. This dissertation encompasses adaptation and mitigation strategies as a response to climate change in the U.S. by examining comprehensively scientific findings on agricultural adaptation to climate change; developing information on the costs and benefits of select adaptations to examine what adaptations are most desirable, for which society can further devote its resources; and studying how ethanol prices are interrelated across, and transmitted within the U.S., and the markets that play an important role in these dynamics. Quantitative analysis using the Forestry and Agricultural Sector Optimization Model (FASOM) shows adaptation to be highly beneficial to agriculture. On-farm varietal and other adaptations contributions outweigh a mix shift northwards significantly, implying progressive technical change and significant returns to adaptation research and investment focused on farm management and varietal adaptations could be quite beneficial over time. Northward shift of corn-acre weighted centroids observed indicates that substantial production potential may shift across regions with the possibility of less production in the South, and more in the North, and thereby, potential redistribution of income. Time series techniques employed to study ethanol price dynamics show that the markets studied are co-integrated and strongly related, with the observable high levels of interaction between all nine cities. Information is transmitted rapidly between these markets. Price seems to be discovered (where shocks originate from) in regions of high demand and perhaps shortages, like Los Angeles and Chicago (metropolitan population centers). The Maximum Likelihood approach following Spiller and Huang's model however shows cities may not belong to the same economic market and the possibility of arbitrage does not exist between all markets.

Potential role of vegetation dynamics on recent extreme droughts over tropical South America

NASA Astrophysics Data System (ADS)

Wang, G.; Erfanian, A.; Fomenko, L.

2017-12-01

Tropical South America is a drought hot spot. In slightly over a decade (2005-2016), the region encountered three extreme droughts (2005, 2010, and 2016). Recurrent extreme droughts not only impact the region's eco-hydrology and socio-economy, but are also globally important as they can transform the planet's largest rainforest, the Amazon, from a carbon sink to a carbon source. Understanding drought drivers and mechanisms underlying extreme droughts in tropical South America can help better project the fate of the Amazon rainforest in a changing climate. In this study we use a regional climate model (RegCM4.3.4) coupled with a comprehensive land-surface model (CLM4.5) to study the present-day hydroclimate of the region, focusing specifically on what might have caused the frequent recurrence of extreme droughts. In the context of observation natural variability of the global oceanic forcing, we tackle the role of land-atmosphere interactions and ran the model with and without dynamic vegetation to study how vegetation dynamics and carbon-nitrogen cycles may have influenced the drought characteristics. Our results demonstrate skillful simulation of the South American climate in the model, and indicate substantial sensitivity of the region's hydroclimatology to vegetation dynamics. This presentation will compare the role of global oceanic forcing versus regional land surface feedback in the recent recurrent droughts, and will characterize the effects of vegetation dynamics in enhancing the drought severity. Preliminary results on future projections of the regional ecosystem and droughts perspective will be also presented.

Sensitivity and Response of Bhutanese Glaciers to Atmospheric Warming

NASA Technical Reports Server (NTRS)

Rupper, Summer; Schaefer, Joerg M.; Burgener, Landon K.; Koenig, Lora S.; Tsering, Karma; Cook, Edward

2013-01-01

Glacierized change in the Himalayas affects river-discharge, hydro-energy and agricultural production, and Glacial Lake Outburst Flood potential, but its quantification and extent of impacts remains highly uncertain. Here we present conservative, comprehensive and quantitative predictions for glacier area and meltwater flux changes in Bhutan, monsoonal Himalayas. In particular, we quantify the uncertainties associated with the glacier area and meltwater flux changes due to uncertainty in climate data, a critical problem for much of High Asia. Based on a suite of gridded climate data and a robust glacier melt model, our results show that glacier area and meltwater change projections can vary by an order of magnitude for different climate datasets. However, the most conservative results indicate that, even if climate were to remain at the present-day mean values, almost 10% of Bhutan s glacierized area would vanish and the meltwater flux would drop by as much as 30%. Under the conservative scenario of an additional 1 C regional warming, glacier retreat is going to continue until about 25% of Bhutan s glacierized area will have disappeared and the annual meltwater flux, after an initial spike, would drop by as much as 65%. Citation

Climate change and the rising cost of living for forests in the southwestern United States and beyond

NASA Astrophysics Data System (ADS)

Williams, P.; Allen, C. D.; Macalady, A. K.; Griffin, D.; Woodhouse, C. A.; Meko, D. M.; Swetnam, T. W.; Rauscher, S.; Seager, R.; Grissino-Mayer, H.; Dean, J.; Cook, E.; Gangodagamage, C.; Cai, M.; McDowell, N. G.

2012-12-01

As climate changes, drought may reduce tree productivity and survival across many forest ecosystems; however, the relative influence of specific climate parameters on forest decline is poorly understood. We derive a forest drought-stress index (FDSI) for the southwestern United States using a comprehensive tree-ring dataset representing CE 1000-2007. FDSI is approximately equally influenced by warm-season atmospheric moisture demand (largely controlled by temperature) and cold-season precipitation, together explaining 82% of FDSI variability. Correspondence between FDSI and measures of forest productivity, mortality, bark-beetle outbreak, and wildfire validate FDSI as a holistic indicator of forest vigor throughout the region. In fact, the exceptionally large burned areas in 2002, 2011, and 2012 were all predictable based upon FDSI. If atmospheric moisture demand continues increasing as projected by climate models, average forest drought stress levels by the 2050s will exceed those of the worst megadroughts in at least 1000 years. Collectively, these results foreshadow 21st century changes in southwestern forest structures and compositions, with a transition of southwestern forests, and perhaps water-limited forests globally, toward distributions unfamiliar to modern civilization.

A comprehensive solar energy system analysis data base in Huntsville, Alabama

NASA Technical Reports Server (NTRS)

Goddard, J. P.

1978-01-01

The history of a comprehensive solar energy system analysis data base developed by NASA/Marshall Space Flight Center and the University of Alabama is presented, along with its current status. The Marshall Information Retrieval and Data Storage (MIRADS) system was chosen for the data base, and feedback systems were arranged to cope with changes in the needs of the program management for the type of data gathered. The final structure of the data base consists of 22 files divided into 6 topical sections: summaries, climatological, utility rates, architectural, equipment, and economics. The data base offers help to the solar industry in two ways: it provides information and it serves as a model for users trying to establish the climatic and socioeconomic variables they should take into account when they examine a potential market for solar energy equipment.

Communicating Urban Climate Change

NASA Astrophysics Data System (ADS)

Snyder, S.; Crowley, K.; Horton, R.; Bader, D.; Hoffstadt, R.; Labriole, M.; Shugart, E.; Steiner, M.; Climate; Urban Systems Partnership

2011-12-01

While cities cover only 2% of the Earth's surface, over 50% of the world's people live in urban environments. Precisely because of their population density, cities can play a large role in reducing or exacerbating the global impact of climate change. The actions of cities could hold the key to slowing down climate change. Urban dwellers are becoming more aware of the need to reduce their carbon usage and to implement adaptation strategies. However, messaging around these strategies has not been comprehensive and adaptation to climate change requires local knowledge, capacity and a high level of coordination. Unless urban populations understand climate change and its impacts it is unlikely that cities will be able to successfully implement policies that reduce anthropogenic climate change. Informal and formal educational institutions in urban environments can serve as catalysts when partnering with climate scientists, educational research groups, and public policy makers to disseminate information about climate change and its impacts on urban audiences. The Climate and Urban Systems Partnership (CUSP) is an interdisciplinary network designed to assess and meet the needs and challenges of educating urban audiences about climate change. CUSP brings together organizations in Philadelphia, Pittsburgh, Queens, NY and Washington, DC to forge links with informal and formal education partners, city government, and policy makers. Together this network will create and disseminate learner-focused climate education programs and resources for urban audiences that, while distinct, are thematically and temporally coordinated, resulting in the communication of clear and consistent information and learning experiences about climate science to a wide public audience. Working at a community level CUSP will bring coordinated programming directly into neighborhoods presenting the issues of global climate change in a highly local context. The project is currently exploring a number of models for community programming and this session will present early results of these efforts while engaging participants in exploring approaches to connecting urban communities and their local concerns to the issues of global climate change.

Cholera in Cameroon, 2000-2012: Spatial and Temporal Analysis at the Operational (Health District) and Sub Climate Levels

PubMed Central

Liang, Song; Kracalik, Ian T.; Morris, Lillian; Blackburn, Jason K.; Mbam, Leonard M.; Ba Pouth, Simon Franky Baonga; Teboh, Andrew; Yang, Yang; Arabi, Mouhaman; Sugimoto, Jonathan D.; Morris, John Glenn

2016-01-01

Introduction Recurrent cholera outbreaks have been reported in Cameroon since 1971. However, case fatality ratios remain high, and we do not have an optimal understanding of the epidemiology of the disease, due in part to the diversity of Cameroon’s climate subzones and a lack of comprehensive data at the health district level. Methods/Findings A unique health district level dataset of reported cholera case numbers and related deaths from 2000–2012, obtained from the Ministry of Public Health of Cameroon and World Health Organization (WHO) country office, served as the basis for the analysis. During this time period, 43,474 cholera cases were reported: 1748 were fatal (mean annual case fatality ratio of 7.9%), with an attack rate of 17.9 reported cases per 100,000 inhabitants per year. Outbreaks occurred in three waves during the 13-year time period, with the highest case fatality ratios at the beginning of each wave. Seasonal patterns of illness differed strikingly between climate subzones (Sudano-Sahelian, Tropical Humid, Guinea Equatorial, and Equatorial Monsoon). In the northern Sudano-Sahelian subzone, highest number of cases tended to occur during the rainy season (July-September). The southern Equatorial Monsoon subzone reported cases year-round, with the lowest numbers during peak rainfall (July-September). A spatial clustering analysis identified multiple clusters of high incidence health districts during 2010 and 2011, which were the 2 years with the highest annual attack rates. A spatiotemporal autoregressive Poisson regression model fit to the 2010–2011 data identified significant associations between the risk of transmission and several factors, including the presence of major waterbody or highway, as well as the average daily maximum temperature and the precipitation levels over the preceding two weeks. The direction and/or magnitude of these associations differed between climate subzones, which, in turn, differed from national estimates that ignored subzones differences in climate variables. Conclusions/Significance The epidemiology of cholera in Cameroon differs substantially between climate subzones. Development of an optimal comprehensive country-wide control strategy for cholera requires an understanding of the impact of the natural and built environment on transmission patterns at the local level, particularly in the setting of ongoing climate change. PMID:27855171

The Co-evolution of Climate Models and the Intergovernmental Panel on Climate Change

NASA Astrophysics Data System (ADS)

Somerville, R. C.

2010-12-01

As recently as the 1950s, global climate models, or GCMs, did not exist, and the notion that man-made carbon dioxide might lead to significant climate change was not regarded as a serious possibility by most experts. Today, of course, the prospect or threat of exactly this type of climate change dominates the science and ranks among the most pressing issues confronting all mankind. Indeed, the prevailing scientific view throughout the first half of the twentieth century was that adding carbon dioxide to the atmosphere would have only a negligible effect on climate. The science of climate change caused by atmospheric carbon dioxide changes has thus undergone a genuine revolution. An extraordinarily rapid development of global climate models has also characterized this period, especially in the three decades since about 1980. In these three decades, the number of GCMs has greatly increased, and their physical and computational aspects have both markedly improved. Modeling progress has been enabled by many scientific advances, of course, but especially by a massive increase in available computer power, with supercomputer speeds increasing by roughly a factor of a million in the three decades from about 1980 to 2010. This technological advance has permitted a rapid increase in the physical comprehensiveness of GCMs as well as in spatial computational resolution. In short, GCMs have dramatically evolved over time, in exactly the same recent period as popular interest and scientific concern about anthropogenic climate change have markedly increased. In parallel, a unique international organization, the Intergovernmental Panel on Climate Change, or IPCC, has also recently come into being and also evolved rapidly. Today, the IPCC has become widely respected and globally influential. The IPCC was founded in 1988, and its history is thus even shorter than that of GCMs. Yet, its stature today is such that a series of IPCC reports assessing climate change science has already been endorsed by many leading scientific professional societies and academies of science worldwide. These reports are considered as definitive summaries of the state of the science. In 2007, in recognition of its exceptional accomplishments, the IPCC shared the Nobel Peace Prize equally with Al Gore. The present era is characterized not only by the reality and seriousness of human-caused climate change, but also by a young yet powerful science that enables us to understand much about the climate change that has occurred already and that awaits in the future. The development of GCMs is a critical part of the scientific story, and the development of the IPCC is a key factor in connecting the science to the perceptions and priorities of the global public and policymakers. GCMs and the IPCC have co-evolved and strongly influenced one another, as both scientists and the world at large have worked to confront the challenge of climate change.

Advanced Large Scale Cross Domain Temporal Topic Modeling Algorithms to Infer the Influence of Recent Research on IPCC Assessment Reports

NASA Astrophysics Data System (ADS)

Sleeman, J.; Halem, M.; Finin, T.; Cane, M. A.

2016-12-01

Approximately every five years dating back to 1989, thousands of climate scientists, research centers and government labs volunteer to prepare comprehensive Assessment Reports for the Intergovernmental Panel on Climate Change. These are highly curated reports distributed to 200 nation policy makers. There have been five IPCC Assessment Reports to date, the latest leading to a Paris Agreement in Dec. 2016 signed thus far by 172 nations to limit the amount of global Greenhouse gases emitted to producing no more than a 20 C warming of the atmosphere. These reports are a living evolving big data collection tracing 30 years of climate science research, observations, and model scenario intercomparisons. They contain more than 200,000 citations over a 30 year period that trace the evolution of the physical basis of climate science, the observed and predicted impact, risk and adaptation to increased greenhouse gases and mitigation approaches, pathways, policies for climate change. Document-topic and topic-term probability distributions are built from the vocabularies of the respective assessment report chapters and citations. Using Microsoft Bing, we retrieve 150,000 citations referenced across chapters and convert those citations to text. Using a word n-gram model based on a heterogeneous set of climate change terminology, lemmatization, noise filtering and stopword elimination, we calculate word frequencies for chapters and citations. Temporal document sets are built based on the assessment period. In addition to topic modeling, we employ cross domain correlation measures. Using the Jensen-Shannon divergence and Pearson correlation we build correlation matrices for chapter and citations topics. The shared vocabulary acts as the bridge between domains resulting in chapter-citation point pairs in space. Pairs are established based on a document-topic probability distribution. Each chapter and citation is associated with a vector of topics and based on the n most probable topics, we establish which chapter-citation pairs are most similar. We will perform posterior inferences based on Hastings -Metropolis simulated annealing MCMC algorithm to infer, from the evolution of topics starting from AR1 to AR4, assertions of topics for AR5 and potentially AR6.